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This upper-level course focuses on data analysis methods for research involving fixed and random factors and where one or more factors are nested (non-independent) including individuals within clusters, time within individuals (growth modeling) measures within studies (meta-analysis) and multiple membership models (cross-classified). A variety of software is presented, including HLM, SAS, and SPSS. Pre-requisites: EDPSY 593 or 594, or equivalent. Recommended for graduate students who will be actively consuming or conducting quantitative research with nested data.

This upper-level course explores IRT models and their roles in the development of large scale educational and psychological tests. A variety of software is presented, including Bilog, Parscale, and Winsteps. Pre-requisites: Edpsy 592 and 594, or equivalent. Recommended for graduate students who will be actively consuming or developing high-quality assessment measures.

This upper-level course focuses on data analysis methods for research involving a variety of simple and complex latent factor structures, including confirmatory factor analysis, path models, growth models, and latent class and trait models. A variety of software is presented, including Amos, EQS, and Mplus. Pre-requisites: EDPSY 594 or equivalent. Recommended for graduate students who will be actively consuming or conducting quantitative research involving causal theoretical models.

This intensive course focuses on analyzing data collected from surveys, quasi-experiments, or experiments with a major emphasis on multiple linear and logistic regression (and introduction to exploratory factor analysis). SPSS software used. Pre-requisites: EDPSY 490 or equivalent. EDPSY 593 helpful but not necessary. Recommended for graduate students who will be actively consuming or conducting quantitative research with secondary data or survey data, as well as those who will be taking advanced coursework in multilevel or structural equation modeling.

This intensive course focuses on design and analysis of quantitative experiments, including fixed, random, and mixed analyses of variance as well as multiple comparison procedures. SPSS software used. Pre-requisites: EDPSY 490 or equivalent. Recommended for graduate students who will be actively consuming or conducting experimental or quasi-experimental research in their program, as well as those who will be taking more advanced coursework in multilevel or structural equation modeling.

This course focuses on classic test theory, including methods of evaluating reliability and validity of items contained in assessments and surveys. SPSS software used. Pre-requisites: EDPSY 490 or equivalent. Recommended for graduate students who will be working with or developing educational assessments as part of their research.

This course focuses on experimental and quasi-experimental research design methods, as well as APA writing standards. Discussions include applied readings in social science research. Pre-requisites: EDPSY 490 or equivalent. Recommended for beginning graduate students who need a broad overview of quantitative research methods, context for consuming research, and APA writing standards.

This course focuses on all aspects of survey research design, including sampling strategies and the science of instrument development. Pre-requisites: EDPSY 490 or equivalent. Recommended for graduate students who will be working with or developing surveys as part of their research.

Characteristics of applied behavior analysis research are presented: direct, daily measurement, and the systematic investigation of important variables. The primary logic of single subject design and the establishment of experimental control are reviewed. Representative studies from various applied situations are discussed in terms of dependent and independent variables, research design, reliability, validity, and data analysis. Pre-requisites: graduate standing in Education or permission of instructor.