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Isaac posted on Thursday, April 02, 2009  11:31 pm



I have a question about regressing a covariate on the slope. If the variable on slope is significant, does that mean that the slope itself is significant as well as the variable being a predictor of the slope? Can you recommend an article related to this topic? 


In the regression of the slope growth factor on a covariate, a signficant relationship says that the covariate has a significant influence on the slope growth factor. This implies the slope growth factor has variance. See the Raudenbush and Bryk book on multilevel modeling. 

Isaac posted on Friday, April 03, 2009  7:54 pm



I have a follow up question if you don't mind. I have a model with a single freely estimated time point. The slope is significantly predicted by a covariate, however the mean for the quadratic for that class is also significant. I know that typically one can't interpret a linear slope when a quadratic trend is observed, however having freely estimated a time point, I've rendered the quadratic meaningless right? Should I then only attend to the slope? Also is the Raudenbush and Bryk book you recommend "Hierarchical Linear Models: Applications and Data Analysis Methods"? I ask because I always end up buying the wrong book by the right authors. 


I don't think it makes sense to have a quadratic model when you have free time scores. You should either capture the nonlinearity using a quadratic model or free time scores but not both. Yes, this is the book I referred to. 

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