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Software, User Manuals, and Video Articles and Commentaries in ISI Journals Articles and Commentaries in Other Journals Proceedings and Working Papers Papers Submitted for Publication Links
My Tilburg University home page: click here Department of Methodology and Statistics: click here Latent GOLD and Latent GOLD Choice
programs: click here SciencePlus (Software for Science): click
here LEM program: download
Latent class analysis (John Uebersax): click
here Latent class analysis (Keith Markus): click
here Harriet van der Vleuten (my wife's
company): click here Software,
User Manuals, and Video
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 Massachussetts:
Statistical Innovations Inc. (see here). Vermunt, J.K. and Magidson, J. (2005).
Technical Guide for Latent GOLD 4.0: Basic and Advanced, Belmont Massachussetts: Statistical Innovations Inc. Vermunt, J.K. and Magidson, J. (2005).
Latent GOLD 4.0 Choice User's Guide, Belmont Massachussetts:
Statistical Innovations Inc. (see here). Vermunt, J.K. and Magidson, J. (2005).
Technical Guide for Latent GOLD Choice 4.0: Basic and Advanced, Belmont Massachussetts: Statistical Innovations Inc. (see here). 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, Massachussetts:
Statistical Innovations Inc. (see here). Vermunt, J.K. and Magidson, J. (2013).
Technical Guide for Latent GOLD 5.0: Basic, Advanced, and Syntax. Belmont Massachussetts: 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, Massachussetts: Statistical Innovations
Inc. (see here). Vermunt, J.K. and Magidson, J. (2016).
Upgrade Manual for Latent GOLD 5.1. Belmont, Massachussetts:
Statistical Innovations Inc. (see here). Vermunt, J.K. and Magidson, J. (2016).
Technical Guide for Latent GOLD 5.1: Basic, Advanced, and Syntax. Belmont Massachussetts: Statistical Innovations Inc. (see here). 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. (see here). Vermunt, J.K. (2004). Video of the Workshop "Latent Class Regression Analysis" at
the SMABS 2004 Conference in Jena (see here). You need to have Real Player
installed (can be obtained here), as well as the
handouts printed (pdf). Latent GOLD Tutorial 1 by Statistical
Consulting Group at UCLA Academic Technology Services: Using Latent GOLD®
4.5 to Estimate LC Cluster Models (see
here). Latent GOLD Tutorial 2 by Statistical
Consulting Group at UCLA Academic Technology Services: Using Latent GOLD®
4.5 to Estimate DFactor Models (see
here). What is Latent GOLD®? -- Introduction
to Latent GOLD® Part 1: (see here). A Tour of the Software -- Introduction to
Latent GOLD® Part 2: (see
here). Data Files and Save Files -- Introduction
to Latent GOLD® Part 3: (see
here). Default Output -- Introduction to Latent
GOLD® Part 4: (see here). GUI Variables Tab -- Introduction to
Latent GOLD® Part 5: (see here). Books
Vermunt, J.K. (1996). Log-linear event histosry 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) De Roover, K., Vermunt, J.K., and
Ceulemans, E. (in press). Mixture multigroup factor analysis for unraveling
factor loading non-invariance across many groups, Psychological Methods,,.(pdf) Vermunt, J.K., and Magidson, J. (in
press). How to perform three-step latent class analysis in the presence of
measurement non-invariance or differential item functioning, Structural
Equation Modeling,,. (pdf) Janssen-de Ruijter,
L., Mulder, E.A., Bongers, I., Vermunt, J.K., and van Nieuwenhuizen, G. (in press). One is not the other: Predicting offending after discharge from
secure residential care of male adolescents with four risk profiles, Journal
of Criminal Justice,,. Dalmartello, M.,
Vermunt, J., Serraino, D., Garavello, W., Negri, E., Levi, F., and La
Vecchia, C. (in press). Dietary patterns and esophageal cancer: a multi-country latent class
analysis, Journal of Epidemiology & Community Health,,. Vogelsmeier,
L.V.D.E., Vermunt, J.K., Keijsers, L., and De Roover, K. (in press). Latent Markov latent trait analysis for exploring measurement model
changes in intensive longitudinal data, Evaluation & the Health
Professions,,.. (pdf) Schmitter, M., Vermunt, J.K., Blaauw, E., and Bogaerts, S. (in press). Risk classes of
patients diagnosed with substance use in Dutch forensic psychiatric centers, Journal
of Forensic Practice,,. 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. (in press). Heterogeneity in quality of life of long-term
colon cancer survivors: a latent class analysis of the population-based
PROFILES registry, The Oncologist,,. 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: Ari 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. 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. 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, pp.
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: Fink, A.,
Lausen, B., Seidel, W. and Ultsch, A. (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: Fink, A.,
Lausen, B., Seidel, W. and Ultsch, A. (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. 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 (in press). Latent class analysis. In: P. Atkinson, S. Delamont, A. Cernat, J.W. Sakshaug and R.A.
Williams (eds.), SAGE Research Methods Foundations. Thousand Oaks, CA:
Sage Publications. Ippel, L., Kaptein, M.C., and Vermunt, J.K (in press). 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,. Abingdon, UK: Taylor&Francis 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, 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. 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,,. Boeschoten, L.,
Scholtus, S., Daalmans, J., Vermunt, J.K., and de Waal, A.G. (2019). Using Multiple Imputation of Latent
Classes (MILC) to construct population census tables with data from multiple
sources,,. DeSarbo, W., Kim. S., Stadler Blank, A., and
Vermunt, J.K. (2019). The spatial representation of consumer dispersion
patterns via a mew multi-level latent class methodology,,. Nagelkerke, E.,
Güngör, D., and Vermunt, J.K. (2019). Detecting measurement nonequivalence with
latent Markov models. (pdf) Vogelsmeier,
L.V.D.E., Vermunt, J.K., Bülow, A., and De
Roover, K. (2020). Evaluating
covariate effects on ESM measurement model changes with latent Markov factor
analysis: A three-step approach. (pdf) D’Urso, E.D.,
De Roover, K., Vermunt, J.K., and Tijmstra, J. (2020). Scale length does matter: recommendations
for measurement invariance testing with categorical factor analysis and item
response theory approaches. (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,,. |