HIERARCHICAL LINEAR MODELING

BMI/STAT 727

Theory and methods of fundamental statistical models for the analysis of longitudinal data, including repeated measures analysis of variance, linear mixed models, generalized linear mixed models, and generalized estimating equations. Introduction of how to implement these methods in statistical softwares such as in R and/or SAS, within the context of appropriate statistical models and carry out and interpret analyses.

EDPSYCH 763

An applied introduction to regression techniques is given, covering nonparametric regression, multiple linear regression and logistic regression. All applied analyses are done in the statistical programming language R.

EDPSYCH 960

Introduction to the theory and practice of structural equation modeling in the educational and social sciences, including path analysis, confirmatory factor analysis and hybrid models.

EDPSYCH 760

Introductory descriptive statistics and statistical inference; measures of central tendency and variability, confidence intervals, theory of hypothesis testing, correlation techniques.

EDPSYCH 761

Analysis of variance and covariance, multiple linear regression; chi-square and various nonparametric techniques.