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| B Chenoworth posted on Thursday, February 14, 2013 - 10:29 pm
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Hello,
I am running a conditional 'linear' latent growth curve model. Does it matter how the categorical predictor variables are coded (i.e., using 0/1 or 1/2 code)? I ask because I seem to get vastly different results when I code them differently?
Secondly, my unconditional model showed a significant negative slope - outcome decreased over time. When I add predictors to the model, the mean of the slope is no longer significant (although there is still significant variability around the slope mean). Why would this be?
Many thanks for your help. |
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No, the coding should not make a difference except for the intercepts of the growth factors.
When you add predictors of the growth factors your output shows the intercepts and not the means for the growth factors. |
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