1: Multinomial logistic regression is used when

1. the outcome variable is nominal with three or more categories.
2. the outcome variable is ordinal with three or more categories.
3. at least one predictor is nominal with three or more categories.
4. at least one predictor is ordinal with three or more categories.

2: The model significance tests for multinomial and ordinal regression use which of the following test statistics?

1. Odds ratios with 95% confidence intervals
2. F-statistics
3. Chi-squared statistics
4. Percent correctly predicted

3: One way to examine model fit for multinomial and ordinal regression is to compute

1. odds ratios with 95% confidence intervals.
2. F-statistics.
3. chi-squared statistics.
4. percent correctly predicted.

4: The assumptions for multinomial regression include

1. the proportional odds assumption.
2. a normally distributed outcome variable.
3. equal group variances.
4. independence of irrelevant alternatives.

5: The assumptions for ordinal regression include

1. the proportional odds assumption.
2. a normally distributed outcome variable.
3. equal group variances.
4. independence of irrelevant alternatives.