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Leite, W. L. (2016). Practical Propensity Score Methods Using R. Thousand Oaks, CA: Sage Publishing.


Leite, W. L., Stapleton, L. M., & Bettini, E. F. (in press). Propensity Score Analysis of Complex Survey Data with Structural Equation Modeling: A Tutorial with Mplus. Structural Equation Modeling: A Multidisciplinary Journal.

Aydin, B., Algina, J., & Leite, W. L. (in press). Comparison of Model and Design-Based Approaches to Detect the Treatment Effect and Covariate by Treatment Interactions in Three-Level Models for Multi-site Cluster Randomized Trials. Behavior Research Methods.

Bishop, C. D., Leite, W. L., Snyder, P. (2018). Using Propensity Score Weighting to Reduce Selection Bias in Large-Scale Data Sets. Journal of Early Intervention, 40(4), 347-362.

Leite, W. L., Aydin, B. & Gurel, S. (in press) A Comparison of Propensity Score Weighting Methods for Evaluating the Effects of Programs with Multiple Versions. The Journal of Experimental Education, DOI: 10.1080/00220973.2017.1409179

Cetin-Berber, D. D., & Leite, W. L. (in press). A comparison of one-step and three-step approaches for including covariates in the shared parameter growth mixture model. Structural Equation Modeling. 10.1080/10705511.2018.1428806

Bettini, E., Jones, N., Brownell, M. , Conroy, M., Leite, W. L. (2018). Relationships between Novice Teachers’ Social Resources and Workload Manageability. Journal of Special Education, 52 (2), 113-126.

Rarborn, A. W. , & Leite, W. L. (2018). ShortForm: An R package to select scale short forms with the ant colony optimization algorithm. Applied Psychological Measurement, 42(6), 516-517.

Gage, N., Leite, W. L., Childs, K. & Kincaid, D. (2017). Average Treatment Effect of School-wide Positive Behavior Supports (SWPBIS) on School-Level Academic Achievement in Florida. Journal of Positive Behavior Interventions. 19(3), 158-167.

Collier, Z. K. & Leite, W. L. (2017). A Comparison of Three-Step Approaches for Auxiliary Variables in Latent Class and Latent Profile Analysis. Structural Equation Modeling, 24:6, 819-830, DOI: 10.1080/10705511.2017.1365304

Li, Z., Leite, W. L., Thompson, L., Gross, H. E., Shenkman,  E., Reeve, B. B., DeWalt, D. A., & Huang. I. (2017). Determinants of longitudinal health-related quality of life change in children with asthma from low-income families: a report from the PROMIS Pediatric Asthma Study. Clinical and Experimental Allergy. 47, 383–394, doi: 10.1111/cea.12827

Hu, J., & Leite, W. L. (2017). An Evaluation of the Use of Covariates to Assist in Class Enumeration in Linear Growth Mixture Modeling. Behavior Research Methods, 49 (3), 1179-1190.

Kaya, Y., & Leite, W. L. (2017). Assessing change in latent skills across time with longitudinal cognitive diagnosis modeling: An evaluation of model performance. Educational and Psychological Measurement, 77(3) 369–388.

Barnes, T., Leite, W. L., & Smith, S. (2017). A Quasi-Experimental Analysis of School-Wide Violence Prevention Programs. Journal of School Violence, 16, 49-67.

Aydin, B., Leite, W. L, & Algina, J. (2016). The effects of including observed means or latent means as covariates in multilevel models for cluster randomized trials. Educational and Psychological Measurement, 76, 803–823.

Koo, N., Leite, W. L., & Algina, J. (2016). Mediated effects with the parallel process latent growth model: an evaluation of methods for testing mediation in the presence of nonnormal data. Structural Equation Modeling, 23, 32-44.

Leite, W. L., Jimenez, F., Kaya, Y., Stapleton, L. M., MacInnes, J. W., & Sandbach, R. (2015). An evaluation of weighting methods based on propensity scores to reduce selection bias in multilevel observational studies. Multivariate Behavioral Research. 50, 265–284.

Leite, W. L. (2015). Latent growth modeling of longitudinal data with propensity score matched groups In Wei Pan, & Haiyan Bai. Propensity Score Analysis: Fundamentals, Developments, and Extensions, (pp. 191-216.) New York: Guilford.

Leite, W. L., Jimenez, F., Kaya, Y., Stapleton, L. M., MacInnes, J. W., & Sandbach, R. (2015). An evaluation of weighting methods based on propensity scores to reduce selection bias in multilevel observational studies. Multivariate Behavioral Research.

Park, Y., Gurel, S., Oh, J., Leite, W., & Bettini, E. F. (in press). Literacy related school readiness skills of English language learners in Head Start: An analysis of the School Readiness Survey. Journal of Early Childhood Research.

Aydin, B., Leite, W. L., & Algina, J. (2014). The Consequences of Ignoring Variability in Measurement Occasions within Data Collection Waves in Latent Growth Models. Multivariate Behavioral Research, 49, 149–160.

Koo, N. & Leite, W. L. (2014). The Impact of Ignoring Time Series Processes in Linear Growth Mixture Modeling. Structural Equation Modeling, 21, 210–224.

Zhang, L., Jin, R., Leite, W. L., & Algina, J. (2014). Additive Models for Multitrait-Multimethod Data with a Multiplicative Trait-Method Relationship: A Simulation Study. Structural Equation Modeling, 21, 68–80.

Matos, D. A. S., Cirino, S. D., Brown, G. T. L., & Leite, W. L. (2013).  A avaliação no ensino superior: Concepções múltiplas de estudantes Brasileiros [Assessment in higher education: Multiple conceptions of Brazilian students]. Estudos em avaliação educacional, 24 (54), 172-193.

Marcoulides, G., & Leite, W. L. (2013). Exploratory data mining algorithms for conducting searches in structural equation modeling: A comparison of some fit criteria. In. J. J. McArdle & G. Ritschard. Contemporary issues in exploratory data mining in the behavioral sciences (pp. 150-171). New York, NY: Taylor & Francis.

Bandalos, D. L. & Leite, W. L. (2013). Use of Monte Carlo Studies in Structural Equation Modeling Research. In G. R. Hancock & R. O. Mueller (Eds.), Structural equation modeling: A second course (2nd Ed.). (pp.564-666 ) Greenwich, CT: Information Age Publishing. Click here for code related to this chapter.

Adams, A., Ross, D., Swain, C., Dana, N, Leite, W., & Sandbach, R. (2013). Preparing teacher leaders in a job-embedded graduate program: Changes within and beyond the classroom walls. Teacher Education and Practice, 26 (3), 581-597.

Leite, W. L., Sandbach, R., Jin, R., MacInnes, J., & Jackman, G. A. (2012). An Evaluation of Latent Growth Models for Propensity Score Matched Groups. Structural Equation Modeling. 19, 437–456.

Boman IV, J. H., Ward, J. T., Gibson, C. L., & Leite, W. L. (2012) Can a perceptual peer deviance measure accurately measure a peer’s self-reported deviance? Journal of Criminal Justice. 40, 463–471.

Leite, W. L. (2012): Latent Growth Curve Modeling By Kristopher J. Preacher, Aaron L. Wichman, Robert C. MacCallum, and Nancy E. Briggs.  Structural Equation Modeling, 19, 152-155.

Leite, W. L., & Stapleton, L. (2011). Detecting growth shape misspecifications in latent growth models: An evaluation of fit indices. The Journal of Experimental Education, 79, 361-381.

Jackman, M. G., Leite, W. L., & Cochrane, D. (2011). Estimating latent variable interactions with the unconstrained approach: A comparison of methods to form product indicators for large, unequal numbers of items. Structural Equation Modeling, 18, 274-288.

Leite, W. L., & Zuo, Y. (2011). Modeling latent Interactions at level two in multilevel structural equation models: An evaluation of mean-centered and residual-centered unconstrained Approaches. Structural Equation Modeling, 18, 449-464.

Leite, W. L., & Beretvas, S. N. (2010). The performance of multiple imputation for Likert-type items with missing data. Journal of Modern Applied Statistical Methods, 9(1), 64-74.

Ward, J., Gibson, C., Boman, J. &  Leite, W. L. (2010). Assessing the validity of the Retrospective Behavioral Self-Control scale: Is the General Theory of Crime stronger than the evidence suggestsCriminal Justice and Behavior. 37, 336-357.

Leite, W. L., & Cooper, L. A. (2010). Detecting social desirability bias using factor mixture models. Multivariate Behavioral Research, 45, 271-293.

Leite, W. L., Svinicki, M., & Shi, Y. (2010). Attempted validation of the scores of the VARK: Learning Styles Inventory with multitrait–multimethod confirmatory factor analysis models. Educational and Psychological Measurement. 70, 323-339.

Tuccitto, D. E., Giacobbi Jr., P. R.,  & Leite, W. L. (2010). The internal structure of positive and negative affect: A confirmatory factor analysis of the PANASEducational and Psychological Measurement, 70, 125-141.

Shi, Y., Leite, W. L., & Algina, J. (2010). The impact of omitting the interaction between crossed factors in cross-classified random effects modeling. British Journal of Mathematical and Statistical Psychology.63, 1-15.

Huang, I. C., Shenkman, E. A., Leite, W., Knapp, C. A., Thompson, L. A., & Revicki, D. A. (2009). Agreement was not found in adolescents’ quality of life rated by parents and adolescentsJournal of Clinical Epidemiology, 62, 337-346.

Lane, H. B., Hudson, R. F., Leite, W. L., Kosanovich, M. L., Strout, M. T., Fenty, N. S., & Butler, T. W.  (2009). Teacher knowledge about reading fluency and students’ reading fluency growth in Reading First schools. Reading and Writing Quarterly. 25(1), 57-86.

Leite, W. L., Huang, I., & Marcoulides, G. A. (2008). Item selection for the development of short-forms of scales using an Ant Colony Optimization algorithm. Multivariate Behavioral Research.43, 411-431.

Huang, I., Liu, J., Wu, A., Wu, M., Leite, W., & Hwang, C. (2008). Evaluating the reliability, validity and minimally important difference of the Taiwanese version of the Diabetes Quality of Life (DQOL) measurementHealth and Quality of Life Outcomes. 6, 87-99.

Huang I., Hwang, C. Wu M., Leite, W. L., & Wu A. W. (2008). Diabetes-specific or generic measures for health-related quality of life? Evidence from psychometric validation of the D-39 and SF-36Value in Health, 11, 405-461.

Huang I., Frangakis C., Atkinson, M. J., Willkes, R. J., Leite, W. L., Vogel, W. B., & Wu., A. W. (2008). Addressing ceiling effects in health status measures: A comparison of techniques applied to measures for people with HIV diseaseHealth Services Research. 43,  327-339.

Leite, W. L. (2007). A comparison of latent growth models for constructs measured by multiple Items. Structural Equation Modeling. 14, 581-610.

Leite, W. L., & Beretvas, S. N. (2005). Validation of scores on the Marlowe-Crowne Social Desirability Scale and the Balanced Inventory of Desirable Responding.Educational and Psychological Measurement, 65, 140-154.

Stapleton, L. M., & Leite, W. L. (2005). A review of syllabi for a sample of structural equation modeling courses. Structural Equation Modeling, 12, 642-664.

Beretvas, S. N., Meyers, J. L., & Leite, W. L. (2002). A reliability generalization study of the Marlowe-Crowne Social Desirability ScaleEducational and Psychological Measurement, 62(4), 570 -589.