


Unpublished 1) Muthén, B. (1977). Some results on using summed raw scores and factor scores from dichotomous items in the estimation of structural equation models. Unpublished Technical Report, University of Uppsala, Sweden. [Available as PDF] 1) Wheaton, B., Muthén, B., Alwin, D., & Summers, G. (1977). Assessing reliability and stability in panel model. In D. R. Heise (Ed.), Sociological Methodology 1977 (pp. 84136). San Francisco: JosseyBass, Inc. [Available as PDF] 2)
Muthén, B., Petersson, T., Stahlberg, G., & Olsson, U. (1977).
Measuring religious attitudes using the semantic differential technique:
An application of threemode factor analysis. Journal for the Scientific
Study of Religion, 16, 275287.
[Available as PDF] 4) Muthén, B. (1979). A structural probit model with latent variables. Journal of the American Statistical Association, 74, 807811. [Available as PDF] 5) Muthén, B. (1981). Factor analysis of dichotomous variables: American attitudes toward abortion. In D. J. Jackson, & E. F. Borgatta (Eds.), Factor analysis and measurement in sociological research: A multidimensional perspective. London: Sage. [Available as PDF] 6) Muthén, B., & Christoffersson, A. (1981). Simultaneous factor analysis of dichotomous variables in several groups. Psychometrika, 46, 407419. [Available as PDF] 7) Muthén, B. (1982). Some categorical response models with continuous latent variables. In K. G. Joreskog, & H. Wold (Eds.), Systems under indirect observation: Causality, structure, prediction (the conference volume). Amsterdam: North Holland. [Available as PDF] 8) Muthén, B., & Speckart, G. (1983). Categorizing skewed, limited dependent variables: Using multivariate probit regression to evaluate the California Civil Addict Program. Evaluation Review, 7, 257269. [Available as PDF] 9) Muthén, B. (1983). Latent variable structural equation modeling with categorical data. Journal of Econometrics, 22, 4865. [Available as PDF] 11) Muthén, B. (1984). A general structural equation model with dichotomous, ordered categorical, and continuous latent variable indicators. Psychometrika, 49, 115132. [Available as PDF] 12) Muthén, B., & Kaplan D. (1985). A comparison of some methodologies for the factor analysis of nonnormal Likert variables. British Journal of Mathematical and Statistical Psychology, 38, 171189. [Available as PDF] 13) Muthén, B. (1985). A method for studying the homogeneity of test items with respect to other relevant variables. Journal of Educational Statistics, 10, 121132. [Available as PDF] 14) Muthén, B., & Speckart, G. (1985). Latent variable probit ANCOVA: Treatment effects in the California Civil Addict Program. British Journal of Mathematical and Statistical Psychology, 38, 161170. 15) Muthén, B., & Lehman. J. (1985). Multiplegroup IRT modeling: Applications to item bias analysis. Journal of Educational Statistics, 10, 133142. [Available as PDF] 16) Muthén, B., Kaplan, D., & Hollis, M. (1987). On structural equation modeling with data that are not missing completely at random. Psychometrika, 42, 431462. [Available as PDF] 17) Muthén, B. (1987). Response to Freedman's critique of path analysis: Improve credibility by better methodological training. Journal of Educational Statistics, 12, 178184. [Available as PDF] 18)
Muthén, B. (1988). Some uses of structural equation modeling in
validity studies: Extending IRT to external variables. In H. Wainer, & H. Braun (Eds.), Test Validity (pp. 213238). Hillsdale, NJ: Erlbaum Associates.
[Available
as PDF] 21)
Muthén, B. (1989). Dichotomous factor analysis of symptom data. In Eaton, & Bohrnstedt (Eds.), Latent Variable Models for Dichotomous
Outcomes: Analysis of Data from the Epidemiological Catchment Area Program
(pp. 1965), a special issue of Sociological Methods & Research, 18,
1965.
[Available
as PDF] 23)
Muthén, B. (1989). Factor structure in groups selected on observed
scores. British Journal of Mathematical and Statistical Psychology, 42,
8190.
[Available
as PDF] 26) Muthén, B. (1989). Multiplegroup structural modeling with nonnormal continuous variables. British Journal of Mathematical and Statistical Psychology, 42, 5562. [Available as PDF] 27) Byrne,
B. M., Shavelson, R. J., & Muthén, B. (1989). Testing for the
equivalence of factor covariance and mean structures: The issue of partial
measurement invariance. Psychological Bulletin, 105(3), 456466. [Available as PDF] 29) Muthén,
B. (1989). Tobit factor analysis. British Journal of Mathematical and
Statistical Psychology, 42, 241250. [Available as PDF] 31) Muthén, B., Hollis, M., Muthén, L., & Tam, T. (1990). Applying logistic regression to choicebased and supplementary samples for the prediction of MBA matriculation. UCLA Statistics Series 63. [Available as PDF] 34) Gold, K., & Muthén, B. (1991) Extensions of covariance structure analysis: Hierarchical modeling of multidimensional achievement data. Presented at the annual meeting of the American Educational Research Association, Chicago, 1991. [Available as PDF] 35)
Muthén, B., Kao, ChihFen, & Burstein, L. (1991). Instructional
sensitivity in mathematics achievement test items: Applications of a new
IRTbased detection technique. Journal of Educational Measurement, 28,
122. [Available
as PDF] 39) Muthén, B. (1992). A comment on ShroutParides: Conventional factor
analysis as an approximation to latent trait models for dichotomous data.
International Journal of Methods in Psychiatric Research, 2, 6769.
[Available as PDF] 41) Longford, N. T., & Muthén, B. (1992). Factor analysis for clustered observations. Psychometrika, 57, 581597. [Available as PDF] 42) Waller, N. G., & Muthén, B. (1992). Genetic tobit factor analysis: quantitative genetic modeling with censored data. Behavior Genetics, 22, 265292. [Available as PDF] 43) Muthén, B. (1992). Latent variable modeling in epidemiology. Alcohol Health & Research World, 16, 286292. [Available as PDF] 44) Muthén, B., Hasin, D., & Wisnicki, K. S. (1993). Factor analysis of ICD10 symptom items in the 1988 National Health Interview Survey on Alcohol Dependence. Addiction, 88, 10711077. [Available as PDF] 45) Muthén, B. (1993). Goodness of fit with categorical and other nonnormal variables. In K. A. Bollen, & J. S. Long (Eds.), Testing Structural Equation Models (pp. 205243). Newbury Park, CA: Sage. [Available as PDF] 46)
Muthén, B., Tam, T., Muthén, L., Stolzenberg, R. M., &
Hollis, M. (1993). Latent variable modeling in the LISCOMP framework:
Measurement of attitudes toward career choice. In D. Krebs, & P. Schmidt
(Eds.), New Directions in Attitude Measurement, Festschrift for Karl Schuessler
(pp. 277290). Berlin: Walter de Gruyter. [Available
as PDF] 48) Muthén,
B., & Yang Hsu, J. W. (1993). Selection and predictive validity with
latent variable structures. British Journal of Mathematical and Statistical
Psychology, 46, 255271. [Available as PDF] 50) Benson, J., & Muthén, B. (1993). Testing factor structure invariance of the Test Anxiety Inventory using categorical variable methodology. [Available as PDF] 51) Muthén, B., Grant, B., & Hasin (1993). The dimensionality of
alcohol abuse and dependence: Factor analysis of DSMIII and proposed
DSMIV criteria in the 1988 National Health Interview Survey. Addiction,
88, 10791090. [Available as PDF] 57) Hasin, D., Muthén, B., & Grant, B. (1994). The dimensionality of DSMIV alcohol abuse and dependence: Factor analyses in a clinical sample. 58) Hasin, D., Muthén, B., Wisnicki, K. S., & Grant, B. (1994). Validity of the biaxial dependence concept: A test in the U.S. general population. Addiction, 89, 573579. 59) Muthén, B., & Satorra, A. (1995). Complex sample data in structural equation modeling. In P.V. Marsden (Ed.), Sociological Methodology (pp. 267316). Washington, DC: American Sociological Association. [Available as PDF] 60) Muthén, B. (1995). Factor analysis of alcohol abuse and dependence symptom items in the 1988 National Health Interview survey, Addiction, 90, 637645. [Available as PDF] 61) Muthén, B., Huang, L. C., Jo, B., Khoo, S. T., Goff, G., Novak, J., & Shih, J. (1995). Opportunitytolearn effects on achievement: analytical aspects. Educational Evaluation and Policy Analysis, 17(3), 371403. [Available as PDF] 62) Muthén,
B. & Satorra, A. (1995). Technical aspects of Muthén's LISCOMP
approach to estimation of latent variable relations with a comprehensive
measurement model. Psychometrika, 60, 489503. [Available
as PDF] 66)
Muthén, B. (1996). Psychometric evaluation of diagnostic criteria:
Application to a twodimensional model of alcohol abuse and dependence. Drug and Alcohol Dependence, 41, 101112. [Available
as PDF] 73) Muthén, B. (1997). Latent variable modeling with longitudinal and multilevel data. In A. Raftery (ed.), Sociological Methodology 1997 (pp. 453480). Boston: Blackwell Publishers. [Available as PDF] 75) Muthén, B., du Toit, S.H.C., & Spisic, D. (1997). Robust inference using weighted least squares and quadratic estimating equations in latent variable modeling with categorical and continuous outcomes. Accepted for publication in Psychometrika. [Available as PDF] 76) Arminger, G. and Muthén, B. (1998). A Bayesian approach to nonlinear
latent variable models using the Gibbs sampler and the MetropolisHastings
algorithm. Psychometrika, 63, 271300. [Available as PDF] 84) Curran, P.J., Muthén, B., & Harford, T.C. (1998). The influence of changes in marital status on developmental trajectories of alcohol use in young adults. Journal of Studies on Alcohol, 59, 647658. [Available as PDF] 85) Muthén, B. & Muthén, L. (2000). Integrating personcentered and variablecentered analysis: growth mixture modeling with latent trajectory classes. Alcoholism: Clinical and Experimental Research, 24, 882891. [Available as PDF] 87) Muthén, B., Brown, C.H., Masyn, K., Jo, B., Khoo, S.T., Yang, C.C., Wang, C.P., Kellam, S., Carlin, J., & Liao, J. (2002). General growth mixture modeling for randomized preventive interventions. Biostatistics, 3, 459475. [Available as PDF] 90) Jo, B. & Muthén, B. (2001). Modeling of intervention effects with noncompliance: A latent variable modeling approach for randomized trials. In G. A. Marcoulides & R.E. Schumacker (eds.), New Developments and Techniques in Structural Equation Modeling (pp. 5787). Lawrence Erlbaum Associates. [Available as PDF] 91) Harford, T. & Muthén, B. (2001). Alcohol use among college students: The effects of prior problem behaviors and change of residence, Journal of Studies on Alcohol, 62, 306312. [Available as PDF] 94) Muthén, B. (2001). Twopart growth mixture modeling. [Available as PDF] 95) Muthén, B. (2002). Beyond SEM: General latent variable modeling. Behaviormetrika, 29, 81117. 96) Muthén,
L.K. and Muthén, B.O. (2002). How to use a Monte Carlo study to
decide on sample size and determine power. Preliminary version of a paper
scheduled to appear in Structural Equation Modeling. [Available
as PDF] 98) Muthén, B., Jo, B. & Brown, C. H. (2002). Assessment of treatment effects using latent variable modeling: Comments on the New York school choice study. [Available as PDF] 99) Muthen, B. (2004). Latent variable analysis: Growth mixture modeling and related techniques for longitudinal data. In D. Kaplan (ed.), Handbook of quantitative methodology for the social sciences (pp.345368). Newbury Park, CA: Sage Publications. [Available as PDF] 100) Lubke, G.H. & Muthén, B. (2005). Investigating population heterogeneity with factor mixture models. Psychological Methods, 10, 2139. [Available as PDF] 101) Muthén, B. (2006). Should substance use disorders be considered as categorical or dimensional? Addiction, 101, 616. [Available as PDF] 102) Muthén, B. & Asparouhov, T. (2006). Item response mixture modeling: Application to tobacco dependence criteria. Addictive Behaviors, 31, 10501066. [Available as PDF] 103) Muthén, B., Asparouhov, T. & Rebollo, I. (2006). Advances in behavioral genetics modeling using Mplus: Applications of factor mixture modeling to twin data. Twin Research and Human Genetics, 9, 313324. [Available as PDF] 104) Muthén, B. (2006). The potential of growth mixture modelling. Commentary. Infant and Child Development, 15, 000000. [Available as PDF] 106) Kreuter, F. & Muthen. B (2008). Analyzing criminal trajectory profiles: Bridging multilevel and groupbased approaches using growth mixture modeling.Journal of Quantitative Criminology, 24, 131. [Available as PDF] 107) Muthén, B. & Masyn, K. (2005). Discretetime survival mixture analysis. Journal of Educational and Behavioral Statistics, 30, 2758. [Available as PDF] 108) Asparouhov, T., Masyn, K. & Muthen, B. (2006). Continuous time survival in latent variable models. Proceedings of the Joint Statistical Meeting in Seattle, August 2006. ASA section on Biometrics, 180187. [Available as PDF] 109) Asparouhov, T. & Muthen, B. (2006). Multilevel modeling of complex survey data. Proceedings of the Joint Statistical Meeting in Seattle, August 2006. ASA section on Survey Research Methods, 27182726. [Available as PDF] 110) Asparouhov, T. & Muthen, B. (2006). Comparison of estimation methods for complex survey data analysis. [Available as PDF] 111) Nylund, K.L., Asparouhov, T., & Muthen, B. (2007). Deciding on the number of classes in latent class analysis and growth mixture modeling. A Monte Carlo simulation study. Structural Equation Modeling, 14, 535569. [Available as PDF] 112) Lüdtke, O., Marsh, H.W., Robitzsch, A., Trautwein, U., Asparouhov, T., & Muthén, B. (2008). The multilevel latent covariate model: A new, more reliable approach to grouplevel effects in contextual studies. Psychological Methods, 13, 203229. [Available as PDF] 113) Lubke, G., Muthén, B., Moilanen, I., McGough, J., Loo, S., Swanson, J., Yang, M., Taanila, A., Hurtig, T., Jarvelin, M. & Smalley, S. (2007). Subtypes versus severity differences in the AttentionDeficit/Hyperactivity disorder in the northern Finnish birth cohort. Journal of the American Academy of Child and Adolescent Psychiatry, 46, 15841593. [Available as PDF] 114) Lubke, G. & Muthén, B. (2007). Performance of factor mixture models as a function of model size, covariate effects, and classspecific parameters. Structural Equation Modeling, 14(1), 26–47.[Available as PDF] 115) Kim, Y.K. & Muthén, B. (2007). Twopart factor mixture modeling: Application to an aggressive behavior measurement instrument. Submitted for publication. [Available as PDF] 116) Klein, A. & Muthén, B. (2007). Quasimaximum likelihood of structural equation modeling with multiple interaction and quadratic effects. Multivariate Behavioral Research, 42, 647673. [Available as PDF] 117) Jo, B., Asparouhov, T., Muthén, B., Ialongo, N. & Brown, H. (2007). Cluster randomized trials with treatment noncompliance. Accepted for publication in Psychological Methods. [Available as PDF] 118) Jo, B., Asparouhov, T. & Muthén, B. (2007). Intentiontotreat analysis in cluster randomized trials with noncompliance. Forthcoming in Statistics in Medicine. [Available as PDF] 119) Boomsma, D., Cacioppo, J., Muthén, B., Asparouhov, T. & Clark, S. (2007). Longitudinal genetic analysis for loneliness in Dutch twins. Twin Research and Human Genetics, 10, 267273. [Available as PDF] 120) Asparouhov, T. & Muthén, B. (2007). Computationally efficient estimation of multilevel highdimensional latent variable models. Proceedings of the 2007 JSM meeting in Salt Lake City, Utah, Section on Statistics in Epidemiology. [Available as PDF] 121) Asparouhov, T. & Muthén, B. (2007). Testing for informative weights and weights trimming in multivariate modeling with survey data. Proceedings of the 2007 JSM meeting in Salt Lake City, Utah, Section on Survey Research Methods. [Available as PDF] 122) Muthén, B., Brown, H., Leuchter, A. & Hunter A. (2008). General approaches to analysis of course: Applying growth mixture modeling to randomized trials of depression medication. Forthcoming in P.E. Shrout (ed.), Causality and Psychopathology: Finding the Determinants of Disorders and their Cures. Washington, DC: American Psychiatric Publishing. [Available as PDF] 123) Muthén, B. (2008). Latent variable hybrids: Overview of old and new models. In Hancock, G. R., & Samuelsen, K. M. (Eds.), Advances in latent variable mixture models, pp. 124. Charlotte, NC: Information Age Publishing, Inc. [Available as PDF] 124) Kreuter, F. & Muthen, B. (2008). Longitudinal modeling of population heterogeneity: Methodological challenges to the analysis of empirically derived criminal trajectory profiles. In Hancock, G. R., & Samuelsen, K. M. (Eds.), Advances in latent variable mixture models, pp. 5375. Charlotte, NC: Information Age Publishing, Inc. [Available as PDF] 125) Boscardin, C., Muthén, B., Francis, D. & Baker, E. (2008). Early identification of reading difficulties using heterogeneous developmental trajectories. Journal of Educational Psychology, 100, 192208. [Available as PDF] 126) Asparouhov, T. & Muthen, B. (2008). Multilevel mixture models. In Hancock, G. R., & Samuelsen, K. M. (Eds.), Advances in latent variable mixture models, pp. 2751. Charlotte, NC: Information Age Publishing, Inc. [Available as PDF] 127) Lüdtke, O., Marsh, H.W., Robitzsch, A., Trautwein, U., Asparouhov, T., & Muthén, B. (2008). The multilevel latent covariate model: A new, more reliable approach to grouplevel effects in contextual studies. Psychological Methods, 13, 203229. [Available as PDF] 128) Muthén, B. & Asparouhov, T. (2009). Growth mixture modeling: Analysis with nonGaussian random effects. In Fitzmaurice, G., Davidian, M., Verbeke, G. & Molenberghs, G. (eds.), Longitudinal Data Analysis, pp. 143165. Boca Raton: Chapman & Hall/CRC Press.[Available as PDF] 129) Muthén, B. & Asparouhov, T. (2009). Multilevel regression mixture analysis. Journal of the Royal Statistical Society, Series A, 172, 639657. [Available as PDF] 130) Asparouhov, T. & Muthén, B. (2009). Exploratory structural equation modeling. Structural Equation Modeling, 16, 397438. [Available as PDF] 131) Muthén, B.& Brown, H. (2009). Estimating drug effects in the presence of placebo response: Causal inference using growth mixture modeling. Statistics in Medicine, 28, 33633385. [Available as PDF] 132) Henry, K. & Muthén, B. (2010). Multilevel latent class analysis: An application of adolescent smoking typologies with individual and contextual predictors. Structural Equation Modeling, 17, 193215. [Available as PDF] 138) Muthén, B. & Asparouhov, T. (2011). Bayesian SEM: A more flexible representation of substantive theory. Second version, April 14, 2011. Accepted for publication in Psychological Methods. [Available as PDF] 139) Asparouhov, T. & Muthén, B. (2011). Using Bayesian priors for more flexible latent class analysis. Proceedings of the 2011 Joint Statistical Meetings. Submitted for publication. [Available as PDF]


Copyright © 2004 Bengt O. Muthén 