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Lassibille, Gérard; Navarro Gómez, Mª Lucia – Education Economics, 2020
The paper aims to evaluate and compare across a large range of countries the impact of gender diversity on the overall job satisfaction of lower-secondary education teachers. It also seeks to examine whether the effects of gender similarity are asymmetrical for men and women. The empirical evidence is based on the estimation of multilevel models…
Descriptors: Job Satisfaction, Gender Differences, Disproportionate Representation, Cooperative Education
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Vidotto, Davide; Vermunt, Jeroen K.; van Deun, Katrijn – Journal of Educational and Behavioral Statistics, 2018
With this article, we propose using a Bayesian multilevel latent class (BMLC; or mixture) model for the multiple imputation of nested categorical data. Unlike recently developed methods that can only pick up associations between pairs of variables, the multilevel mixture model we propose is flexible enough to automatically deal with complex…
Descriptors: Bayesian Statistics, Multivariate Analysis, Data, Hierarchical Linear Modeling
Bilgili, Özge – OECD Publishing, 2017
This paper focuses on children with a migration background and conceptualises their migration experience as adversity. The paper adapts the resilience framework to understand how immigrant children can overcome adversity. The paper discusses policy models that can be derived from adopting a resilience approach to the measurement of immigrant…
Descriptors: Immigrants, Immigration, Models, Resilience (Psychology)
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Hollway, Jill A.; Aman, Michael G.; Butter, Eric – Journal of Autism and Developmental Disorders, 2013
We explored possible cognitive, behavioral, emotional, and physiological risk markers for sleep disturbance in children with autism spectrum disorders. Data from 1,583 children in the Autism Treatment Network were analyzed. Approximately 45 potential predictors were analyzed using hierarchical regression modeling. As medication could confound…
Descriptors: Correlation, Risk, Autism, Sleep
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Creech, Leah Renee; Sweeder, Ryan D. – CBE - Life Sciences Education, 2012
This study examined the historical performance of students at Michigan State University in 12 life sciences courses over 13 yr to find variables impacting student success. Hierarchical linear modeling predicted 25.0-62.8% of the variance in students' grades in the courses analyzed. The primary predictor of a student's course grade was his or her…
Descriptors: Academic Achievement, Majors (Students), Grade Point Average, Biochemistry