Graduate level. Prerequisite: PSYC 7710 or equivalent.

This course covers topics including different types of experimental designs, analysis of variance, analysis of covariance, statistical power analysis, model diagnostics, and R programming to analyze experimental data.

Graduate level, advanced undergraduate level.

This course will provide a practical introduction to classic and modern Bayesian methods, with an emphasis on applications in social sciences. Bayesian estimation for several widely used models in psychology will also be discussed.

Advanced undergraduate level.

Research on sustainability aims at answering the age-old question of how to build a society that can sustain. In this course, we will learn innovative tools of longitudinal data analysis to investigate sustainability issues.

Graduate level.

This course provides an introduction to the principles and methods (e.g., multilevel models, mixed-effects models, latent growth curve models) for the analysis of longitudinal data. Emphasis is on data analysis and interpretation.

Undergraduate level.

In this engagement course, we will develop our answers to motivating questions by learning and understanding the idea of Bayesian methodology. We will explore the dynamic procedure of knowledge processing, how prior knowledge can contribute to our understanding, and how biased prior information may lead us to incorrect conclusions.

Undergraduate level. J-term course.

This course was co-taught by Cynthia and her colleagues Karen Schmidt and Joey Meyer in the January Terms of 2021 and 2022. Basis R programming, linear models, and advanced multiple regression topics were covered.

Undergraduate level. Prerequisite: PSYC2005 or PSYC3005.

Cynthia taught in Spring 2016.

A continuation of discussion of research methods and basic statistical analysis in psychology based on R programming.

June 2-3, 2022. 51 participants.

Topics of this workshop include Bayesian analysis of multilevel models, growth curve models, growth mixture models, and longitudinal structural equation models. Additionally, we teach the application of Bayesian robust methods for nonnormal ignorable and non-ignorable missing data.

Pacific Rim Objective Measurement Symposium (PROMS) 2021 – Preconference Workshop. December 4, 2021

The workshop discusses how to read, explore, and structure data with R , use data visualization packages to present psychological data in a visually informational and understandable way and connect R programming to psychology research.