Vermunt, J.K. (1991). Causal log-linear modelling with latent variables and missing data using LOGLAT. Voorburg: Hoofdafdeling Bevolkingsstatistieken, CBS.

Vermunt, J.K. (1993). LEM 0.1:Log-linear and event history analysis with missing data using the EM algorithms. Tilburg: Tilburg University.

Vermunt, J.K. (1997). LEM 1.0: A general program for the analysis of categorical data. Tilburg: Tilburg University. (download)

Vermunt, J.K. and Magidson, J. (2000). Latent GOLD User's Manual. 185 pages. Boston: Statistical Innovations Inc.

Vermunt, J.K. and Magidson, J. (2003). Addendum to Latent GOLD User's Guide: Upgrade for Version 3.0. 44 pages. Boston: Statistical Innovations Inc.

Vermunt, J.K. and Magidson, J. (2003). Latent GOLD Choice User's Guide.. 99 pages. Boston: Statistical Innovations Inc.

Vermunt, J.K. and Magidson, J. (2005). Latent GOLD 4.0 User's Guide, Belmont MA: Statistical Innovations Inc. (pdf).

Vermunt, J.K. and Magidson, J. (2005). Technical Guide for Latent GOLD 4.0: Basic and Advanced, Belmont MA: Statistical Innovations Inc.

Vermunt, J.K. and Magidson, J. (2005). Latent GOLD 4.0 Choice User's Guide, Belmont MA: Statistical Innovations Inc. (pdf).

Vermunt, J.K. and Magidson, J. (2005). Technical Guide for Latent GOLD Choice 4.0: Basic and Advanced, Belmont MA: Statistical Innovations Inc. (pdf).

Vermunt, J.K. and Magidson, J. (2008). LG-Syntax User’s Guide: Manual for Latent GOLD 4.5 Syntax Module, Belmont, MA: Statistical Innovations Inc.

Vermunt, J.K. and Magidson, J. (2013). Latent GOLD 5.0 Upgrade Manual, Belmont, MA: Statistical Innovations Inc. (pdf).

Vermunt, J.K. and Magidson, J. (2013). Technical Guide for Latent GOLD 5.0: Basic, Advanced, and Syntax. Belmont MA: Statistical Innovations Inc.

Vermunt, J.K. and Magidson, J. (2013). LG-Syntax User’s Guide: Manual for Latent GOLD 5.0 Syntax Module, Belmont, MA: Statistical Innovations Inc.

Vermunt, J.K. and Magidson, J. (2014). Upgrade Manual for Latent GOLD Choice 5.0: Basic, Advanced, and Syntax. Belmont, MA: Statistical Innovations Inc. (pdf).

Vermunt, J.K. and Magidson, J. (2016). Upgrade Manual for Latent GOLD 5.1. Belmont, MA: Statistical Innovations Inc. (pdf).

Vermunt, J.K. and Magidson, J. (2016). Technical Guide for Latent GOLD 5.1: Basic, Advanced, and Syntax. Belmont MA: Statistical Innovations Inc. (pdf).

Vermunt, J.K. and Magidson, J. (2016). LG-Syntax User’s Guide: Manual for Latent GOLD 5.1 Syntax Module, Belmont, MA: Statistical Innovations Inc.

Vermunt, J.K. and Magidson, J. (2021). Upgrade Manual for Latent GOLD Basic, Advanced/Syntax, and Choice Version 6.0. Arlington, MA: Statistical Innovations Inc. (pdf).

Vermunt, J.K. and Magidson, J. (2021). LG-Syntax User’s Guide: Manual for Latent GOLD Syntax Module Version 6.0, Arlington, MA: Statistical Innovations Inc. (pdf).

Books

Vermunt, J.K. (1996). Log-linear event history analysis: a general approach with missing data, latent variables, and unobserved heterogeneity, 350 pages, Tilburg: Tilburg University Press. Phd thesis. (pdf)

Vermunt, J.K. (1997). Log-linear models for event histories . Advanced Quantitative Techniques in the Social Sciences Series, vol 8., 348 pages, Thousand Oaks: Sage Publications. (pdf)

Articles and Commentaries in ISI Journals

Rees, K., and Vermunt, J.K. (1996). Event history analysis of author's reputations. Poetics, 23, 317-333. (pdf)

Pieters, R., Baumgarter H., Vermunt, J., and Bijmolt, T. (1999). Importance and similarity in the evolving citation network of the International Journal of Research in Marketing. International Journal of Research in Marketing, 16, 113-127. (pdf)

Rees, K., Vermunt, J.K., and Verboord, M. (1999). Cultural classifications under discussion. Latent class analysis of highbrow and lowbrow reading. Poetics, 26, 349-365. (pdf)

Vermunt, J.K. (1999). A general class of nonparametric models for ordinal categorical data. Sociological Methodology, 29, 187-223. (pdf)

Vermunt, J.K. Langeheine, R., and Böckenholt, U. (1999). Discrete-time discrete-state latent Markov models with time-constant and time-varying covariates. Journal of Educational and Behavioral Statistics, 24, 179-207. (pdf)

Van den Oord, E., and Vermunt, J.K. (2000). Testing for linkage disequilibrium, maternal effects, and imprinting with (in)complete case-parent triads using the computer program LEM. American Journal of Human Genetics, 66, 335-338. (pdf; LEM scripts)

Anderson, C., and Vermunt, J.K. (2000). Log-multiplicative association models as latent variable models for nominal and/or ordinal data. Sociological Methodology, 30, 81-122. (pdf)

Bassi, F., Hagenaars, J.A., Croon, M., and Vermunt, J.K. (2000). Estimating true changes when categorical panel data are affected by uncorrelated and correlated classification errors. Sociological Methods and Research, 29, 230-268. (pdf)

Vossen, A., and Vermunt, J.K. (2000) Young adult's preferences regarding the partner's age, and the importance of age as a partner choice determinant. Genus, 56, 177-201.(pdf)

Van Poppel, F., Liefbroer, A.C., Vermunt, J.K., and Smeets, W. (2001). Love, Necessity and opportunity: Changing patterns of marital age homogamy in the Netherlands, 1850-1993. Population Studies, 55, 1-13. (pdf)

Vermunt, J.K. (2001) The use restricted latent class models for defining and testing nonparametric and parametric IRT models. Applied Psychological Measurement, 25, 283-294. (pdf)

Vermunt, J.K., Rodrigo, M.F., and Ato-Garcia, M. (2001) Modeling joint and marginal distributions in the analysis of categorical panel data. Sociological Methods and Research, 30, 170-196. (pdf)

Magidson, J., and Vermunt, J.K. (2001) Latent class factor and cluster models, bi-plots and related graphical displays. Sociological Methodology, 31, 223-264. (pdf)

Vermunt, J.K. (2002). Comments on “Latent class analysis of complex sample survey data”. Journal of the American Statistical Association, 97, 736-737. (pdf)

Brouhns, N., Denuit, M., and Vermunt, J.K. (2002). A Poisson log-bilinear approach to the construction of projected lifetables. Insurance: Mathematics & Economics, 31, 373-393. (pdf)

Vermunt, J.K., and Magidson, J. (2003). Latent class models for classification. Computational Statistics and Data Analysis, 41,3-4, 531-537. (pdf)

Vermunt, J.K. (2003). Applications of latent class analysis in social science research. Lecture Notes in Artificial Intelligence, 2711, 22-36 (pdf)

Vermunt, J.K.(2003). Multilevel latent class models. Sociological Methodology, 33, 213-239. (pdf)

Vermunt, J.K. (2004). An EM algorithm for the estimation of parametric and nonparametric hierarchical nonlinear models. Statistica Neerlandica, 58, 220- 233. (pdf)

Maas, C,J.M., and Vermunt, J.K. (2004). Editorial introduction to special issue on "Multilevel and other types of random coefficients models". Statistica Neerlandica, 58, 125-126. (pdf)

Van Abswoude, A., Vermunt, J.K., Hemker, B., and Van der Ark, A. (2004). Mokken scale analysis using hierarchical clustering procedures. Applied Psychological Measurement, 28, 332-354 (pdf)

Galindo-Garre, F., Vermunt, J.K. (2004). The order-restricted association model: Two estimation algorithms and issues in testing. Psychometrika, 69, 641-654. (pdf)

Galindo-Garre, F., Vermunt, J.K., and W. Bergsma (2004). Bayesian posterior estimation of logit parameters with small samples. Sociological Methods and Research, 33, 88-117. (pdf)

Bijmolt, T.H., Paas, L.J., and Vermunt, J.K. (2004). Country and consumer segmentation: Multi-level latent class analysis of financial product ownership. International Journal of Research in Marketing, 21, 323-340. (pdf)

Bouwmeester, S., Sijtsma, K., and Vermunt, J.K. (2004). Latent class regression analysis for describing cognitive developmental phenomena: an application to transitive reasoning. European Journal of Developmental Psychology, 1, 67-86. (pdf)

Vermunt, J.K. (2004). Comment on “An analysis of classification error for the revised current population survey employment questions”. Survey Methodology, 30, 141-144. (pdf)

Magidson, J. and Vermunt, J.K. (2005). Comment on “Current Issues and a “Wish List” for Conjoint Analysis”. Applied Stochastic Models in Business and Industry, 21, 327-328. (pdf)

Vermunt, J.K (2005). Mixed-effects logistic regression models for indirectly observed outcome variables. Multivariate Behavioral Research, 40, 281-301. (pdf)

Vermunt, J.K. (2005). Book review of "Analyzing Categorical Data" by Jeffrey S. Simonoff. Statistics in Medicine, 24, 1289-1290. (pdf)

Galindo-Garre, F., and Vermunt, J.K. (2005). Testing log-linear models with inequality constraints: A comparison of asymptotic, bootstrap, and posterior predictive p values. Statistica Neerlandica, 59, 82-94. (pdf)

Vermunt, J.K., and Anderson, C.A (2005). Maximum likelihood joint correspondence analysis. Methodology, 1, 18-26. (pdf)

Notelaers, G., Einarsen, S., De Witte, H., and Vermunt, J.K. (2006). Measuring exposure to bullying at work: The validity and advantages of the latent class cluster approach. Work & Stress, 20, 288-301. (pdf)

van Mierlo, H., Rutte, C.G., Vermunt, J.K., Kompier, M.A.J., and Doorewaard, J.A.C.M. (2006). Individual autonomy in work teams: the role of team autonomy, self-efficacy, and social support. European Journal of Work and Organizational Psychology, 15, 281-299. (pdf)

Vermunt, J.K., and Kalmijn., M. (2006). Random-effects models for personal networks: An application to marital status homogeneity. Methodology, 2, 34-41. (pdf)

Van Duijn, M.A.J., and Vermunt, J.K. (2006). What is special about social network analysis? Methodology, 2, 2-6. (pdf)

Vermunt, J.K., and Van Duijn, M.A.J. (2006). Special issue "Social network analysis". Methodology, 2, 1-1. (pdf)

Lee, H.-K., Baillargeon, R.H., Vermunt, J.K., Wu, H.-X., and Tremblay, R.E. (2007). Age differences in the prevalence of physical aggression among 5- to 11-year-old Canadian boys and girls. Aggressive Behavior, 33, 26-37. (pdf)

Kalmijn, M., and Vermunt, J.K. (2007). Homogeneity of social networks by age and marital status: A multilevel analysis of ego-centered networks. Social Networks, 29, 25-43. (pdf)

Bouwmeester, S., Vermunt, J.K., and Sijtsma, K. (2007). Development and individual differences in transitive reasoning: a fuzzy trace theory approach. Developmental Review, 27, 41-74. (pdf)

Paas, L.J., Bijmolt, T.H, and Vermunt, J.K. (2007). Acquisition patterns of financial products: A longitudinal investigation. Journal of Economic Psychology, 28, 229-241. (pdf)

Van Ginkel, J.R., Van der Ark, L.A., Sijtsma, K., and Vermunt, J.K. (2007). Two-way imputation: A Bayesian method for estimating missing scores in tests and questionnaires, and an accurate approximation. Computational Statistics and Data Analysis, 51, 4013-4027. (pdf)

Vermunt, J.K. (2007). A hierarchical mixture model for clustering three-way data sets. Computational Statistics and Data Analysis, 51, 5368-5376. (pdf)

Infant-Rivard, C., Vermunt, J.K., and Weinberg, C.R. (2007). Excess transmission of the NAD(P)H: quinone oxidoreductase 1 (NQO1) C609T polymorphism in families of children with acute lymphoblastic leukemia. American Journal of Epidemiology, 165, 1248-1254. (pdf)

Van Abswoude, A., Vermunt, J.K., and Hemker,N. (2007). Assessing dimensionality by maximizing H coefficient based objective functions. Applied Psychological Measurement, 31, 308-330. ( pdf)

Vermunt, J.K., and Magidson, J. (2007). Latent class analysis with sampling weights: A maximum likelihood approach. Sociological Methods and Research, 36, 87-111. (pdf)

Boks, M.P.M., Leask, S., Vermunt, J.K., and Kahn, R.S. (2007). The structure of psychosis revisited: The role of mood symptoms. Schizophrenia Research , 93, 178-185. (pdf)

Anderson, C.J., Zhushan L., and Vermunt, J.K. (2007). Estimation of models in a Rasch family for polytomous items and multiple latent variables. Journal of Statistical Software, 20 (6), 1-35. (pdf)

Paas, L.J., Vermunt, J.K., and Bijmolt, T.H, (2007). Discrete-time discrete-state latent Markov modelling for assessing and predicting household acquisitions of financial products. Journal of the Royal Statistical Society, Series A (Statistics in Society), 170, 955-974 . (pdf)

van Mierlo, H. Rutte, C.G., Vermunt, J.K., Kompier, M.A.J., and Doorewaard, J.A.C.M. (2007). A multilevel mediation model of the relationships between team autonomy, individual task design, and psychological well-being. Journal of Occupational and Organizational Psychology, 80, 647-664. (pdf)

Moors, G., and Vermunt, J.K. (2007). Heterogeneity in postmaterialist value priorities. Evidence from a latent class discrete choice approach. European Sociological Review, 23, 631-648. (pdf)

Chen, F., Mackey, A.J., Vermunt, J.K., and Roos, D.S. (2007). Assessing performance of orthology detection strategies applied to eukaryotic genomes. PLoS ONE, 2(4): e383. doi:10.1371/journal.pone.0000383. (pdf)

Dias, J.G., and Vermunt, J.K. (2007). Latent class modeling of website users' search patterns: Implications for online market segmentation. Journal of Retailing and Consumer Services, 14, 359-368. (pdf)

Vermunt, J.K. (2008). Latent class and finite mixture models for multilevel data sets. Statistical Methods in Medical Research, 17, 33-51. (pdf)

Van Hest, N.A.H., Hoebe, C.J.P.A., Den Boer, J.W., Vermunt, J.K., Ijzerman, E.P.F., Boersman, W.G., and Richardus, J.H. (2008). Incidence and completeness of notification of Legionnaires' disease in the Netherlands: Covariate capture-recapture analysis acknowledging regional differences. Epidemiology and Infection, 136, 540-550. (pdf)

de Vries, H., van 't Riet, J., Spigt, M., Metsemakers, J., van den Akker, M., Vermunt, J.K., and Kremers, S. (2008). Clusters of lifestyle behaviors: Results from the Dutch SMILE study. Preventive Medicine, 46, 203–208. (pdf)

Dias, J.G., and Vermunt, J.K. (2008). A bootstrap-based aggregate classifier for model-based clustering. Computational Statistics, 23, 643–659. (pdf)

Vermunt, J.K., Van Ginkel, J.R., Van der Ark, and L.A., and Sijtsma K. (2008). Multiple imputation of categorical data using latent class analysis. Sociological Methodology, 33, 369-297. (pdf)

van Mierlo, H., Vermunt, J.K., and Rutte, C.G. (2009). Composing group-level constructs from individual-level survey data. Organizational Research Methods, 12, 368-392. (pdf)

Leask, S.J., Vermunt, J.K., Done, D.J., Crowd, T.J., Blows, M., and Boks, M.P. (2009). Beyond symptom dimensions: Schizophrenia risk factors for patient groups derived by latent class analysis. Schizophrenia Research, 115, 346-350. (pdf)

Pavlopoulos, D., Muffels, R., and Vermunt, J.K. (2010). Wage mobility in Europe: A comparative analysis using restricted multinomial logit regression. Quality and Quantity, 44, 115-129. (pdf)

Van Ginkel, J.R., Sijtsma, K., Van der Ark, L.A., and Vermunt, J.K. (2010). Incidence of missing item scores in personality measurement, and simple item-score imputation. Methodology, 6, 17-30. (pdf)

Van der Ark, L.A., and Vermunt, J.K. (2010). New developments in missing data analysis. Methodology, 6, 1-2. (pdf)

Palardy, G., and Vermunt, J.K.. (2010). Multilevel growth mixture models for classifying groups. Journal of Educational and Behavioral Statistics, 35, 532-565. (pdf)

Vermunt, J.K. (2010). Latent class modeling with covariates: Two improved three-step approaches. Political Analysis, 18, 450-469. (pdf)

Manzoni, A., Vermunt, J.K., Luijkx, R., and Muffels, R. (2010). Memory bias in retrospectively collected employment careers: a model-based approach to correct for measurement error. Sociological Methodology, 40, 39-73. (pdf)

Lukociene, O., Varriale, R., and Vermunt, J.K.. (2010). The simultaneous decision(s) about the number of lower- and higher-level classes in multilevel latent class analysis. Sociological Methodology, 40, 247-283.(pdf)

Mulder, E.J.H., Koopman, C.M., Vermunt, J.K., de Valk, H.W., and Visser, G.H.A. (2010). Fetal growth trajectories in type-1 diabetic pregnancy. Ultrasound in Obstetrics and Gynecology, 36(6), 735-742.

Tay, L., Newman, D.A., and Vermunt, J.K. (2011). Using mixed-measurement item response theory with covariates (MM-IRT-C) to ascertain observed and unobserved measurement equivalence. Organizational Research Methods , 14, 147-176. (pdf)

Tay, L., Diener, E., Drasgow, F., and Vermunt, J.K. (2011). Multilevel mixed-measurement IRT analysis: An explication and application to self-reported emotions across the world Organizational Research Methods, 14, 177-207. (pdf)

Notelaers, G., Vermunt, J.K., Baillien, E., Einarsen, S., and De Witte, H. (2011). Exploring risk groups and risk factors for workplace bullying. Industrial Health, 49, 73-88.

Vermunt, J.K.. (2011). K-means may perform as well as mixture model clustering but may also be much worse: Comment on Steinley and Brusco (2011). Psychological Methods, 16, 82-88. (pdf)

Kankaras, M., Vermunt, J.K., and Moors, G. (2011). Measurement equivalence of ordinal items: A comparison of factor analytic, item response theory, and latent class approaches. Sociological Methods and Research, 40, 279-310. (pdf)

Almansa, J., Vermunt, J.K., Forero, C.G., Vilagut, G., De Graaf, R., de Girolamo, and G., Alonso, J. (2011). Measurement and description of underlying dimensions of comorbid mental disorders using factor mixture models: results on the ESEMeD project.International Journal of Methods in Psychiatric Research, 20, 116–133.

Ramos, S.B., Vermunt, J.K., and Dias, J.G. (2011). When markets fall down: Are emerging markets all equal? International Journal of Finance and Economics, 16, 324–338. (pdf)

Morren, M., Gelissen, J.P.T.M., and Vermunt, J.K. (2011). Dealing with extreme response style in cross-cultural research: A restricted latent class factor analysis approach. Sociological Methodology , 41, 13-47. (pdf)

Martella, F., Vermunt, J.K., Beekman, M., Westendorp, R.G.J., Slagboom, P.E., and Houwing-Duistermaat, J.J. (2011). A mixture model with random-effects components for classifying sibling pairs. Statistics in Medicine, 30, 3252–3264. (pdf)

De Kleijn, W.P.E., Drent, M., Vermunt, J.K., Shigemitsu, H., and De Vries, J. (2011). Types of fatigue in sarcoidosis patients. Journal of Psychosomatic Research, 71, 416-422.

Koppenol-Gonzalez, G.V., Bouwmeester, S., and Vermunt, J.K. (2012). The development of verbal and visual working memory processes: A latent variable approach. Journal of Experimental Child Psychology , 111, 439-454.

Mulder, E., Vermunt, J.K., Brand, E., Bullens, R., and Van Marle, H. (2012). Recidivism in subgroups of serious juvenile offenders: Different profiles, different risks? Criminal Behaviour and Mental Health, 22, 122–135. (pdf)

Fahey, M.T., Ferrari, P., Slimani, N., Vermunt, J.K., White, I.R., Hoffmann, K., Wirfält, E., Bamia, C., Touvier, M., Linseisen, J., Rodríguez-Barranco, M., Tumino, R., Lund, E., Overvad, K., Bueno de Mesquita, B., Bingham, S., and Riboli, E. (2012). Identifying dietary patterns using a normal mixture model: application to the EPIC study. Journal of Epidemiology and Community Health, 66, 89-94.

Varriale, R., and Vermunt, J.K. (2012). Multilevel mixture factor models. Multivariate Behavioral Research, 47, 247-275. (pdf)

Derks, E.M., Allardyce, J., Boks, M.P., Vermunt, J.K., Hijman, R., Ophoff, R.A., and G.R.O.U.P. (2012). Kraepelin was right: A latent class analysis of psychosis dimensions in patients and controls. Schizophrenia Bulletin, 38, 495-505.

Ligtvoet, R., and Vermunt, J.K. (2012). Latent class models for testing monotonicity and invariant item ordering for polytomous items. British Journal of Mathematical and Statistical Psychology, 65, 237-250. (pdf)

Bouwmeester, S., Vermunt, J.K., and Sijstma, K. (2012). The latent variable approach as applied to transitive reasoning. Cognitive Development, 27, 168–180.

Crayen, C., Eid, M., Lischetzke, T.; Courvoisier, D.S., and Vermunt, J.K. (2012). Exploring dynamics in mood regulation - mixture latent Markov modeling of ambulatory assessment data. Psychosomatic Medicine, 74, 366-376. (pdf)

Pavlopoulos, D., Muffels, R., and Vermunt, J.K. (2012). How real is mobility between low pay, high pay and non-employment? Journal of the Royal Statistical Society, Series A (Statistics in Society), 175, 749–773. (pdf)

Morren, M., Gelissen, J.P.T.M., and Vermunt, J.K. (2012). Response strategies and response styles in cross-cultural surveys. Cross-Cultural Research, 46, 255-279. (pdf)

Morren, M., Gelissen, J.P.T.M., and Vermunt, J.K. (2012). The impact of controlling for extreme responding on measurement equivalence in cross-cultural research. Methodology , 8, 159-170. (pdf)

Derks, E.M., Boks, M.P.M., Vermunt, J.K., and GROUP (2012). The identification of family subtype based on the assessment of subclinical levels of psychosis in relatives. BMC Psychiatry, 12, 71.

Notelaers, G., Baillien, E., De Witte, H., Einarsen, S., and Vermunt, J.K. (2013). Testing the strain hypothesis of the Demand Control Model to explain severe bullying at work. Economic and Industrial Democracy, 34, 69-87.

Morren, M., Gelissen, J.P.T.M., and Vermunt, J.K. (2013). Exploring the response process of culturally differing survey respondents with a response style: a sequential mixed-methods study. Field Methods, 25, 162-181.

van Lettow, B., Vermunt, J.K., de Vries, H., Burdorf. A., and van Empelen, P. (2013). Clustering of drinker image characteristics: What characterizes the typical drinker? British Journal of Psychology, 104, 382-399.

Oberski, D.L, van Kollenburg, G.H., and Vermunt, J.K. (2013). A Monte Carlo evaluation of three methods to detect local dependence in binary data latent class models. Advances in Classification and Data Analysis, 7, 267-279. (pdf)

Bock, H.H, Ingrassia, S., and Vermunt, J.K. (2013). Special issue on "Model-Based Clustering and Classification". Preface by Guests Editors. Advances in Classification and Data Analysis, 7, 237-240.

Bakk, Zs., Tekle, F.B., and Vermunt, J.K. (2013). Estimating the association between latent class membership and external variables using bias adjusted three-step approaches. Sociological Methodology, 43, 272-311. (pdf)

Bennink, M., Croon, M.A., and Vermunt, J.K. (2013). Micro-macro multilevel analysis for discrete data: A latent variable approach and an application on personal network data. Sociological Methods and Research , 42, 431-457. (pdf)

Martella, F., and Vermunt, J.K. (2013). Model-based approaches to synthesize microarray data: a unifying review using mixture of SEMs. Statistical Methods in Medical Research, 22, 567-582. (pdf)

Koppenol-Gonzalez, G.V., Bouwmeester, S., and Vermunt, J.K. (2013). Short term memory for serial order: Unraveling individual differences in the use of processes and changes across tasks. Frontiers in Psychology: Cognition , 4, article 589 (doi: 10.3389/fpsyg.2013.00589).

Almansa J., Vermunt, J.K., Forero C.G., and Alonso J. (2014). A factor mixture model for multivariate survival data. An application to the analysis of lifetime mental disorders. Journal of the Royal Statistical Society, Series C (Applied Statistics), 63, 85-102. (pdf)

Tay, L., Woo, S.E., and Vermunt, J.K. (2014). A conceptual and methodological framework for psychometric isomorphism: Validation of multilevel construct measures. Organizational Research Methods, 17, 77-106.

Pavlopoulos, D., Fouarge, D., Muffels, R., and Vermunt, J.K. (2014). Who benefits from a job change: The dwarfs or the giants? European Societies, 16, 299-319. (pdf)

Koppenol-Gonzalez, G.V., Bouwmeester, S., and Vermunt, J.K. (2014). Short term memory development: Differences in serial position curves between age groups and latent classes. Journal of Experimental Child Psychology, 126, 138–151.

Eusebi, P., Reitsma, J.B., and Vermunt, J.K. (2014). Latent class bivariate model for the meta-analysis of diagnostic test accuracy studies. BMC Medical Research Methodology, 14, 88.

Bennink, M., Croon, M.A., Keuning, J., and Vermunt, J.K. (2014). Measuring student ability, classifying schools, and detecting item-bias at school-level based on student-level dichotomous attainment items. Journal of Educational and Behavioral Statistics, 39, 180-202. (pdf)

Moors, G., Kieruj, N., and Vermunt, J.K. (2014). The effect of labeling and numbering of response scales on the likelihood of response bias. Sociological Methodology, 44, 369–399. (pdf)

Bakk, Z., Oberski, D.L., and Vermunt, J.K. (2014). Relating latent class assignments to external variables: standard errors for corrected inference. Political Analysis, 22, 520-540. (pdf)

Forero, C.G., Almansa, J., Adroher, N.D., Vermunt, J.K., Vilagut, G., De Graaf, R., Harode, J.M., and Alonso Caballero, J. (2014). Partial likelihood estimation of IRT models with censored lifetime data: An application to mental disorders in the ESEMeD surveys. Psychometrika, 79, 470-488.

Bock, H.H, Ingrassia, S., and Vermunt, J.K. (2014). Special issue on "Model-Based Clustering and Classification" (part 2). Preface by Guests Editors. Advances in Classification and Data Analysis, 8, 1-3.

Dias, J.G., Vermunt, J.K., and Ramos, S. (2015). Clustering financial time series: New insights from an extended hidden Markov model. European Journal of Operational Research, 243, 852–864. (pdf)

Van Kollenburg, G.H., Mulder, J., and Vermunt, J.K. (2015). Assessing model fit in latent class analysis when asymptotics do not hold. Methodology, 11, 65–79. (pdf)

Pavlopoulos, D., and Vermunt, J.K. (2015). Measuring temporary employment. Do survey or register data tell the truth? Survey Methodology, 41(1), 197-214. (pdf)

Oberski, D.L., Vermunt, J.K., and Moors, G.B.D. (2015). Evaluating measurement invariance in categorical data latent variable models with the EPC-interest, Political Analysis, 23, 550-563. (pdf)

Duivis, H.E., Kupper, N., Vermunt, J.K., Penninx, B.W., Bosch, N.M., Riese, H., Oldehinkel, and A.J., de Jonge, P. (2015). Depression trajectories, inflammation, and lifestyle factors in adolescence: The TRacking Adolescents' Individual Lives Survey. Health Psychology, 34, 1047-1057.

Eusebi, P., Reitsma, J.B., and Vermunt, J.K. (2015). On mixture models for diagnostic meta-analyses. Journal of Clinical Epidemiology, 68, 1523-1523.

Bennink, M., Croon, M.A., and Vermunt, J.K. (2015). Stepwise latent class models for explaining group-Level outcomes using discrete individual-level predictors. Multivariate Behavioral Research, 50, 662-675. (pdf)

Hadiwijaya, H,, Klimstra, T., Vermunt, J.K., Branje, S., and Meeus, W. (2015). Parent-adolescent relationships: An adjusted person-centered approach, European Journal of Developmental Psychology, 12, 728-739.

Bakk, Zs., and Vermunt, J.K. (2016). Robustness of stepwise latent class modeling with continuous distal outcomes. Structural Equation Modeling, 23, 20-31. (pdf)

Gudicha, D.W., Schmittmann, V.D., and Vermunt, J.K. (2016). Power computation for likelihood ratio tests for the transition parameters in latent Markov models. Structural Equation Modeling, 23, 234-245. (pdf)

Bakk, Zs., Oberski, D., and Vermunt, J.K. (2016). Relating latent class membership to continuous distal outcomes: improving the LTB approach and a modified three-step implementation. Structural Equation Modeling, 23, 278-289. (pdf)

Tay, L., Huang, Q., and Vermunt, J.K. (2016). Item response theory with covariates (IRT-C): Assessing item recovery and differential item functioning for the three-parameter logistic model. Educational and Psychological Measurement, 76, 22-42.

Lamont, A.E., Vermunt, J.K., and Van Horn, M.L. (2016). Regression mixture models: Does modeling the covariance between independent variables and latent classes improve the results?, Multivariate Behavioral Research, 51, 35-52.

Moors, G., Vriens, I., Gelissen, J.P.T.M., and Vermunt, J.K. (2016). Two of a kind. Similarities between ranking and rating data in measuring values. Survey Research Methods, 10, 15-33. (pdf)

van der Palm, D.W., van der Ark, L.A., and Vermunt, J.K. (2016). A comparison of incomplete-data methods for categorical data. Statistical Methods in Medical Research, 25, 754-774. (pdf)

Bennink, M., Croon, M.A., Kroon, B., and Vermunt, J.K. (2016). Micro-macro multilevel latent class models with multiple discrete individual-level variables. Advances in Classification and Data Analysis, 10, 139-154. (pdf)

Tekle, F.B., Gudicha, G.W., and Vermunt, J.K. (2016). Power analysis for the bootstrap likelihood ratio test for the number of classes in latent class models. Advances in Classification and Data Analysis, 10, 209-224. (pdf)

van der Palm, D.W., van der Ark, L.A., and Vermunt, J.K. (2016). Divisive latent class modeling as a density estimation method for categorical data. Journal of Classification, 33, 52-72. (pdf)

Gudicha, G.W., Tekle, F.B., and Vermunt, J.K. (2016). Power and sample size computation for Wald tests in latent class models. Journal of Classification, 33, 30-51. (pdf)

Kim, M., Vermunt, J.K., Bakk, Zs., Jaki, T., and Van Horn, M.L. (2016). Modeling predictors of latent classes in regression mixture models. Structural Equation Modeling, 23, 601-614.

Nagelkerke, E., Oberski, D.L., and Vermunt, J.K. (2016). Goodness-of-fit of multilevel latent class models for categorical data, Sociological Methodology, 46, 252-282. (pdf)

Di Mari, R., Oberski, D.L., and Vermunt, J.K. (2016). Bias-adjusted three-step latent Markov modeling with covariates, Structural Equation Modeling, 23 , 649-660. (pdf)

Ippel, L., Kaptein, M.C., and Vermunt, J.K. (2016). Estimating random-intercept models on data streams. Computational Statistics and Data Analysis, 104, 169–182. (pdf)

Van Smeden, M., Oberski, D.L., Reitsma, J.B., Vermunt, J.K., Moons, K.G.M., and de Groot, J.A.H. (2016). Problems in detecting misfit of latent class models in diagnostic research without a gold standard were shown. Journal of Clinical Epidemiology , 74, 158–166.

Gudicha, G.W., Schmittmann, V.D., Tekle, F.B., and Vermunt, J.K. (2016). Power Analysis for the likelihood-ratio test in latent Markov models: Short-cutting the bootstrap p-value based method. Multivariate Behavioral Research, 51, 649-660. (pdf)

Molenaar, D., Oberski, D., Vermunt, J.K., and De Boeck, P. (2016). Hidden Markov IRT models for responses and response times. Multivariate Behavioral Research, 51, 606-626. (pdf)

van der Velden, P.G., Bosmans, M.W.G., van der Meulen, E., and Vermunt, J.K. (2016). Pre-event trajectories of mental health and post-event traumatic stress symptoms and health: a multi-wave study, Psychiatry Research, 246, 466–473.

Wanders, R.B.K., van Loo, H.M., Vermunt, J.K., Meijer, R.R., Hartman, C.A., Schoevers, R.A., Wardenaar, K.J., and de Jonge, P. (2016). Casting wider nets for anxiety and depression: disability-driven cross-diagnostic subtypes in a large population study. Psychological Medicine, 46, 3371-3382.

Ippel, L., Kaptein, M.C., and Vermunt, J.K. (2016). Dealing with big data: An online, row-by-row, estimation tutorial. Methodology, 12, 124-138. (pdf)

Nagelkerke, E., Oberski, D.L., and Vermunt, J.K. (2017). Power and type I error of local fit statistics in multilevel latent class analysis, Structural Equation Modeling, 24, 216-229. (pdf)

Van de Schoot, R., Sijbrandij, M., Winter, S.D., Depaoli, S., and Vermunt, J.K. (2017). The GRoLTS-checklist: Guidelines for Reporting on Latent Trajectory Studies, Structural Equation Modeling, 24, 451-467.

Vriens, I., Moors, G., Gelissen, J., and Vermunt, J.K. (2017). Controlling for response order effects in ranking items using latent choice factor modeling. Sociological Methods and Research, 46, 218–241. (pdf)

Van den Bergh, M., Schmittmann, V.D., and Vermunt, J.K. (2017). Building latent class trees, with an application to a study of social capital. Methodology, 13(Supplement), 13–22. (pdf)

De Roover, K., Vermunt, J.K., Timmerman, M., and Ceulemans, E. (2017). Mixture simultaneous factor analysis for capturing differences in latent variables between higher-level units of multilevel data, Structural Equation Modeling, 24, 506-523. (pdf)

Hadiwijaya, H., Klimstra, T., Vermunt, J.K., Branje, S., and Meeus, W. (2017). On the development of harmony, turbulence, and independence in parent-adolescent relationships: A five-wave longitudinal study, Journal of Youth and Adolescence, 46, 1772–1788.

Van Kollenburg, G.H., Mulder, J., and Vermunt, J.K. (2017). Posterior calibration of posterior predictive p-values. Psychological Methods, 22, 382-396. (pdf)

Van Montfort, E., Denollet, J., Vermunt, J.K., Widdershoven, J., and Kupper, N. (2017). The tense, the hostile and the distressed: multidimensional psychosocial risk profiles based on the ESC interview in patients with coronary heart disease - the THORESCI study. General Hospital Psychiatry, 47, 103-111.

Crayen, C., Eid, M., Lischetzke, T., and Vermunt, J.K. (2017). A continuous-time mixture latent state-trait Markov model for experience sampling data: Application and evaluation, European Journal of Psychological Assessment, 33, 296-311. (pdf)

Gudicha, D.W., Schmittmann, V.D., and Vermunt, J.K. (2017). Statistical power of likelihood-ratio and Wald tests in latent class models with covariates, Behavior Research Methods, 47, 1824–1837. (pdf)

Janssen-de Ruijter, L., Mulder, E.A., Vermunt, J.K., and van Nieuwenhuizen, G. (2017). Many, more, most: Four risk profiles of adolescents in residential care with major psychiatric problems, Child and Adolescent Psychiatry and Mental Health, 11, 63.

Van den Bergh, M., and Vermunt, J.K. (2018). Building latent class growth trees, Structural Equation Modeling, 25, 331-342. (pdf)

Molenaar, D., Bolsinova, M., and Vermunt, J.K. (2018). A semi-Parametric within-subject mixture approach to the analyzes of responses and response times, British Journal of Mathematical and Statistical Psychology, 71, 205-228. (pdf)

Altena, M.A., Beijersbergen, M.D., Vermunt, J.K., and Wolf, J. (2018). Subgroups of Dutch homeless young adults based on risk- and protective factors for quality of life: Results of a latent class analysis, Health and Social Care in the Community, 26, e587.

Vidotto, D., Vermunt, J. K., and Van Deun, K. (2018). Bayesian latent class models for the multiple imputation of categorical data, Methodology, 14, 56-68. (pdf)

Koppenol-Gonzalez, G.V., Bouwmeester, S., and Vermunt, J.K. (2018). Accounting for individual differences in the development of verbal and visual short term memory processes in children, Learning and Individual Differences, 66, 29-37.

Boeschoten, L., Oberski, D.L., de Waal, A.G., and Vermunt, J.K. (2018). Updating latent class imputations with external auxiliary variables, Structural Equation Modeling, 25, 750-761. (pdf)

Vidotto, D., Vermunt, J.K., and Van Deun, K. (2018). Bayesian multilevel latent class models for the multiple imputation of nested categorical data. Journal of Educational and Behavioral Statistics, 43, 511-539. (pdf)

Van den Bergh, M., van Kollenburg, G.H., and Vermunt, J.K. (2018). Deciding on the starting number of classes of a latent class tree, Sociological Methodology, 48, 303-336. (pdf)

Blanken, T.F., Benjamins, J.S., Borsboom, D., Vermunt, J.K., Paquola, C., Ramautar, J., Dekker, K., Stoffers, D., Wassing, R., Wei, Y., and van Someren, E.J.W. (2019). Robust insomnia disorder subtypes revealed by non-sleep-related traits and life history, Lancet Psychiatry, 6, 151-163.

Ippel, L., Kaptein, M.C., and Vermunt, J.K. (2019). Online estimation of individual-level effects using streaming shrinkage factors, Computational Statistics and Data Analysis, 137, 16-32. (pdf)

Hadiwijaya, H,, Klimstra, T., Vermunt, J.K., Branje, S., and Meeus, W. (2019). Perceived relationship development in anxious and non-anxious adolescents: A person-centered five-wave longitudinal study, Journal of Abnormal Child Psychology, 47, 499-513.

Ippel, L., Kaptein, M.C., and Vermunt, J.K. (2019). Estimating multilevel models on data streams, Psychometrika, 84, 41-64. (pdf)

Van den Bergh, M., and Vermunt, J.K. (2019). Latent class trees with the three-step approach, Structural Equation Modeling, 26, 481-492. (pdf)

Vogelsmeier, L.V.D.E., Vermunt, J.K., Van Roekel, G.H., and De Roover, K. (2019). Latent Markov factor analysis for exploring measurement model changes in time-intensive longitudinal studies, Structural Equation Modeling, 26, 557-575. (pdf)

De Roover, K., and Vermunt, J.K. (2019). On the exploratory road to unravelling factor loading non-invariance: A new multigroup rotation approach, Structural Equation Modeling, 26, 905-923. (pdf)

Boeschoten, L., de Waal, A.G., and Vermunt, J.K. (2019). Estimating the number of serious road injuries per vehicle type in the Netherlands using Multiple Imputation of Latent Classes, Journal of the Royal Statistical Society, Series A (Statistics in Society), 182, 1463-1486. (pdf)

Billen, E., Garofalo, C., Vermunt, J.K., and Bogaerts, S. (2019). Trajectories of self-control in a forensic psychiatric sample: Stability and association with psychopathology, criminal history and recidivism, Criminal Justice and Behavior, 46, 1255-1275.

Hilterman, E.L.B., Vermunt, J.K., Bongers, I., Nicholls, T.L., and van Nieuwenhuizen, Ch. (2019). Profiles of SAVRY risk and protective factors within male and female juvenile offenders: A latent class and latent transition analysis, International Journal of Forensic Mental Health,18, 350-364.

Vogelsmeier, L.V.D.E., Vermunt, J.K., Böing-Messing, F., and De Roover, K. (2019). Continuous-time latent Markov factor analysis for exploring measurement model changes across time, Methodology, 15(Supplement), 29-42. (pdf)

Kim, M., Van Horn, M.L., Jaki, T., Vermunt, J.K., Feaster, D., Lichstein, Taylor, D.J., and Riedel, B.W. (2020). Repeated measures regression mixture models, Behavior Research Methods, 52, 591–606.

Hadiwijaya, H,, Klimstra, T., Darling, N., Vermunt, J.K., Branje, S., and Meeus, W. (2020). The family context as foundation for romantic relationships: A person-centered multi-informant longitudinal study, Journal of Family Psychology, 34, 46–56.

Dalmartello, M., Decarli, A., Ferraroni, M., Bravi, F., Serraino, D., Garavello, W., Negri, E., Vermunt, J., and La Vecchia, C. (2020). Dietary patterns and oral and pharyngeal cancer using latent class analysis, International Journal of Cancer, 147, 719-727.

Spronken, M., Brouwers, E.P.M., Vermunt, J.K., Arends, I., Oerlemans, W.G.M., van der Klink, J.J.L., and Joosen, M.C.W. (2020). Identifying return to work trajectories among employees on sick leave due to mental health problems using latent class transition analysis, BMJ Open, 10, e032016.

Vidotto, D., Vermunt, J.K., and Van Deun, K. (2020). Multiple Imputation of longitudinal categorical data through Bayesian mixture latent Markov models, Journal of Applied Statistics, 47, 1720-1738. (pdf)

Vermunt, J.K., and Magidson, J. (2021). How to perform three-step latent class analysis in the presence of measurement non-invariance or differential item functioning, Structural Equation Modeling, 28, 356-364. (pdf)

Janssen-de Ruijter, L., Mulder, E.A., Bongers, I., Vermunt, J.K., and van Nieuwenhuizen, G. (2021). One is not the other: Predicting offending after discharge from secure residential care of male adolescents with four risk profiles, Journal of Criminal Justice, 72, 101758.

Dalmartello, M., Vermunt, J., Serraino, D., Garavello, W., Negri, E., Levi, F., and La Vecchia, C. (2021). Dietary patterns and esophageal cancer: a multi-country latent class analysis, Journal of Epidemiology & Community Health, 75, 567-573.

Vogelsmeier, L.V.D.E., Vermunt, J.K., Keijsers, L., and De Roover, K. (2021). Latent Markov latent trait analysis for exploring measurement model changes in intensive longitudinal data, Evaluation & the Health Professions, 44, 61-76.. (pdf)

Clouth, F.J., Moncada-Torres, A., Geleijnse, G., Mols, F., van Erning, F.N., de Hingh, I.H.J.T., Pauws, S.C., van de Poll-Franse, L.V., and Vermunt, J.K. (2021). Heterogeneity in quality of life of long-term colon cancer survivors: a latent class analysis of the population-based PROFILES registry, The Oncologist, 26, e492-e499.

Schmitter, M., Vermunt, J.K., Blaauw, E., and Bogaerts, S. (2021). Risk classes of patients diagnosed with substance use in Dutch forensic psychiatric centers, Journal of Forensic Practice, 23, 39-52.

Leertouwer, I., Cramer, A.O.J., Vermunt, J.K., and Schuurman, N.K. (2021). A review of explicit and implicit assumptions when providing personalized feedback based on EMA data. Frontiers in Psychology: Psychology for Clinical Settings, 12, 764526. (PsyArXiv)

Clouth, F.J., Pauws, S., Mols, F., and Vermunt, J.K. (2022). A new three-step method for using inverse propensity weighting with latent class analysis. Advances in Classification and Data Analysis, 16, 351–371. (pdf)

Boeschoten, L., Scholtus, S., Daalmans, J., Vermunt, J.K., and de Waal, A.G. (2022). Using Multiple Imputation of Latent Classes to construct population census tables with data from multiple sources. Survey Methodology, 48, 119-144. (pdf)

De Roover, K., Vermunt, J.K., and Ceulemans, E. (2022). Mixture multigroup factor analysis for unraveling factor loading non-invariance across many groups, Psychological Methods, 27, 281–306.(pdf)

Kim. S., Stadler Blank, A., DeSarbo, W., and Vermunt, J.K. (2022). The spatial representation of consumer dispersion patterns via a new multi-level latent class methodology, Journal of Classification, 39, 218–239.

Havermans, R.J.M., Clouth, F.J., Lansink, K.W.W., Vermunt, J.K., de Jongh, M.A.C, and de Munter, L. (2022). Prediction of recovery in trauma patients using latent Markov models. European Journal of Trauma and Emergency Surgery, 48, 2059–2080.

Dalmartello, M., Vermunt, J., Negri, E., Levi, F., and La Vecchia, C. (2022). Adult lifetime body mass index trajectories and endometrial cancer risk. BJOG: An International Journal of Obstetrics and Gynaecology, 129, 1521-1529

Alagöz, O.E.C. and Vermunt, J.K. (2022). Stepwise latent class analysis in the presence of missing values on the class indicators. Structural Equation Modeling, 29, 784-790. (pdf)

Dalmartello, M., Vermunt, J., Parazzini, F., Serraino, D.; Giacosa, A., Crispo, A., Levi, F., La Vecchia, C., and Negri, E. (2022). Comorbidity patterns, family history and breast cancer risk: A latent class analysis, Journal of Epidemiology & Community Health, 76, 867-872.

Tuithof, M., ten Have, M., van Dorselaer, S., de Beurs, D, de Graaf, R., and Vermunt, J.K. (2022). Identification of latent alcohol use groups and transitions over time using a 9-year follow-up study in the adult general population. European Addiction Research, 28, 425-435.

Leertouwer, I., Vermunt, J.K., and Schuurman, N.K. (2022). Are retrospective assessments means of people’s experiences? Accounting for interpersonal and intrapersonal variability when comparing retrospective assessment data to ecological momentary assessment data. Journal for Person-Oriented Research, 8, 52-70. (PsyArXiv)

D’Urso, E.D., De Roover, K., Vermunt, J.K., and Tijmstra, J. (2022). Scale length does matter: recommendations for measurement invariance testing with categorical factor analysis and item response theory approaches. Behavior Research Methods, 54, 2114–2145,. (pdf)

D’Urso, E.D., De Roover, K., Vermunt, J.K., and Tijmstra, J. (2023). Awareness is bliss: How acquiescence affects exploratory factor analysis. Educational and Psychological Measurement, 83, 433-472. (PsyArXiv)

de Wit - de Visser, B., Rijckmans, M., Vermunt, J.K., and van Dam A. (2023). Pathways to antisocial behavior: a proposal to improve diagnostics and interventions. Frontiers in Psychology: Psychopathology, 14, 993090.

Vogelsmeier, L.V.D.E., Vermunt, J.K., Bülow, A., and De Roover, K. (2023). Evaluating covariate effects on ESM measurement model changes with latent Markov factor analysis: A three-step approach, Multivariate Behavioral Research, 58, 262-291. (pdf)

Haslbeck, J.M.B., Vermunt, J.K., and Waldorp, L.J. (2023). The impact of ordinal scales on Gaussian mixture recovery. Behavior Research Methods, 55, 2143-2156. (PsyArXiv)

Vogelsmeier, L.V.D.E., Vermunt, J.K., and De Roover, K. (2023). How to explore within-person and between-person measurement model differences in intensive longitudinal data with the R package lmfa. Behavior Research Methods, 55, 2387–2422. (PsyArXiv)

Clouth, F.J., Pauws, S., and Vermunt, J.K. (2023). Three-step latent class analysis with inverse propensity weighting in the presence of differential item functioning. Structural Equation Modeling, 30, 737-748. (PsyArXiv)

Constantin, M.A., Schuurman, N.K., and Vermunt, J.K. (in press). A general Monte Carlo method for sample size analysis in the context of network models. Psychological Methods,,. (PsyArXiv)

Schoenmakers, M., Tijmstra, J., Vermunt, J.K., and Bolsinova, M. (in press). Correcting for extreme response style: Model choice matters. Educational and Psychological Measurement,,.

Articles and Commentaries in Other Journals

Vermunt, J.K., and Georg, W. (1995). Die Analyse kategorialer Panel-Daten mit Hilfe von log-linearen Kausalmodellen mit latenten Variablen: Eine Anwendung am Beispiel der Skala `Jugendzentrismus'. ZA-Information, 36, 61-90. (pdf)

Vermunt, J.K., and Van Dijk. L. (2001). A nonparametric random-coefficients approach: the latent class regression model. Multilevel Modelling Newsletter, 13, 6-13. (pdf)

Magidson, J., and Vermunt, J.K. (2002). Latent class models for clustering: A comparison with K-means. Canadian Journal of Marketing Research, 20, 36-43. (pdf)

Vermunt, J.K., and Georg, W. (2002). Longitudinal data analysis using log-linear path models with latent variables. Metodología de las Ciencias del Comportamiento, 4, 37-53. (pdf)

Galindo-Garre, F., Vermunt, J.K., and Croon M.A. (2002). Likelihood-ratio tests for order-restricted log-linear models: A comparison of asymptotic and bootstrap methods. Metodología de las Ciencias del Comportamiento, 4, 325-337. (pdf)

Vermunt. J.K. (2002). An Expectation-Maximization algorithm for generalised linear three-level models. Multilevel Modelling Newsletter, 14, 3-10. (pdf)

Magidson, J., and Vermunt, J.K. (2002). Latent class modeling as a probabilistic extension of K-means clustering. Quirk’s Marketing Research Review, March 2002, 20 & 77-80. (pdf)

Brouhns, N., Denuit, M., & Vermunt, J.K. (2002). Measuring the longevity risk in mortality projections. Bulletin of the Swiss Association of Actuaries, 105-130. (pdf)

Galindo-Garre, F., and Vermunt, J.K,, (2006). Avoiding boundary estimates in latent class analysis by Bayesian posterior mode estimation. Behaviormetrika, 33, 43-59. (pdf)

Pavlopoulos, D. Fouarge, D., Muffels, R., and Vermunt, J.K. (2007). Job mobility and wage mobility of high- and low-paid workers. Schmollers Jahrbuch: Journal of Applied Social Science Studies, 127 (1), 47-58. (pdf)

Notelaers, G., De Witte, H., M. Van Veldhoven, and Vermunt, J.K. (2007). Construction and validation of the short inventory to monitor psychological hazards. Medecine du Travail & Ergonomie (Arbeidsgezondheidszorg & Ergonomie) , 44. 11-17.

Vermunt, J.K. (2008). Multilevel latent variable modeling: An application in educational testing. Austrian Journal of Statistics, 37 (3&4), 285–299. (pdf)

Pavlopoulos, D., Muffels, R., and Vermunt, J.K. (2009). Training and low-pay mobility. The case of the UK, the Netherlands and Germany. Labour, 21, 37-59. (pdf)

Tay, L., Vermunt, J.K., and Wang, C. (2013). Assessing the item response theory with covariate (IRT-C) procedure for ascertaining differential item functioning. International Journal of Testing, 13, 201-222. (pdf)

Oberski, D.L., and Vermunt, J.K. (2013). A model-based approach to goodness-of-fit evaluation in item response theory, Measurement: Interdisciplinary Research and Perspectives, 3, 117-122. (pdf)

Vidotto, D., Kapteijn, M.C., and Vermunt, J.K. (2015). Multiple imputation of missing categorical data using latent class models: State of art. Psychological Test and Assessment Modeling, 57, 542-576. (pdf)

Paas, L.J., Bijmolt, T.H.A., and Vermunt, J.K. (2015). Long-term developments of EU household financial product portfolios: A multilevel latent class analysis. Metron, 73, 249-262. (pdf)

Oberski, D.L., and Vermunt, J.K. (2015). The relation between CUB and loglinear models with latent variables, Electronic Journal of Applied Statistical Analysis, 8, 368-377. (pdf)

Book Chapters

De Beer, J., Vermunt, J.K., and Hoorn, W. van (1991). Demographic changes in the Netherlands with special reference to the relationship between female labour supply and fertility. In: J.J.Siegers and F. Tazelaar (eds.), The Dutch labour market in 2000, demographic changes & policy implications, 21-52. Groningen: Wolters-Noordhof.

Vermunt, J.K. (1996). Causal log-linear modelling with latent variables and missing data. In: U. Engel and J. Reinecke (eds.), Analysis of change: advanced techniques in panel data analysis, 35-60. Berlin/New York: Walter de Gruyter. (pdf)

Van Dijk, N., and Vermunt, J.K. (1997). Literary careers and critical reputation: a longitudinal study. In: S. Tötösy de Zepetnek and I. Sywenky (eds.), The systematic and empirical approach to literature and culture as theory and application, Vol. 7, 60-71. Alberta and Siegen: University of Alberta: RICL and Siegen University: LUMIS.(pdf)

Vermunt, J.K. (2002). A general latent class approach to unobserved heterogeneity in the analysis of event history data. In: J. Hagenaars and A. McCutcheon (eds.), Applied latent class analysis, 383-407. Cambridge, UK: Cambridge University Press. (pdf)

Vermunt, J.K., and Magidson, J. (2002). Latent class cluster analysis. In: J.Hagenaars and A.McCutcheon (eds.), Applied latent class analysis, 89-106. Cambridge, UK: Cambridge University Press. (pdf)

Van Abswoude, A.A.H., and Vermunt, J.K. (2003). Some alternative clustering methods for Mokken scale analysis. In: H Yanai, A.Okada, K.Shigemasu, Y.Kano, and J.J. Meulman (eds.), New Developments in Psychometrics, 623-630. Tokyo: Springer Verlag.

Kampen, J.K., Maddens, B., and Vermunt, J.K. (2003). Trust and satisfaction: A case study of the micro-performance theory. In: A. Salminen (ed.), Governing Networks, 319-326. Amsterdam: IOS Press.

Magidson, J., and Vermunt, J.K. (2003). Comparing latent class factor analysis with the traditional approach in datamining. In: H. Bozdogan (ed.), Statistical Data Mining and Knowledge Discovery, 373-383. Boca Raton: Chapman & Hall/CRC. (pdf)

Magidson, J., and Vermunt, J.K. (2004). Latent class models. In: D. Kaplan (ed.), The Sage Handbook of Quantitative Methodology for the Social Sciences, Chapter 10, 175-198. Thousand Oaks: Sage Publications. (pdf) (pdf: updated version from 2016)

Vermunt, J.K. & Hagenaars, J.A. (2004). Ordinal longitudinal data analysis. In: R.C. Hauspie, N. Cameron and L. Molinari (eds.), Methods in Human Growth Research, Chapter 15, 374-393. Cambridge, UK: Cambridge University Press. (pdf)

Vermunt, J.K., and Magidson, J. (2005). Factor Analysis with categorical indicators: A comparison between traditional and latent class approaches. In: A. Van der Ark, M.A. Croon, and K. Sijtsma (eds.), New Developments in Categorical Data Analysis for the Social and Behavioral Sciences, 41-62. Mahwah: Erlbaum. (pdf)

Vermunt, J.K., and Magidson, J. (2005). Hierarchical mixture models for nested data structures. In: C. Weihs und W. Gaul (eds.), Classification: The Ubiquitous Challenge, 176-183. Heidelberg: Springer. (pdf)

Magidson, J., and Vermunt, J.K. ( 2005). An extension of the CHAID tree-based segmentation algorithm to multiple dependent variables. In: C. Weihs und W. Gaul (eds.), Classification: The Ubiquitous Challenge, 240-247. Heidelberg: Springer. (pdf)

Dias, J.G., and Vermunt, J.K. (2006). Bootstrap methods for measuring classification uncertainty in latent class analysis. In: A. Rizzi and M Vichi (eds.), Proceedings in Computational Statistics, 31-41, Heidelberg: Springer. (pdf)

Magidson, J., and Vermunt, J.K. (2006). Use of latent class regression models with a random intercept to remove overall response level effects in ratings data. In: A. Rizzi and M Vichi (eds.), Proceedings in Computational Statistics, 351-360, Heidelberg: Springer. (pdf)

Vermunt, J.K. (2007). Growth models for categorical response variables: standard, latent-class, and hybrid approaches. In: K. van Montfort, H. Oud, and A. Satorra (eds.), Longitudinal Models in the Behavioral and Related Sciences, 139-158. Mahwah, NJ: Erlbaum. (pdf)

Vermunt, J.K., Tran, B., and Magidson, J. (2008). Latent class models in longitudinal research. In: S. Menard (ed.), Handbook of Longitudinal Research: Design, Measurement, and Analysis, 373-385. Burlington, MA: Elsevier. (pdf)

Magidson, J., Vermunt, J.K., and Tran, B. (2009). Using a mixture latent Markov model to analyze longitudinal U.S. employment data involving measurement error. In: K. Shigemasu, A. Okada, T. Imaizumi, and T. Hoshino (eds.), New Trends in Psychometrics, 235-242. Universal Academy Press, Inc. (pdf)

Vermunt, J.K. (2009). Event history analysis. In: R. Millsap and A. Maydeu-Olivares (eds.), Handbook of Quantitative Methods in Psychology, 658-674. London: Sage. (pdf)

Lukociene, O., Vermunt, J.K (2010). Determining the number of components in mixture models for hierarchical data. In: A. Fink, B. Lausen, W. Seidel, and A. Ultsch (eds.), Advances in data analysis, data handling and business intelligence, 241-249. Berlin-Heidelberg: Springer. (pdf)

Dias, J.G., Vermunt, J.K., and Ramos, S. (2010). Mixture hidden Markov models in finance research. In: A. Fink, B. Lausen, W. Seidel, and A. Ultsch (eds.), Advances in data analysis, data handling and business intelligence , 451-459. Berlin-Heidelberg: Springer. (pdf)

Vermunt, J.K (2010). Longitudinal research using mixture models. In: K. van Montfort, J.H.L. Oud, and A. Satorra (eds.), Longitudinal Research with Latent Variables , 119-152. Heidelberg, Germany: Springer. (pdf)

Bacher, J., and Vermunt, J.K. (2010). Analyse latenter Klassen. In: C. Wolf und H. Hennig (Hrsq.), Handbuch der sozialwissenschaftlichen Datenanalyse , 553-574. Wiesbaden: VS Verlag. (pdf)

Vermunt, J.K (2010). Mixture models for multilevel data sets. In: J. Hox and J.K. Roberts (eds.), Handbook of Advanced Multilevel Analysis, 59-81. New York: Routledge. (pdf)

Kankaras, M., Moors, G., and Vermunt, J.K (2010). Testing for measurement invariance with latent class analysis. In: E. Davidov, P. Schmidt, and J. Billiet (eds.), Cross-Cultural Analysis: Methods and Applications, 359-384. New York: Routledge. (pdf)

Tekle, F.B., and Vermunt, J.K. (2012). Event history analysis. In: Cooper, H., Camic, P. M., Long, D. L., Panter, A. T., Rindskopf, D. & Sher, K. J. (eds.), APA Handbook of Research Methods in Psychology, Volume 3, Data analysis and research publication. 267-290. Washington: American Psychological Association. (pdf)

Riggi, M., and Vermunt, J.K (2012). Students reading motivation: A multilevel mixture factor analysis. In: W.A. Gaul, A. Geyer-Schulz, L. Schmidt-Thieme, and J. Kunze (eds.), Challenges at the Interface of Data Analysis, Computer Science, and Optimization; Studies in Classification, Data Analysis, and Knowledge Organization, 567-573. Berlin: Springer.

Gudicha, D.W., and Vermunt, J.K. (2013). Mixture model clustering with covariates using adjusted three-step approaches. In: B. Lausen, D. van den Poel, and A. Ultsch (eds), Algorithms from and for Nature and Life; Studies in Classification, Data Analysis, and Knowledge Organization. 87-93. Heidelberg: Springer-Verlag GmbH. (pdf)

Vermunt, J.K. (2013). Categorical response data. In: M.A. Scott, J.S. Simonoff, and B.D. Marx (eds.), The SAGE Handbook of Multilevel Modeling, 287-298. Thousand Oaks, CA: Sage. (pdf)

Vermunt, J.K., and Paas, L.J. (2017). Mixture models. In: P.S.H Leeflang, J.E. Wieringa, T.H.A. Bijmolt, and K.H. Pauwels (eds.), Advanced Methods for Modeling Markets, 383-403. Cham, Switzerland: Springer. (pdf)

Vermunt, J.K. (2018). Latent GOLD. In: W.J. van der Linden and R.K. Hambleton (eds.), Handbook of item response theory, Volume Three: Applications, 533-540. Abingdon, UK: CRC/Taylor&Francis. (pdf)

Vermunt, J.K. (2019). Latent class scaling models for longitudinal and multilevel data sets. In: G. R. Hancock, J.R. Harring and G. B. Macready (eds.), Advances in latent class analysis: A Festschrift in honor of C. Mitchell Dayton. 223-238. Charlotte, NC: Information Age Publishing, Inc. (pdf)

Magidson, J., Vermunt, J.K., and John P. Madura (2020). Latent class analysis. In: P. Atkinson, S. Delamont, A. Cernat, J.W. Sakshaug and R.A. Williams (eds.), SAGE Research Methods Foundations. https://www.doi.org/10.4135/9781526421036883636.

Ippel, L., Kaptein, M.C., and Vermunt, J.K (2022). Analyzing data streams for social scientists. In: U. Engel, A. Quan-Haase, S. Xun-Liu and L. Lyberg (eds.), Handbook of Computational Social Science, Volume 2: Data Science, Statistical Modelling, and Machine Learning Methods, 71-81. Abingdon, UK: Routledge. (pdf)

Encyclopedia Entries

Vermunt, J.K. (2001). Event history analysis, selectivity. In: Smetser and Baltes (eds.), International Encyclopedia of the Social and Behavioral Sciences, Vol 7, 7956-7962. Elvesier. (pdf)

Vermunt, J.K., and Magidson, J. (2004). Latent class analysis. In: M.S. Lewis-Beck, A. Bryman, and T.F. Liao (eds.), The Sage Encyclopedia of Social Sciences Research Methods, 549-553. Thousand Oaks, CA: Sage Publications. (pdf)

Vermunt, J.K., and Magidson, J. (2004). Latent variable. In: M.S. Lewis-Beck, A. Bryman, and T.F. Liao (eds.), The Sage Encyclopedia of Social Sciences Research Methods, 555-556. Thousand Oaks, CA: Sage Publications. (pdf)

Vermunt, J.K., and Magidson, J. (2004). Local independece. In: M.S. Lewis-Beck, A. Bryman, and T.F. Liao (eds.), The Sage Encyclopedia of Social Sciences Research Methods, 580-58. Thousand Oaks, CA: Sage Publications. (pdf)

Vermunt, J.K., and Magidson, J. (2004). Non-parametric random-effects model. In: M.S. Lewis-Beck, A. Bryman, and T.F. Liao (eds.), The Sage Encyclopedia of Social Sciences Research Methods, 732-733. Thousand Oaks, CA: Sage Publications. (pdf)

Vermunt, J.K. (2004). Latent Markov model. In: M.S. Lewis-Beck, A. Bryman, and T.F. Liao (eds.), The Sage Encyclopedia of Social Sciences Research Methods, 553-554. Thousand Oaks, CA: Sage Publications. (pdf)

Vermunt, J.K. (2004). Latent profile model. In: M.S. Lewis-Beck, A. Bryman, and T.F. Liao (eds.), The Sage Encyclopedia of Social Sciences Research Methods, 554-555. Thousand Oaks, CA: Sage Publications. (pdf)

Vermunt, J.K. (2004). Mover-stayer model. In: M.S. Lewis-Beck, A. Bryman, and T.F. Liao (eds.), The Sage Encyclopedia of Social Sciences Research Methods, 665-666. Thousand Oaks, CA: Sage Publications. (pdf)

Vermunt, J.K. (2004). Mixture model. In: M.S. Lewis-Beck, A. Bryman, and T.F. Liao (eds.), The Sage Encyclopedia of Social Sciences Research Methods, 653. Thousand Oaks, CA: Sage Publications. (pdf)

Vermunt, J.K., and Magidson, J. (2005). Structural equation models: Mixture models. In: B. Everitt and D. Howell (eds.), Encyclopedia of Statistics in Behavioral Science, 1922–1927. Chichester, UK: Wiley (pdf)

Vermunt, J.K., and Moors, G. (2005). Event history analysis. In: B. Everitt and D. Howell (eds.), Encyclopedia of Statistics in Behavioral Science, 568–575. Chichester, UK: Wiley. (pdf)

Vermunt, J.K. (2005). Log-linear models. In: B. Everitt and D. Howell (eds.), Encyclopedia of Statistics in Behavioral Science, 1082-1093. Chichester, UK: Wiley. (pdf)

Vermunt, J.K., and Magidson, J. (2005). Latent variable. In: B. Everitt and D. Howell (eds.), Encyclopedia of Statistics in Behavioral Science, 1036-1037. Chichester, UK: Wiley. (pdf)

Vermunt, J.K. (2010). Latent class models. In: P. Peterson, E. Baker, and B. McGaw (eds.), International Encyclopedia of Education, Volume 7, 238-244. Oxford: Elsevier. (pdf)

Vermunt, J.K. (2014). Latent class model. In: A.C. Michalos (ed.), Encyclopedia of Quality of Life Research and Well-Being Research, 3509-3515. Dordrecht: Springer.

Kankaras, M., and Vermunt, J.K. (2014). Simultaneous latent class analysis across groups. In: A.C. Michalos (ed.), Encyclopedia of Quality of Life and Well-Being Research, 5969-5974. Dordrecht: Springer.

Vermunt, J.K. (in press). Latent class analysis. In: P. Peterson, E. Baker, B. McGaw, F. Rizvi, G. Smith, and K. Gutierrez (eds.), International Encyclopedia of Education, Fourth Edition, Oxford: Elsevier. (pdf)

Proceedings and Working Papers

Vermunt, J. (1999). On the use of order-restricted latent class models for defining and testing non-parametric IRT models. Methods of Psychological Research, 4, 71.

Magidson, J., and Vermunt, J. (1999). Latent class factor analysis. Methods of Psychological Research, 4, 46-47

Vermunt, J.K., and J. Magidson (2000). Graphical displays for latent class cluster and latent class factor models. W. Jansen and J.G. Bethlehem (eds.), Proceedings in Computational Statistics 2000, 121-122. Statistics Netherlands. ISSN 0253-018X. (pdf)

Magidson, J. and Vermunt, J. (2000). Bi-plots and related graphical displays based on latent class factor and cluster models. J. Blasius, J.Hox, E. de Leuw, and P. Schmith (eds.), Proceedings of the Fifth International Conference on Logic and Methodology, TT-Publikations. (pdf)

Aris, E.M., Hagenaars, J.A.P., Croon, M., and Vermunt, J.K. (2000). The use of randomisation for logit and logistic models, results from a simulation study. J. Blasius, J.Hox, E. de Leuw, and P. Schmith (eds.), Proceedings of the Fifth International Conference on Logic and Methodology, TT-Publikations. (pdf)

Galindo-Garre, F., Vermunt, J.K., and Ato-Garcia, M. (2000) Bayesian approaches to the problem of sparse tables in log-linear modelling. J. Blasius, J.Hox, E. de Leeuw, and P. Schmidt (eds.), Proceedings of the Fifth International Conference on Logic and Methodology, TT-Publikations. (pdf)

Van Abswoude, Vermunt, Hemker, and Van der Ark (2002). Mokken scale analysis by hierarchical clustering procedures. CITO-reeks 2002-2. Arnhem: CITO.

Magidson, J., Eagle, T., and Vermunt, J.K. (2003). New developments in latent class choice modeling. April 2003 Sawtooth Software Conference Proceedings, 89-112. (pdf)

Magidson, J., Eagle, T., and Vermunt, J.K. (2005). Using parsimonious conjoint and choice models to improve the accuracy of put-of-sample share predictions. Paper presented at the ART Forum 2005 (pdf)

Vermunt, J.K. (2007). Multilevel mixture item response theory models: an application in education testing. Bulletin of the International Statistical Institute, 56th Session, paper #1253, 1-4. ISI 2007: Lisboa, Portugal. (pdf)

Magidson, J., and Vermunt, J.K. (2007). Use of a random intercept in latent class regression models to remove response level effects in ratings data Bulletin of the International Statistical Institute, 56th Session, paper #1604, 1-4. ISI 2007: Lisboa, Portugal. (pdf)

Lukociené, O., and Vermunt, J.K. (2007). A comparison of parametric and nonparametric approaches for two-level random coefficient model. Bulletin of the International Statistical Institute, 56th Session, paper #927, 1-4. ISI 2007: Lisboa, Portugal.

Magidson, J., and Vermunt, J.K. (2007). Removing the scale factor confound in multinomial logit choice models to obtain better estimates of preference. Sawtooth Software Conference Proceedings, October 2007, 139-154. (pdf)

Dias, J.G., Vermunt, J.K., and Ramos, S. (2008). Heterogeneous hidden markov models. Compstat 2008 Proceedings. (pdf)

Magidson, J., Thomas, D., and Vermunt, J.K. (2009). A new model for the fusion of maxdiff scaling and ratings data. Sawtooth Software Conference Proceedings, March 2009, 83-103. (pdf)

Pirani, E., Schifini D’Andrea, S., and Vermunt, J.K. (2009). Poverty and social exclusion in Europe: differences and similarities across regions. Paper presented at XXVI IUSSP, Marrakech. (pdf)

Publications in Dutch

Vermunt, J.K. (1988). Loglineaire modellen met latente variabelen en missing data. Doctoraal scriptie (master thesis), Katholieke Universiteit Brabant (Tilburg University). (pdf)

Latten, J.J., and Vermunt, J.K. (1991). Jong en alleenstaand in de jaren '80 en '90. Maandstatistiek van de Bevolking. CBS, Voorburg.

Vermunt, J.K. (1990). Het aantal jonge moeders neemt weer toe. Maandstatistiek van de Bevolking, CBS.

Vermunt, J.K. (1990). Kleinere verschillen in huishoudensverdeling tussen gemeenten verwacht. Maandstatistiek van de Bevolking, CBS.

Vermunt, J.K. (1991). Een multivariaat model voor de geboorte van het eerste kind. Maandstatistiek van de Bevolking 91/5, 22-33. CBS, Voorburg.

Vermunt, J.K. (1991). Een model ter bepaling van de cohortcomponent in de sterfte. In: L. van Leeuwen en H. Cruijssen (eds.), Sterfte en gezondheid: nu en straks, 25-46. NIDI, Den Haag.

Vermunt, J.K. (1991). Leefstijl en demografisch gedrag: een toepassing van latente-klasse-analyse. Maandstatistiek van de Bevolking 91/11, 13-25. CBS, Voorburg.

Vermunt, J.K. (1992). Geboorte: ontwikkelingen in het verleden en toekomstverwachtingen. Maandstatistiek van de Bevolking 92/1, 18-28. CBS, Voorburg.

Vermunt, J.K. (1993). De geboorte van het eerste kind: uitstel of afstel. Gezin, 5, 31-52.

Vermunt, J.K. (2004). Toepassingen van latent klasse analyse in sociaal wetenschappelijk onderzoek (Rede van 3-10-2003). Sociale Wetenschappen. 47, 2-14. (pdf)

Vermunt, J.K., Bijmolt, T.H.A., and Paas, L.J. (2006). Multi-niveau latent klasse analyse: met een toepassing bij het simultaan clusteren van landen en consumenten. In: A.E. Bronner. P. Dekker, E. de Leeuw, L.J. Paas, K. de Ruyter, A. Smidts en J.W. Wieringa (eds.), Ontwikkelingen in Marktonderzoek, Jaarboek 2006, 161-173. Haarlem: Spaar en Hout. (pdf)

Notelaers, G., De Witte, H., Vermunt, J.K., and Einarsen, S. (2006). Pesten op het werk, gewikt en gewogen. Een latente-klassen benadering op basis van de Negative Acts-vragenlijst. Gedrag en Organisatie, 44-63.

Unpublished Manuscripts

Lukociene, O., and Vermunt, J.K.. (2007). A Comparison of multilevel logistic regression models with parametric and nonparametric random intercepts. (pdf)

Simons, A., Vermunt, J.K., and Van den Bergh, B.R.H. (2009). Maternal anxiety throughout pregnancy and its association with depression in late pregnancy and babies' birth weight.

Lukociene, O., and Vermunt, J.K.. (2009). Logistic regression analysis with multidimensional random effects: A comparison of three approaches. (pdf)

Bakker, R.M., Oerlemans, L.A.G., Kenis, P., and Vermunt, J.K. (2009). Headed for an empirically derived taxonomy of temporary project networks: A configurational approach toward project-based learning and innovation.

Almansa J., Vermunt, J.K., Forero C.G., Vilagut G., Ormel J., Haro J.M., de Girolamo G., and Alonso J. (2010). Exploring conceptual comorbidity models as measurement instruments for mental health epidemiology research.

Pieters, R., Baumgarter, H., and Vermunt, J.K. (2010). Trajectories of productivity: Stratification, mobility, and research portfolios.

Dawson, J., Walsh, W.A., Mattingly, M.J., and Vermunt, J.K. (2011). Latent class derived child maltreatment types: evidence from the National Survey of Child and Adolescent Well-Being.

Papers Submitted for Publication

Oberski, D.L., and Vermunt, J.K. (2012). The expected parameter change (EPC) for local dependence assessment in binary data latent class models. (pdf)

Meulders, M., Vermunt, J.K., and Van Mechelen, I. (2014). Modeling dependency and heterogeneity in probabilistic feature models with feature selection. (pdf)

Klimstra, T.A., Vermunt, J.K., and Denissen, J.J.A. (2018). Personality types: Conceptual issues, meta-analytic evidence for replicability, and adjustments for classification inaccuracy,,.

Nagelkerke, E., Güngör, D., and Vermunt, J.K. (2019). Detecting measurement nonequivalence with latent Markov models. (pdf)

Spronken, M., Brouwers, E.P.M., Vermunt, J.K., Arends, I., Oerlemans, W.G.M., van der Klink, J.J.L., and Joosen, M.C.W. (2020). Return-to-work trajectories among employees with mental health problems: Relation with sustainable work resumption and characteristics according to experts.

Janssen-de Ruijter, L., Mulder, E.A., Bongers, I.L., Vermunt, J.K., and van Nieuwenhuizen, Ch. (2020). Like two peas in a pod? The relationship between externalizing behavior trajectories of male adolescents in secure residential care and premature termination of treatment,,.

Dalmartello, M., Vermunt, J., Serraino, D.; Crispo, A., Negri, E., Pelucchi, C., and La Vecchia, C. (2022). Comorbidities, diet and endometrial cancer risk: A latent class analysis.

Leertouwer, I., Vermunt, J.K., and Schuurman, N.K. (2022). Do people gain insight from personalized feedback about distributions of their affective experiences? (PsyArXiv)

Leertouwer, I., Vermunt, J.K., and Schuurman, N.K. (2022). A pre-post design for testing insight from personalized feedback about positive affect in contexts. (PsyArXiv)

D’Urso, E.D., Tijmstra, J., Vermunt, J.K., and De Roover, K. (2022). Does acquiescence disagree with measurement invariance testing? (PsyArXiv)

Vermunt, J.K. (2023). The Vuong-Lo-Mendell-Rubin test for latent class and latent profile analysis: A note on the different implementations in Mplus and LatentGOLD. (pdf)

Perez Alonso, A.F., Rosseel, Y., Vermunt, J.K., and De Roover, K. (2023). Mixture multigroup structural equation modeling: A novel method for comparing structural relations across many groups. (PsyArXiv)

Lé, T.T., Clouth, F.J., and Vermunt, J.K. (2023). Causal latent class analysis with distal outcomes: A modified three-step method using inverse propensity weighting. (PsyArXiv)

Clouth, F.J., Bijlsma, M.J., Pauws, S., and Vermunt, J.K. (2023). Causal inference for latent Markov models using the parametric g-formula. (PsyArXiv)