Most papers can be downloaded by clicking on the links below. 
To request a paper without a PDF version, please email bmuthen@ucla.edu and refer to the paper number.


Unpublished 1) Muthén, B. (1977).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 Unpublished Technical Report, University of Uppsala, Sweden.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. 84-136). San Francisco: Jossey-Bass, 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 three-mode factor analysis. Journal for the Scientific Study of Religion, 16, 275-287. [Available as PDF]

3) Muthén, B. (1978). Contributions to factor analysis of dichotomous variables. Psychometrika, 43, 551-560. [Available as PDF]

4) Muthén, B. (1979). A structural probit model with latent variables. Journal of the American Statistical Association, 74, 807-811. [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 multi-dimensional perspective. London: Sage. [Available as PDF]

6) Muthén, B., & Christoffersson, A. (1981). Simultaneous factor analysis of dichotomous variables in several groups. Psychometrika, 46, 407-419. [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, 257-269. [Available as PDF]

9) Muthén, B. (1983). Latent variable structural equation modeling with categorical data. Journal of Econometrics, 22, 48-65. [Available as PDF]

10) Muthén, B., & Joreskog, K. (1983). Selectivity problems in quasi-experimental studies. Evaluation Review, 7, 139-174.
[Available as PDF]

11) Muthén, B. (1984). A general structural equation model with dichotomous, ordered categorical, and continuous latent variable indicators. Psychometrika, 49, 115-132. [Available as PDF]

12) Muthén, B., & Kaplan D. (1985). A comparison of some methodologies for the factor analysis of non-normal Likert variables. British Journal of Mathematical and Statistical Psychology, 38, 171-189. [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, 121-132. [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, 161-170.

15) Muthén, B., & Lehman. J. (1985). Multiple-group IRT modeling: Applications to item bias analysis. Journal of Educational Statistics, 10, 133-142. [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, 431-462. [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, 178-184. [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. 213-238). Hillsdale, NJ: Erlbaum Associates. [Available as PDF]

19) Muthén, B., & Hofacker, C. (1988). Testing the assumptions underlying tetrachoric correlations. Psychometrika, 53, 563-578. [Available as PDF]

20) Muthén, B., & Short, L. (1989). Applying regression and factor analysis of categorical variables to fitness and exercise data. Invited contribution to T. F. Drury (Ed.), Assessing Physical Fitness and Activity Patterns in Central Population Surveys, National Center for Health Statistics, U.S. Department of Health and Human Services. Washington, DC: U.S. Government Printing Office, in press. [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. 19-65), a special issue of Sociological Methods & Research, 18, 19-65. [Available as PDF]

22) Muthén, B. (1989). Discussion of Bertholet's paper. Invited comment appearing in H. Wold (Ed.), Theoretical empiricism: A General Rationale for Scientific Model-Building (pp. 281-285). New York: Paragon House.

23) Muthén, B. (1989). Factor structure in groups selected on observed scores. British Journal of Mathematical and Statistical Psychology, 42, 81-90. [Available as PDF]

24) Muthén, B. (1989). Latent variable modeling in heterogeneous populations. Presidential address to the Psychometric Society, July, 1989. Psychometrika, 54, 557-585. [Available as PDF]

25) Muthén, B., & Satorra, A. (1989). Multilevel aspects of varying parameters in structural models. Invited paper for the conference, "Multilevel Analysis of Educational Data," Princeton, NJ, April 1987. In D. R. Bock (Ed.), Multilevel Analysis of Educational Data (pp. 87-99). San Diego, CA: Academic Press. [Available as PDF]

26) Muthén, B. (1989). Multiple-group structural modeling with non-normal continuous variables. British Journal of Mathematical and Statistical Psychology, 42, 55-62. [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), 456-466. [Available as PDF]

28) Muthén, B. (1989). The future of methodological training in educational psychology: The problem of teaching students to use new sophisticated statistical techniques. In M. C. Wittrock, & F. Farley (Eds.), The Future of Educational Psychology ( pp. 181-189). Hillsdale, NJ: Erlbaum Associates. [Available as PDF]

29) Muthén, B. (1989). Tobit factor analysis. British Journal of Mathematical and Statistical Psychology, 42, 241-250. [Available as PDF]

30) Muthén, B. (1989). Using item-specific instructional information in achievement modeling. Psychometrika, 54, 385-396. [Available as PDF]

31) Muthén, B., Hollis, M., Muthén, L., & Tam, T. (1990). Applying logistic regression to choice-based and supplementary samples for the prediction of MBA matriculation. UCLA Statistics Series 63. [Available as PDF]

32) Muthén, B. (1990). Mean and covariance structure analysis of hierarchical data. Paper presented at the Psychometric Society meeting in Princeton, NJ, June 1990. UCLA Statistics Series 62. [Available as PDF]


33) Muthén, B. (1991). Analysis of longitudinal data using latent variable models with varying parameters. In L. Collins, & J. Horn (Eds.), Best Methods for the Analysis of Change. Recent Advances, Unanswered Questions, Future Directions (pp. 1-17). Washington DC: American Psychological Association. [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, Chih-Fen, & Burstein, L. (1991). Instructional sensitivity in mathematics achievement test items: Applications of a new IRT-based detection technique. Journal of Educational Measurement, 28, 1-22. [Available as PDF]

36) Muthén, B. (1990). Moments of the censored and truncated bivariate normal distribution. British Journal of Mathematical and Statistical Psychology, 43, 131-143.[Available as PDF]

37) Muthén, B. (1991). Multilevel factor analysis of class and student achievement components. Journal of Educational Measurement, 28, Winter 1991, 338-354. [Available as PDF]

38) Fienberg, S. F., & Muthén, B. (1991). Testimony before the National Science Foundation Directorate for Biological, Behavioral, and Social Sciences task force looking to the 21st century. AmStat News, American Statistical Association, 172, 20-22. [Available as PDF]

39) Muthén, B. (1992). A comment on Shrout-Parides: Conventional factor analysis as an approximation to latent trait models for dichotomous data. International Journal of Methods in Psychiatric Research, 2, 67-69. [Available as PDF]

40) Muthén, B., & Kaplan, D. (1992). A comparison of some methodologies for the factor analysis of non-normal Likert variables: A note on the size of the model. British Journal of Mathematical and Statistical Psychology, 45, 19-30. [Available as PDF]

41) Longford, N. T., & Muthén, B. (1992). Factor analysis for clustered observations. Psychometrika, 57, 581-597. [Available as PDF]

42) Waller, N. G., & Muthén, B. (1992). Genetic tobit factor analysis: quantitative genetic modeling with censored data. Behavior Genetics, 22, 265-292. [Available as PDF]

43) Muthén, B. (1992). Latent variable modeling in epidemiology. Alcohol Health & Research World, 16, 286-292. [Available as PDF]

44) Muthén, B., Hasin, D., & Wisnicki, K. S. (1993). Factor analysis of ICD-10 symptom items in the 1988 National Health Interview Survey on Alcohol Dependence. Addiction, 88, 1071-1077. [Available as PDF]

45) Muthén, B. (1993). Goodness of fit with categorical and other non-normal variables. In K. A. Bollen, & J. S. Long (Eds.), Testing Structural Equation Models (pp. 205-243). 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. 277-290). Berlin: Walter de Gruyter. [Available as PDF]

47) Muthén, B. (1993). Latent variable modeling of growth with missing data and multilevel data. In C. M. Cuadras, & C. R. Rao (Eds.), Multivariate Analysis: Future Directions 2 (pp. 199-210). Amsterdam: North Holland. [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, 255-271. [Available as PDF]

49) Muthén, B., Grant, B., & Hasin, D. (1993). Subgroup differences in factor structure for DSM-III-R and proposed DSM-IV criteria for alcohol abuse and dependence in the 1988 National Health Interview Survey. Accepted for publication in the Journal of Nervous and Mental Disease. [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 DSM-III and proposed DSM-IV criteria in the 1988 National Health Interview Survey. Addiction, 88, 1079-1090. [Available as PDF]

52) Gallo, J. J., Anthony, J. C., & Muthén, B. (1994). Age differences in the symptoms of depression: A latent trait analysis. Journals of Gerontology: Psychological Sciences. [Available as PDF]

53) Harnqvist, K., Gustafsson, J. E., Muthén, B., & Nelson, G. (1994). Hierarchical models of ability at class and individual levels. Intelligence, 18, 165-187. [Available as PDF]

54) Muthén, B. (1994). Instructionally sensitive psychometrics: Applications to the Second International Mathematics Study. In I. Westbury, C. Ethington, L. Sosniak, & D. Baker (Eds.), In Search of More Effective Mathematics Education: Examining Data from the IEA Second International Mathematics Study (pp. 293-324). Norwood, NJ: Ablex. [Available as PDF]

55) Muthén, B. (1994). Multilevel covariance structure analysis. In J. Hox, & I. Kreft (Eds.), Multilevel Modeling, a special issue of Sociological Methods & Research, 22, 376-398. [Available as PDF]

56) Liu, G., & Muthén, B. (1994). Sensitivity analysis for Pearson-Lawley corrections in the context of nonignorable missingness. Under review, Journal of Educational and Behavioral Statistics.

57) Hasin, D., Muthén, B., & Grant, B. (1994). The dimensionality of DSM-IV alcohol abuse and dependence: Factor analyses in a clinical sample.

58) Hasin, D., Muthén, B., Wisnicki, K. S., & Grant, B. (1994). Validity of the bi-axial dependence concept: A test in the U.S. general population. Addiction, 89, 573-579.

59) Muthén, B., & Satorra, A. (1995). Complex sample data in structural equation modeling. In P.V. Marsden (Ed.), Sociological Methodology (pp. 267-316). 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, 637-645. [Available as PDF]

61) Muthén, B., Huang, L. C., Jo, B., Khoo, S. T., Goff, G., Novak, J., & Shih, J. (1995). Opportunity-to-learn effects on achievement: analytical aspects. Educational Evaluation and Policy Analysis, 17(3), 371-403. [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, 489-503. [Available as PDF]

64) Muthén, B. (1996). Growth modeling with binary responses. In A. V. Eye, & C. Clogg (Eds.), Categorical Variables in Developmental Research: Methods of Analysis (pp. 37-54). San Diego, CA: Academic Press.
[Available as PDF]

65) Duncan, T.E., Duncan, S.C. , Alpert, A., Hops, H., Stoolmiller, M., & Muthén, B. (1997). Latent variable modeling of longitudinal and multilevel substance use data. Multivariate Behavioral Research, 32 (3), 275-318. [Available as PDF]

66) Muthén, B. (1996). Psychometric evaluation of diagnostic criteria: Application to a two-dimensional model of alcohol abuse and dependence. Drug and Alcohol Dependence, 41, 101-112. [Available as PDF]

68) Curran, P., Harford, T.C., & Muthén, B. (1996). The relation between heavy alcohol use and bar patronage: a latent growth model. Journal of Studies on Alcohol, 57, 410-418. [Available as PDF]

69) Muthén, B. (1997). Covariates of alcohol dependence and abuse: A multivariate analysis of a 1988 general population survey in the United States. Accepted for publication in Acta Psychiatrica Scandinavica.
[Available as PDF]

71) Muthén, B. & Curran, P. (1997). General longitudinal modeling of individual differences in experimental designs: a latent variable framework for analysis and power estimation. Psychological Methods, 2, 371-402. [Available as PDF]

72) Muthén, B. (1997). Latent variable growth modeling with multilevel data. In M. Berkane (Ed.), Latent Variable Modeling with Applications to Causality (pp. 149-161). New York: Springer Verlag. [Available as PDF]

73) Muthén, B. (1997). Latent variable modeling with longitudinal and multilevel data. In A. Raftery (ed.), Sociological Methodology 1997 (pp. 453-480). Boston: Blackwell Publishers. [Available as PDF]

74) Muthen, B., Khoo, S.T. & Gustafsson, J.E. (1997). Multilevel latent variable modeling in multiple populations. Under review Sociological Methods & Research. [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 Metropolis-Hastings algorithm. Psychometrika, 63, 271-300. [Available as PDF]

77) Muthén, B., Khoo, S.T., Francis, D. & Kim Boscardin, C. (2003). Analysis of reading skills development from Kindergarten through first grade: An application of growth mixture modeling to sequential processes. Multilevel Modeling: Methodological Advances, Issues, and Applications (in press). S.R. Reise & N. Duan (Eds). Mahaw, NJ: Lawrence Erlbaum Associates, pp.71-89.
[Available as PDF]


77a) Harford, T. & Muthén, B. (2001). The dimensionality of alcohol abuse and dependence: a multivariate analysis of DSM-IV symptom items in the National Longitudinal Survey of Youth. Journal of Studies on Alcohol, 62, 150-157. [Available as PDF]

78) Muthén, B. & Shedden, K. (1999). Finite mixture modeling with mixture outcomes using the EM algorithm. Biometrics, 55, 463-469. [Available as PDF]

78a) Curran, P.J., & Muthén, B. (1999). The application of latent curve analysis to testing developmental theories in intervention research. American Journal of Community Psychology, 27, 567-595. [Available as PDF]

79) Khoo, S.T. & Muthén, B. (2000). Longitudinal data on families: Growth modeling alternatives. Multivariate Applications in Substance use Research, J. Rose, L. Chassin, C. Presson & J. Sherman (eds.), Hillsdale, N.J.: Erlbaum, pp. 43-78. [Available as PDF]


80) Muthén, B. & Khoo, S.T. (1998). Longitudinal studies of achievement growth using latent variable modeling. Learning and Individual Differences, Special issue: latent growth curve analysis, 10, 73-101. [Available as PDF]

81) Muthén, B. (2000). Methodological issues in random coefficient growth modeling using a latent variable framework: Applications to the development of heavy drinking. Multivariate Applications in Substance use Research, J. Rose, L. Chassin, C. Presson & J. Sherman (eds.), Hillsdale, N.J.: Erlbaum, pp. 113-140. [Available as PDF]

82) Muthén, B. (2001). Second-generation structural equation modeling with a combination of categorical and continuous latent variables: New opportunities for latent class/latent growth modeling. In Collins, L.M. & Sayer, A. (Eds.), New Methods for the Analysis of Change (pp. 291-322). Washington, D.C.: APA. [Available as PDF]

83) Muthén, B. & Muthén, L. (2000). The development of heavy drinking and alcohol-related problems from ages 18 to 37 in a U.S. national sample. Journal of Studies on Alcohol, 61, 290-300.
[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, 647-658. [Available as PDF]

85) Muthén, B. & Muthén, L. (2000). Integrating person-centered and variable-centered analysis: growth mixture modeling with latent trajectory classes. Alcoholism: Clinical and Experimental Research, 24, 882-891. [Available as PDF]

86) Muthén, B. (2001). Latent variable mixture modeling. In G. A. Marcoulides & R. E. Schumacker (eds.), New Developments and Techniques in Structural Equation Modeling (pp. 1-33). Lawrence Erlbaum Associates. [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, 459-475. [Available as PDF]

88) Harford, T.C. & Muthén, B. (2000). Adolescent and young adult antisocial behavior and adult alcohol use disorders: a fourteen-year prospective follow-up in a national survey. Journal of Studies on Alcohol, 61, 524-528. [Available as PDF]

89) Jo, B. & Muthén, B. (2000). Intervention studies with noncompliance: Complier Average Causal Effect Estimation in Growth Mixture Modeling. Draft. To appear in N. Duan and S. Reise (Eds.), Multilevel Modeling: Methodological Advances, Issues, and Applications, Multivariate Applications Book Series, Lawrence Erlbaum Associates. [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. 57-87). 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, 306-312. [Available as PDF]

92) Muthén, B. & Masyn, K. (2004). Discrete-time survival mixture analysis. Journal of Educational and Behavioral Statistics, 30(1), 27-58 . [Available as PDF]

93) Muthén, B. & Brown, C. H. (2001). Non-ignorable missing data in a general latent variable modeling framework. [Available as PDF]

94) Muthén, B. (2001). Two-part growth mixture modeling. [Available as PDF]

95) Muthén, B. (2002). Beyond SEM: General latent variable modeling. Behaviormetrika, 29, 81-117.
[Available as PDF]

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]

97) Muthén, B. (2002). Statistical and substantive checking In growth mixture 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.345-368). 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, 21-39. [Available as PDF]

101) Muthén, B. (2006). Should substance use disorders be considered as categorical or dimensional? Addiction, 101, 6-16. [Available as PDF]

102) Muthén, B. & Asparouhov, T. (2006). Item response mixture modeling: Application to tobacco dependence criteria. Addictive Behaviors, 31, 1050-1066. [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, 313-324. [Available as PDF]

104) Muthén, B. (2006). The potential of growth mixture modelling. Commentary. Infant and Child Development, 15, 000-000. [Available as PDF]

106) Kreuter, F. & Muthen. B (2008). Analyzing criminal trajectory profiles: Bridging multilevel and group-based approaches using growth mixture modeling.Journal of Quantitative Criminology, 24, 1-31. [Available as PDF]

107) Muthén, B. & Masyn, K. (2005). Discrete-time survival mixture analysis. Journal of Educational and Behavioral Statistics, 30, 27-58. [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, 180-187. [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, 2718-2726. [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, 535-569. [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 group-level effects in contextual studies.  Psychological Methods, 13, 203-229. [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 Attention-Deficit/Hyperactivity disorder in the northern Finnish birth cohort. Journal of the American Academy of Child and Adolescent Psychiatry, 46, 1584-1593. [Available as PDF]

114) Lubke, G. & Muthén, B. (2007). Performance of factor mixture models as a function of model size, covariate effects, and class-specific parameters. Structural Equation Modeling, 14(1), 26–47.[Available as PDF]

115) Kim, Y.K. & Muthén, B. (2007). Two-part factor mixture modeling:  Application to an aggressive behavior measurement instrument.  Submitted for publication. [Available as PDF]

116) Klein, A. & Muthén, B. (2007). Quasi-maximum likelihood of structural equation modeling with multiple interaction and quadratic effects. Multivariate Behavioral Research, 42, 647-673. [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). Intention-to-treat 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, 267-273. [Available as PDF]

120) Asparouhov, T. & Muthén, B. (2007). Computationally efficient estimation of multilevel high-dimensional 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. 1-24. 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. 53-75. 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, 192-208. [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. 27-51. 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 group-level effects in contextual studies.  Psychological Methods, 13, 203-229. [Available as PDF]

128) Muthén, B. & Asparouhov, T. (2009). Growth mixture modeling: Analysis with non-Gaussian random effects. In Fitzmaurice, G., Davidian, M., Verbeke, G. & Molenberghs, G. (eds.), Longitudinal Data Analysis, pp. 143-165. 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, 639-657. [Available as PDF]

130) Asparouhov, T. & Muthén, B. (2009). Exploratory structural equation modeling. Structural Equation Modeling, 16, 397-438. [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, 3363-3385. [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, 193-215. [Available as PDF]

133) Hunter, A. M., Muthén, B.O., Cook, I.A. & Leuchter, A. F. (2010). Antidepressant response trajectories and quantitative electroencephalography (QEEG) biomarkers in major depressive disorder. Journal of Psychiatric Research, 44, 90-98. 
[Available as PDF]

134) Muthén, B., Brown, C.H., Hunter, A., Cook, I.A. & Leuchter, A.F. (2011). General approaches to analysis of course: Applying growth mixture modeling to randomized trials of depression medication. In P.E. Shrout (ed.), Causality and Psychopathology: Finding the Determinants of Disorders and their Cures (pp. 159-178). New York: Oxford University Press. 
[Available as PDF]

135) Muthén, B. & Asparouhov, T. (2011). Beyond multilevel regression modeling: Multilevel analysis in a general latent variable framework. In J. Hox & J.K. Roberts (eds), Handbook of Advanced Multilevel Analysis, pp. 15-40. New York: Taylor and Francis. 
[Available as PDF]

136) Muthén, B., Asparouhov, T., Hunter, A. & Leuchter, A. (2011). Growth modeling with non-ignorable dropout: Alternative analyses of the STAR*D antidepressant trial.  Psychological Methods, 16, 17-33. 
[Available as PDF] 

137) Leoutsakos, J.S., Muthén, B.O., Breitner, J.C.S. & Lyketsos, C.G. (2011). Effects of NSAID treatments on cognitive decline vary by phase of pre-clinical Alzheimer disease: Findings from the randomized controlled ADAPT trial. International Journal of Geriatric Psychiatry. In Press.
[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]

 

 

 
   
   
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