There are many situations in which we may be interested in doing “multiple comparisons.” For example, after an ANOVA, we may want to compare individual groups to one another (post-hoc pairwise comparisons), or we may be running a variety of models within the same experiment. When making these comparisons, however, we increase the chance of […]
Meta-analysis is a statistical procedure for combining the results from multiple studies in an effort to synthesize their findings. Potential benefits include increased power (over individual studies), improved estimates of effect sizes, and the ability to resolve uncertainty when research disagrees. Meta-analysis has become a popular tool for researchers in many fields. In this workshop, […]
This workshop will teach participants how to make sense of their output from linear statistical models, with an emphasis on the meaning of the model parameters. The workshop is intended for participants who have at least one semester of statistics and some previous experience with linear regression or ANOVA. This is a review and is […]
Logistic regression models are part of the family of generalized linear models which can be used when the dependent variable is binary. This workshop is designed to teach researchers the fundamentals of logistic regression. After attendance at the workshop, you should be able to: Decide whether logistic regression is appropriate for your data Interpret results […]