14 Tutorials

Question 1

What are the three ways of characterising missing data?

Answer 1

1. MCAR (missing completely at random)
2. MAR (missing at random, aka ‘ignorable non-response’)
3. MNAR (missing not at random, or non-ignorable non-response)

Question 2

What is the difference between MCAR, MAR and MNAR?

Answer 2

Missing completely at random (MCAR): data are missing independently of both observed and unobserved data. Example: a participant flips a coin to decide whether to complete the depression survey.

Missing at random (MAR): given the observed data, data are missing independently of unobserved data. Example: male participants are more likely to refuse to fill out the depression survey, but it does not depend on the level of their depression.

Missing Not at Random (MNAR): missing observations related to values of unobserved data. Example: participants with severe depression were more likely to not fill out the depression survey.

Question 3

What does the LMATRIX command give?

Answer 3

The between-subjects part of the interaction contrasts.

Question 4

What does the MMATRIX command give?

Answer 4

The within-subjects part of the interaction contrasts.