Generalized Linear Models in Psychology and Statistics
Delve into the world of Generalized Linear Models (GLMs) in psychology and statistics with a focus on regression, model assumptions, parameter estimates, and model selection. Explore the application of GLMs in analyzing various types of data, including not normally distributed data, counts, and ordi
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Analyzing Experimental Design with One-Factor and Two-Factor GLMs
Comparing the experimental designs of one-factor (1-way ANOVA) and two-factor GLMs, this content explores biological questions that can be answered through the analysis of multiple factors simultaneously in experiments. It discusses sample sizes, drug treatments, factor levels, and concentration var
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Teaching Generalized Linear Models (GLMs) to Undergraduates and Graduates: Challenges and Successes
Teaching GLMs at the University of Auckland involves a collaborative effort, utilizing reproducible research techniques and foundational linear modeling concepts. The courses cover trend analysis, factor variables, mixing variables, and handling exceptions like curves and exponential relationships.
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Understanding Generalized Linear Models and Logistic Regression
Generalized Linear Models (GLMs) are a class of linear models consisting of random, systematic, and link function components. The random component identifies the dependent variable and its probability distribution, while the systematic component involves explanatory variables. The link function conn
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Teaching GLMs in Undergraduates and Graduates - Challenges and Successes
Discover the challenges and successes of teaching Generalized Linear Models (GLMs) to both undergraduates and graduates at the University of Auckland. Explore the strategies used to engage students in statistics concepts effectively.
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