How to Model Longitudinal Data with Interval Data as Response Variable

sabataged — Sat, 26 Jan 2019 20:31:47 GMT

Hello,

I'm having trouble figuring out how to model my data. I am trying to determine gender difference in childhood PTSD at 3 different timepoints.

I have the following:

Predictor variables: Fixed effects such as gender, neighborhood, age, and race.

Outcome variable: PTSD Burden/SCORE

PTSD score is determined by tallying up the score for 17 items on a questionnaire. For each question, there are 4 ordinal choices ranging from 0-3. The answers to these questions add up to a total of 51 possible points. This scale can be considered as interval data.

I was modeling PTSD Burden as a continuous outcome using PROC MIXED, but after some reflection and research, I realized this might not the best way to model this data. For example, I was getting an intercept of 21.56, but it is impossible to get a non-integer PTSD score. I cannot find an integer option with PROC MIXED. As far as I know, only PROC OPTMODEL can give integer solutions. Do I need to transform my data in any way? Would anyone be able to point me in the right direction?

Thanks so much!

Re: How to Model Longitudinal Data with Interval Data as Response Variable

Rick_SAS — Sun, 27 Jan 2019 12:14:39 GMT

Personally, I don't have a problem saying that the average PTSD score (at time=0?) is 21.56. It's an average. We routinely hear that the average American family has 2.5 kids and 1.2 pets. Averages don't have to be integers.

Moving this topic to the Statistic Community for greater visibility.

topic How to Model Longitudinal Data with Interval Data as Response Variable in Statistical Procedures

How to Model Longitudinal Data with Interval Data as Response Variable

Re: How to Model Longitudinal Data with Interval Data as Response Variable