MENU ▼
Read by QxMD icon Read
search
OPEN IN READ APP
JOURNAL ARTICLE

The effect of dropout on the efficiency of D-optimal designs of linear mixed models

S A Ortega-Azurduy, F E S Tan, M P F Berger
Statistics in Medicine 2008 June 30, 27 (14): 2601-17
17943923
Dropout is often encountered in longitudinal data. Optimal designs will usually not remain optimal in the presence of dropout. In this paper, we study D-optimal designs for linear mixed models where dropout is encountered. Moreover, we estimate the efficiency loss in cases where a D-optimal design for complete data is chosen instead of that for data with dropout. Two types of monotonically decreasing response probability functions are investigated to describe dropout. Our results show that the location of D-optimal design points for the dropout case will shift with respect to that for the complete and uncorrelated data case. Owing to this shift, the information collected at the D-optimal design points for the complete data case does not correspond to the smallest variance. We show that the size of the displacement of the time points depends on the linear mixed model and that the efficiency loss is moderate.

Comments

You need to log in or sign up for an account to be able to comment.

No comments yet, be the first to post one!

Related Papers

Available on the App Store

Available on the Play Store
Remove bar
Read by QxMD icon Read
17943923
×

Search Tips

Use Boolean operators: AND/OR

diabetic AND foot
diabetes OR diabetic

Exclude a word using the 'minus' sign

Virchow -triad

Use Parentheses

water AND (cup OR glass)

Add an asterisk (*) at end of a word to include word stems

Neuro* will search for Neurology, Neuroscientist, Neurological, and so on

Use quotes to search for an exact phrase

"primary prevention of cancer"
(heart or cardiac or cardio*) AND arrest -"American Heart Association"