Statistical Analysis of Repeated Measures Data Using SAS (and R)

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Sample Questions for the Final Exam
Ziad Taib Biostatistics, AZ MV, CTH
Name, department
Date
1
2
Question 1

• Formulate the general LMM and
• State its underlying assumptions.
• Explain/interpret its ingredients
• Explain what is meant by the marginal model
• Explain what is meant by the hierarchical model.
• Explain the difference between the marginal- and
  the hierarchical model

Date
2
3
Question 2

• Explain how and why the predicted values of the
  random effects in a linear mixed model can be
  used to identify outliers

Date
3
4
Question 3

• Formulate the generalized linear mixed model and
  give an example of your choice of its use.

Date
4
5
Question 4

• Skiss for how we can obtain a useful formula for
  the prediction of the random effects. Only a
  principle description is needed.

Date
5
6
Question 5

• Define missing at random and missing completely
  at random. Argue why the the direct maximum
  likelihood method can be used under a suitable
  ignorability condition.

Date
6
7
Question 6

• Explain what is meant by Multiple Imputation
  (MI). Describe the main algorithm used in MI and
  give a informal argument for why it is valid.

Date
7
8
Question 7

• Give two different candidates for the definition
  of residual in a general LMM.

Date
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