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Regression with Variables (loaded on ... |
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MSP posted on Monday, November 16, 2015 - 11:06 am
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Hello! Not sure where to post this, so I just started a new thread (sorry). I was wondering what is the conceptual difference between a simple multiple (logistic) regression, and a regression where my predictors are loaded on latent factors. Does the latter make sense? Y on X1-X10; !Y is binary vs. F1-F3 by X1-X10(*1); Y on X1-X10; The output estimates were different (Y on X1-X10), but their signs and significance are similar (some became smaller, some became bigger with F1-F3). What is the effect of loading X1-X10 to F1-F3 in X's prediction of Y? Can I say that X1-X10's prediction of Y is influenced by F1-F3? Any input would be appreciated. Thanks! |
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In the model using BY you are imposing a model, that is, putting a restriction on the correlations of the marginal distribution of the 10 x's while the other model allows them to be freely correlated. The model with BY is a bit strange because you don't relate the f1-f3 factors to other variables such as Y. |
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