Assessing panel data in Smart PLS

Frequently asked questions about PLS path modeling.
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PLS Junior User
Posts: 1
Joined: Sun Jul 08, 2018 10:12 pm
Real name and title: Mr Peter Halliwell

Assessing panel data in Smart PLS

Post by c3195982 » Fri Jul 13, 2018 2:21 am

I would like some advice on how best to apply Smart PLS to a quasi-experimental longitudinal study. In particular, I would like some advice on how I should incorporate panel data (pre and post intervention scores) into the model assessment, e.g. should I create and utilise standardised residualised change scores, latent difference scores, or other? I am primarily interested in intra-individual change as opposed to inter-individual change.

In more detail, I would like to assess whether a change in 'cognitive skills' positively predicts a change in 'leadership effectiveness' and whether this is mediated by a change in 'leadership behaviour', and overall, moderated by 'participant readiness'. All variables in the model were measured pre and post intervention (leadership coaching) using multiple reflective indicators from multiple raters. There is no control group.

I look forward to your thoughts and advice. Thank you, Peter

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