Recent publications and conference presentations.
Zhang, Y. and M. H. C. Lai (2024). “Evaluating two small-sample corrections for fixed-effects standard errors and inferences in multilevel models with heteroscedastic, unbalanced, clustered data”. In: Behavior Research Methods 56.6, p. 5930–5946. ISSN: 1554-3528. DOI: 10.3758/s13428-023-02325-9.
Lai, M. H. C. and W. W. -. Tse (2024). “Are factor scores measurement invariant?” In: Psychological Methods. ISSN: 1082-989X. DOI: 10.1037/met0000658. [postprint]
Lai, M. H. C., Y. Zhang, and F. Ji (2024). “Correcting for Sampling Error in between-Cluster Effects: An Empirical Bayes Cluster-Mean Approach with Finite Population Corrections”. In: Multivariate Behavioral Research 59.3, p. 584–598. ISSN: 1532-7906. DOI: 10.1080/00273171.2024.2307034. [postprint]
Zhang, Y., M. H. C. Lai, and G. J. Palardy (2023). “A Bayesian region of measurement equivalence (ROME) approach for establishing measurement invariance.” In: Psychological Methods 28.4, p. 993–1004. ISSN: 1082-989X. DOI: 10.1037/met0000455.
Liu, Y., M. H. C. Lai, and B. Kelcey (2023). “Comparing MIMIC and MIMIC-interaction to Alignment Methods for Investigating Measurement Invariance concerning a Continuous Violator”. In: Structural Equation Modeling: A Multidisciplinary Journal 31.2, p. 296–309. ISSN: 1532-8007. DOI: 10.1080/10705511.2023.2240517.
Ozturk, E. D., Y. Zhang, M. H. C. Lai, et al. (2023). “Measurement Invariance of the Neurobehavioral Symptom Inventory in Male and Female Million Veteran Program Enrollees Completing the Comprehensive Traumatic Brain Injury Evaluation”. In: Assessment 31.5, p. 967–979. ISSN: 1552-3489. DOI: 10.1177/10731911231198214.
Tse, W. W., M. H. C. Lai, and Y. Zhang (2023). “Does strict invariance matter? Valid group mean comparisons with ordered-categorical items”. In: Behavior Research Methods 56.4, p. 3117–3139. ISSN: 1554-3528. DOI: 10.3758/s13428-023-02247-6.
Lai, M. H. C. and Y. Zhang (2022). “Classification Accuracy of Multidimensional Tests: Quantifying the Impact of Noninvariance”. In: Structural Equation Modeling: A Multidisciplinary Journal 29.4, p. 620–629. ISSN: 1532-8007. DOI: 10.1080/10705511.2021.1977936. [postprint]
Lai, M. H. C. and Y. Hsiao (2022). “Two-stage path analysis with definition variables: An alternative framework to account for measurement error.” In: Psychological Methods 27.4, p. 568–588. ISSN: 1082-989X. DOI: 10.1037/met0000410. [postprint]
Lai, M. H. C., Y. Zhang, and F. Ji (2022). “Correcting for sampling error in between-cluster effects: An empirical Bayes cluster-mean approach with finite population corrections”. DOI: 10.31234/osf.io/3m7hj.
Yu, B. C. L., F. H. N. Chio, K. K. Y. Chan, et al. (2022). “Associations between public and self-stigma of help-seeking with help-seeking attitudes and intention: A meta-analytic structural equation modeling approach.” In: Journal of Counseling Psychology. ISSN: 0022-0167. DOI: 10.1037/cou0000637.
Lai, M. H. C., W. W. Tse, G. Zhang, et al. (2022). “Correcting for Unreliability and Partial Invariance: A Two-Stage Path Analysis Approach”. In: Structural Equation Modeling: A Multidisciplinary Journal 30.2, p. 258–271. ISSN: 1532-8007. DOI: 10.1080/10705511.2022.2125397. [postprint]
Lai, M. H. C. (2021). “Composite reliability of multilevel data: It’s about observed scores and construct meanings.” In: Psychological Methods 26.1, p. 90–102. ISSN: 1082-989X. DOI: 10.1037/met0000287. [postprint]
Ji, Y., W. Luo, M. H. Lai, et al. (2021). “Model-Selection-Based Approaches to Identifying the Optimal Number of Factors in Multilevel Exploratory Factor Analysis”. In: Structural Equation Modeling: A Multidisciplinary Journal 28.5, p. 763–777. ISSN: 1532-8007. DOI: 10.1080/10705511.2021.1916394.
Lai, M. H. C., Y. Liu, and W. W. Tse (2021). “Adjusting for partial invariance in latent parameter estimation: Comparing forward specification search and approximate invariance methods”. In: Behavior Research Methods 54.1, p. 414–434. ISSN: 1554-3528. DOI: 10.3758/s13428-021-01560-2. [postprint]
Lai, M. H. C. (2021). “Adjusting for Measurement Noninvariance with Alignment in Growth Modeling”. In: Multivariate Behavioral Research 58.1, p. 30–47. ISSN: 1532-7906. DOI: 10.1080/00273171.2021.1941730. [postprint]
Hsiao, Y., O. Kwok, and M. H. C. Lai (2020). “Modeling Measurement Errors of the Exogenous Composites From Congeneric Measures in Interaction Models”. In: Structural Equation Modeling: A Multidisciplinary Journal 28.2, p. 250–260. ISSN: 1532-8007. DOI: 10.1080/10705511.2020.1782206.
Lai, M. H. C. (2020). “Bootstrap Confidence Intervals for Multilevel Standardized Effect Size”. In: Multivariate Behavioral Research 56.4, p. 558–578. ISSN: 1532-7906. DOI: 10.1080/00273171.2020.1746902. [postprint]
Lai, M. H. C. (2019). “Correcting Fixed Effect Standard Errors When a Crossed Random Effect Was Ignored for Balanced and Unbalanced Designs”. In: Journal of Educational and Behavioral Statistics 44.4, p. 448–472. ISSN: 1935-1054. DOI: 10.3102/1076998619843168. [postprint]
Lai, M. H., G. B. Richardson, and H. W. Mak (2019). “Quantifying the impact of partial measurement invariance in diagnostic research: An application to addiction research”. In: Addictive Behaviors 94, p. 50–56. ISSN: 0306-4603. DOI: 10.1016/j.addbeh.2018.11.029. [postprint]
Zhang, G., & Lai, M. H. C. (2023, July 25-28). A Two-Stage Path Analysis Approach to Model Interaction Effects for Congeneric Measures [Oral presentation]. European Congress of Methodology (EAM), Ghent, Belgium. https://eam2023.ugent.be/images/eam2023_abstracts_book.pdf
Zhang, Y., & Lai, M. H. C. (2023, July 25-28). Alignment with Bayesian Region of Measurement Equivalence (ABROME) approach for multiple groups comparisons [Oral presentation]. Annual Meeting of the Psychometric Society (IMPS), College Park, Maryland, United States. https://modeling.uconn.edu/2023-preliminary-program/
Tse, W. W. Y., & Lai, M. H. C. (2023, July 25-28). Addressing publication bias and uncertainty for power analysis: A hybrid classical-Bayesian approach [Oral presentation]. Annual Meeting of the Psychometric Society (IMPS), College Park, Maryland, United States. https://modeling.uconn.edu/2023-preliminary-program/
Liu, Y., & Lai, M. H. C. (2023, July 25-28). Examining SEM Trees for Investigating Measurement Invariance Concerning Multiple Violators [Oral presentation]. Annual Meeting of the Psychometric Society (IMPS), College Park, Maryland, United States. https://modeling.uconn.edu/2023-preliminary-program/
Blozis, S., & Lai, M. H. C. (2023, July 25-28). A two-stage approach to a latent variable mixed-effects location scale model [Oral presentation]. Annual Meeting of the Psychometric Society (IMPS), College Park, Maryland, United States. https://www.psychometricsociety.org/sites/main/files/file-attachments/imps2023-abstracts.pdf
Liu, Y., & Lai, M. H. C. (2023, June 26-28). Examining SEM Trees for Investigating Measurement Invariance Concerning Multiple Violators [Paper session]. Modern Modeling Methods Conference, Storrs, CT, United States. https://modeling.uconn.edu/2023-preliminary-program/
Ji, Y., Luo, W., Lai, M. H. C., Kwok. O., & Yoon, M. (2023, April 13-16). An Eigenvalues-Based Approaches to Identifying the Optimal Number of Factors in Multilevel Exploratory Factor Analysis [Roundtable presentation]. AERA Annual Meeting, Chicago, IL, United States. https://convention2.allacademic.com/one/aera/aera23
Lai, M. H. C., Zhang, Y., & Ji, F. (2023, April 13-16). An Empirical Bayes Cluster-Mean Approach to Correct for Sampling Error in Between-Cluster Effects [Poster presentation]. AERA Annual Meeting, Chicago, IL, United States. https://convention2.allacademic.com/one/aera/aera23
Tse, W. W. Y., & Lai, M. H. C. (2023, April 13-16). Addressing Uncertainty in Power Analysis for Designing Cluster Randomized Trials. [Paper session]. AERA Annual Meeting, Chicago, IL, United States. https://convention2.allacademic.com/one/aera/aera23
Lai, M. H. C., Tse, W. W. Y., Zhang, G., Li, Y., & Hsiao, Y. Y. (2022, September 21-24). Correcting for unreliability and partial invariance: A two-stage path analysis approach [Symposium presentation]. Society for Research on Educational Effectiveness 2022 Conference, Arlington, VA, United States. https://www.psychometricsociety.org/sites/main/files/file-attachments/imps2022-version-7-abstract.pdf
Zhang, G., & Lai, M. H. C. (2022, July 11-15). A systematic review of measurement invariance research of the CES-D across gender: calculation and report of effect size [Oral presentation]. Annual Meeting of the Psychometric Society (IMPS), Bologna, Italy. https://www.psychometricsociety.org/sites/main/files/file-attachments/imps2022-version-7-abstract.pdf
Tse, W. W., & Lai, M. H. C. (2022, July 11-15). Incorporating information from historical data for power analysis: A hybrid classical-Bayesian approach for multilevel studies [Oral presentation]. Annual Meeting of the Psychometric Society (IMPS), Bologna, Italy. https://www.psychometricsociety.org/sites/main/files/file-attachments/imps2022-version-7-abstract.pdf
Zhang, Y., & Lai, M. H. C. (2022, July 11-15). Bayesian region of measurement equivalence (ROME) approach with alignment [Oral presentation]. Annual Meeting of the Psychometric Society (IMPS), Bologna, Italy. https://www.psychometricsociety.org/sites/main/files/file-attachments/imps2022-version-7-abstract.pdf
Tse, W. W., & Lai, M. H. C. (2022, June 27-29). Incorporating Uncertainty in power analysis to more realistically determine sample size [Workshop]. Meeting of the Society for the Improvement of Psychological Science (SIPS), Victoria, B. C., Canada. https://docs.google.com/document/d/1Rka3f0ZY9BBZVIlZoVINrpyaJYeitpq1yKXBLukeMng
Zhang, Y., & Lai, M. H. C. (2022, April 21-26). Evaluating standard error estimators and resampling method for multilevel models on small samples with heteroscedasticity and unbalanced cluster sizes [Poster presentation]. AERA Annual Meeting, San Diego, CA, United States. https://convention2.allacademic.com/one/aera/aera22
Palardy, G. J., Zhang, Y., & Lai, M. H. C. (2022, April 21-26). Measurement invariance testing via the alignment method: Intersectional grouping and multiple cohorts [oral presentation]. AERA Annual Meeting, San Diego, CA, United States. https://convention2.allacademic.com/one/aera/aera22
Zhang, G., Yue, H., & Lai, M. H. C. (2021, July 19-23). A systematic review of measurement invariance research of the CES-D across gender [Poster presentation]. Virtual conference of the Psychometric Society (IMPS) due to covid-19. https://www.psychometricsociety.org/sites/main/files/file-attachments/imps_2021_virtual_schedule.pdf
Zhang, Y. & Lai, M. H. C. (2021, July 19-23). Classification Accuracy of multidimensional tests: Quantifying the impact of noninvariance [Oral presentation]. Virtual conference of the Psychometric Society (IMPS) due to covid-19. https://www.psychometricsociety.org/sites/main/files/file-attachments/imps_2021_virtual_schedule.pdf
Tse, W. W. & Lai, M. H. C. (2021, July 19-23). Incorporating uncertainty in design parameters: A hybrid classical-Bayesian power analysis approach for two-level cluster randomized trials [Oral presentation]. Virtual conference of the Psychometric Society (IMPS) due to covid-19. https://www.psychometricsociety.org/sites/main/files/file-attachments/imps_2021_virtual_schedule.pdf
Lai, M. H. C., Ji, F., & Chen, S. (2021, July 19-23). Obtaining reliability for daily diary data using multilevel factor analysis [Oral presentation]. Virtual conference of the Psychometric Society (IMPS) due to covid-19. https://www.psychometricsociety.org/sites/main/files/file-attachments/imps_2021_virtual_schedule.pdf
Hsiao, Y., Kwok, O., & Lai, M. H. C. (2021, April 8-12). Improving estimation accuracy of the tnteraction effects in models with composite scores [Structured poster session]. AERA Annual Meeting, Orlando, FL, United States. https://convention2.allacademic.com/one/aera/aera21
Lai, M. H. C. & Hsiao, Y. (2021, April). Two-stage path analysis with definition variables: A general framework for modeling with categorical indicators [Structured Poster Session]. AERA Annual Meeting, Orlando, FL, United States.
Wen, L., & Lai, M. H. C. (2021, April 8-12). A multilevel weighted bootstrap procedure to handle sampling weights [Paper session]. AERA Annual Meeting, Orlando, FL, United States. https://convention2.allacademic.com/one/aera/aera21
Lai, M. H. C. (2020, July). Multilevel bootstrap confidence intervals for standardized effect size [Paper Session]. Annual Meeting of the Psychometric Society (IMPS), College Park, MD, United States. Schedule
Tse, W. W. & Lai, M. H. C. (2020, July 14-17). Measurement Invariance for Ordered Categorical Variables: The Necessity of Strict Invariance for Valid Group Comparisons [Poster Session]. Annual Meeting of the Psychometric Society (IMPS), College Park, MD, United States. Schedule
Zhang, Y. & Lai, M. H. C. (2020, July 14-17). A Bayesian Region of Measurement Equivalence (ROME) Approach for Establishing Measurement Invariance [Poster Session]. Annual Meeting of the Psychometric Society (IMPS), College Park, MD, United States. Schedule
Tse, W. W. & Lai, M. H. C. (2020, June 25-26). Measurement Invariance for Ordered Categorical Variables: The Necessity of Strict Invariance for Valid Group Comparisons [Conference Session]. A Meeting of Methodologies (AMOM), Vancouver, BC, Canada. Powerpoint slides
Lai, M. H. C. (2020, June 2-3). Constructing bootstrap confidence intervals for standardized effect size in cluster-randomized trials [Paper Session]. Modern Modeling Methods Conference (MMM), Storrs, CT, United States. (Conference canceled)
Tse, W. W. & Lai, M. H. C. (2020, June 2-3). Path to valid means comparisons: The necessity of strict measurement invariance for ordered categorical variables [Poster Session]. Modern Modeling Methods Conference (MMM), Storrs, CT, United States. (Conference canceled)
Zhang, Y. & Lai, M. H. C. (2020, June 2-3). A Bayesian Region of Measurement Equivalence (ROME) Approach for Establishing Measurement Invariance [Poster Session]. Modern Modeling Methods Conference (MMM), Storrs, CT, United States. (Conference canceled)