problem with longitudinal dyadic data set

[jstebbings]

Hi all,

I have a data set that contains measurements from coaches and athletes before a training session and after a training session, for ten training sessions.

I am familiar with using MLwin for longitudinal data analysis assessing the relationships between independent and dependent variables at the within-person and between-person levels. However, normally, at each time point (i.e. ten training sessions), there are one set of variables measured. In my data set however, at each time point (i.e. the ten training sessions), we have measured variables before AND after the sessions.

As such, the post-session measures are the dependent variables, and the pre-session measures are the independent variables

Am i correct in thinking that this constitutes TWO elements of time, i.e. the pre-post session element and then the over time (ten sessions) element?

I would really like to assess the relationships between dependent and independent variables at the the within- and between-person levels, yet am unsure how to go about this with this type of data set.

If anyone could give me some advice or point me in the direction of studies who have used this type of 'pre- and post measues, over time' data structure, I would be extrenmely grateful.

I look forward to hearing back, thanks in advance,

Juliette

[RobFrench]

I'd assume the only time element was the 10 sessions, treating the before and after as the same time point.