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Sonya K. Sterba, Ph.D.

Affiliations: 
2010 Psychology University of North Carolina, Chapel Hill, Chapel Hill, NC 
Area:
Psychometrics Psychology
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Daniel J. Bauer grad student 2010 UNC Chapel Hill
 (Recovery of predictor relationships via semiparametric and parametric growth models under misspecification.)

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Publications

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Rights JD, Sterba SK. (2019) New Recommendations on the Use of R-Squared Differences in Multilevel Model Comparisons. Multivariate Behavioral Research. 1-32
Sterba SK. (2019) Problems with Rationales for Parceling that Fail to Consider Parcel-Allocation Variability. Multivariate Behavioral Research. 1-24
Rights JD, Sterba SK. (2018) Quantifying explained variance in multilevel models: An integrative framework for defining R-squared measures. Psychological Methods
Lee WY, Cho SJ, Sterba SK. (2018) Ignoring a Multilevel Structure in Mixture Item Response Models: Impact on Parameter Recovery and Model Selection. Applied Psychological Measurement. 42: 136-154
Preacher KJ, Sterba SK. (2018) Aptitude-by-Treatment Interactions in Research on Educational Interventions Exceptional Children. 85: 248-264
Rights JD, Sterba SK, Cho S, et al. (2018) Addressing model uncertainty in item response theory person scores through model averaging Behaviormetrika. 45: 495-503
Rights JD, Sterba SK. (2017) A Framework of R-Squared Measures for Single-Level and Multilevel Regression Mixture Models. Psychological Methods
Sterba SK, Rights JD. (2017) Effects of parceling on model selection: Parcel-allocation variability in model ranking. Psychological Methods. 22: 47-68
Gottfredson NC, Sterba SK, Jackson KM. (2016) Explicating the Conditions Under Which Multilevel Multiple Imputation Mitigates Bias Resulting from Random Coefficient-Dependent Missing Longitudinal Data. Prevention Science : the Official Journal of the Society For Prevention Research
Rights JD, Sterba SK. (2016) The relationship between multilevel models and non-parametric multilevel mixture models: Discrete approximation of intraclass correlation, random coefficient distributions, and residual heteroscedasticity. The British Journal of Mathematical and Statistical Psychology. 69: 316-343
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