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Andrew Gelman; Daniel Lee; Jiqiang Guo – Journal of Educational and Behavioral Statistics, 2015
Stan is a free and open-source C++ program that performs Bayesian inference or optimization for arbitrary user-specified models and can be called from the command line, R, Python, Matlab, or Julia and has great promise for fitting large and complex statistical models in many areas of application. We discuss Stan from users' and developers'…
Descriptors: Programming Languages, Bayesian Statistics, Inferences, Monte Carlo Methods
Quesen, Sarah – ProQuest LLC, 2016
When studying differential item functioning (DIF) with students with disabilities (SWD) focal groups typically suffer from small sample size, whereas the reference group population is usually large. This makes it possible for a researcher to select a sample from the reference population to be similar to the focal group on the ability scale. Doing…
Descriptors: Test Items, Academic Accommodations (Disabilities), Testing Accommodations, Disabilities
Özdemir, Murat; Demircioglu, Ebru – Educational Management Administration & Leadership, 2015
In recent years educational organizations have begun to be administered by more sharing, participation and democratic principles. The school-based management approach accelerated during the decentralization period in education is also seen as a cause for spread of leadership throughout the school. This trend is reflected in the educational…
Descriptors: Foreign Countries, High Schools, Participative Decision Making, School Based Management
Boyajian, Jonathan – Online Submission, 2011
This conference presentation reviews the authors' work on autocorrelations in single-case designs. The bias-corrected autocorrelation is computed, results are meta-analyzed with 5-level multilevel analysis in SAS Proc Mixed. Results suggest autocorrelations are normally distributed, and that taking into account nesting in outcomes and articles…
Descriptors: Correlation, Research Design, Meta Analysis, Statistical Distributions
Shin, Jihyung – ProQuest LLC, 2012
This research is motivated by an analysis of reading research data. We are interested in modeling the test outcome of ability to fluently recode letters into sounds of kindergarten children aged between 5 and 7. The data showed excessive zero scores (more than 30% of children) on the test. In this dissertation, we carefully examine the models…
Descriptors: Educational Research, Hierarchical Linear Modeling, Reading Research, Kindergarten