Search Results - "Sterba, Sonya"

Quantifying Explained Variance in Multilevel Models: An Integrative Framework for Defining R-Squared Measures by Rights, Jason D., Sterba, Sonya K.

“…Researchers often mention the utility and need for R-squared measures of explained variance for multilevel models (MLMs). Although this topic has been…”
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Fitting Nonlinear Latent Growth Curve Models With Individually Varying Time Points by Sterba, Sonya K.

“…Individual growth trajectories of psychological phenomena are often theorized to be nonlinear. Additionally, individuals' measurement schedules might be…”
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r2mlm: An R package calculating R-squared measures for multilevel models by Shaw, Mairead, Rights, Jason D., Sterba, Sonya S., Flake, Jessica Kay

“…Multilevel models are used ubiquitously in the social and behavioral sciences and effect sizes are critical for contextualizing results. A general framework of…”
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Partially nested designs in psychotherapy trials: A review of modeling developments by Sterba, Sonya K.

“…Objective: Individually-randomized psychotherapy trials are often partially nested. For instance, individuals assigned to a treatment arm may be clustered into…”
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New Recommendations on the Use of R-Squared Differences in Multilevel Model Comparisons by Rights, Jason D., Sterba, Sonya K.

“…When comparing multilevel models (MLMs) differing in fixed and/or random effects, researchers have had continuing interest in using R-squared differences to…”
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Understanding Linkages Among Mixture Models by Sterba, Sonya K.

“…The methodological literature on mixture modeling has rapidly expanded in the past 15 years, and mixture models are increasingly applied in practice…”
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Problems with Rationales for Parceling that Fail to Consider Parcel-Allocation Variability by Sterba, Sonya K.

“…In structural equation modeling applications, parcels-averages or sums of subsets of item scores-are often used as indicators of latent constructs…”
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Cautions on the Use of Multiple Imputation When Selecting Between Latent Categorical versus Continuous Models for Psychological Constructs by Sterba, Sonya K

“…Clinical psychology researchers studying adolescents and young adults long have been interested in characterizing the latent categorical (classes/profiles)…”
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Closing the Word-Problem Achievement Gap in First Grade: Schema-Based Word-Problem Intervention with Embedded Language Comprehension Instruction by Fuchs, Lynn S, Seethaler, Pamela M, Sterba, Sonya K, Craddock, Caitlin, Fuchs, Douglas, Compton, Donald L, Geary, David C, Changas, Paul

“…The main purpose of this study was to test the effects of word-problem (WP) intervention, with versus without embedded language comprehension (LC) instruction,…”
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Building Word-Problem Solving and Working Memory Capacity: A Randomized Controlled Trial Comparing Three Intervention Approaches by Fuchs, Lynn S., Fuchs, Douglas, Sterba, Sonya K., Barnes, Marcia A., Seethaler, Pamela M., Changas, Paul

“…This study's purpose was to investigate effects of 3 intervention approaches for building working memory (WM) and improving word-problem solving (WPS)…”
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R-squared Measures for Multilevel Models with Three or More Levels by Rights, Jason D., Sterba, Sonya K.

“…Applications of multilevel models (MLMs) with three or more levels have increased alongside expanding software capability and dataset availability. Though…”
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On the Common but Problematic Specification of Conflated Random Slopes in Multilevel Models by Rights, Jason D., Sterba, Sonya K.

“…For multilevel models (MLMs) with fixed slopes, it has been widely recognized that a level-1 variable can have distinct between-cluster and within-cluster…”
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Pattern Mixture Models for Quantifying Missing Data Uncertainty in Longitudinal Invariance Testing by Sterba, Sonya K.

“…Many psychology applications assess measurement invariance of a construct (e.g., depression) over time. These applications are often characterized by few time…”
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Fitting Multilevel Models with Ordinal Outcomes: Performance of Alternative Specifications and Methods of Estimation by Bauer, Daniel J, Sterba, Sonya K

“…Previous research has compared methods of estimation for fitting multilevel models to binary data, but there are reasons to believe that the results will not…”
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Matching method with theory in person-oriented developmental psychopathology research by Sterba, Sonya K, Bauer, Daniel J

“…The person-oriented approach seeks to match theories and methods that portray development as a holistic, highly interactional, and individualized process. Over…”
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R-squared Measures for Multilevel Mixture Models with Random Effects by Sterba, Sonya K., Rights, Jason D.

“…Multilevel regression mixtures involving both discrete latent classes and continuous random effects are an increasingly popular approach for accommodating…”
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Aptitude-by-Treatment Interactions in Research on Educational Interventions by Preacher, Kristopher J., Sterba, Sonya K.

“…A common theme uniting articles in this special issue is a focus on aptitude-by-treatment interactions (ATIs). This timely and welcome focus allows the field…”
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Effect size measures for longitudinal growth analyses: Extending a framework of multilevel model R‐squareds to accommodate heteroscedasticity, autocorrelation, nonlinearity, and alternative centering strategies by Rights, Jason D., Sterba, Sonya K.

“…Developmental researchers commonly utilize multilevel models (MLMs) to describe and predict individual differences in change over time. In such growth model…”
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Effects of Parceling on Model Selection: Parcel-Allocation Variability in Model Ranking by Sterba, Sonya K., Rights, Jason D.

“…Research interest often lies in comparing structural model specifications implying different relationships among latent factors. In this context parceling is…”
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Transfer Between Reading Comprehension and Word-Problem Solving Among Children With Learning Difficulty in Both Domains by Fuchs, Lynn S., Seethaler, Pamela M., Sterba, Sonya K., Fuchs, Douglas, Cutting, Laurie E., Mancilla-Martinez, Jeannette, Martin, BrittanyLee N., Espinas, Daniel

“…Reading comprehension (RC) and word-problem solving (WPS) both involve text processing. Yet, despite evidence that RC text-structure intervention (RC.INT)…”
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