A researcher collected some data to look at tiredness (measured on a 10-point scale ranging from 0 (I'm wide awake) to 10 (I can't keep my eyes open) as a predictor of the following mood states (people were classified into each mood based on a diary): more depressed than normal (score = 2), more anxious than normal (score = 1) or normal (score = 0). Which of the following tests would be the most appropriate method for analysing these data?
A)Loglinear analysis
B)Multiple regression
C)Multinomial logistic regression
D)Binary logistic regression

Question

Quizplus · Accepted Answer

Multinomial logistic regression is the most appropriate method for analysing these data as there are three categorical outcomes (more depressed than normal, more anxious than normal, and normal), and the predictor variable is continuous (tiredness measured on a 10-point scale). Binary logistic regression would only be appropriate if there were only two categorical outcomes, and multiple regression would not be appropriate for categorical outcomes. Loglinear analysis is more appropriate for analysing contingency tables with more than two categorical variables.

A Researcher Collected Some Data to Look at Tiredness (Measured