Qn1. What do generalized linear models (GLMs) generalize?
The linear model, which encompasses the ANOVA The linear model, which is a subset of the ANOVA The general model, which supersedes the ANOVA The general model, which is a subset of the ANOVA None of the above
Qn2. Generalized linear models (GLMs) handled only between-subjects factors.
Qn3. Poisson regression is an example of a generalized linear model (GLM) with a Poisson distribution for the response and a log link function.
Qn4. Which of the following is not an example of a generalized linear model (GLM)?
Poisson regression Binomial regression Gamm regression Ordinal logistic regression All are GLMs
Qn5. The link function in a generalized linear model (GLM) most precisely relates what to what?
Factors to each of the responses Factors to the mean of the response Factors to the distribution of the response Factors to the error in the response None of the above
Qn6. Nominal logistic regression is also known as multinomial regression
Qn7. Multinomial regression with the cumulative logit link function is also know as:
Nominal logistic regression Ordinal logistic regression Poisson regression Binomial regression None of the above
Qn8. Poisson regression is often appropriate for analyzing which kind of data?
Error rates Success percentages Logarithmic distributions Rare event counts None of the above
Qn9. Exponential regression is a special case of which generalized linear model (GLM)
Poisson regression Binomial regression Ordinal logistic regression Gamm regression None of the above
Qn10. The generalized linear model (GLM) can be used in place of the linear mode (LM) for between-subjects designs.