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Comparing effect of different predictors |
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Clio Berry posted on Thursday, July 26, 2012 - 7:42 am
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I have 3 latent variables; rel, belong, act. I also have 4 predictor variables; occ_hope, soc_hope, das_dp and das_na. The occ_hope and soc_hope are hope scores. The das_dp and das_na variables are measures of two kinds of self-beliefs. I want to know whether the hope variables are more important than the self-belief variables in predicting my latent variables. How do I do this? Sorry if this is a stupid question. Is it just a case of looking at the values of the standardised path coefficients and seeing which are bigger in magnitude? This is my model: Model: Act by sim_sc sim_ci lei_m f2f spo_resp; Belong by sim_p sim_b occ_hrs; Rel by srs_no srs_rec; sim_ci with sim_sc; rel belong act on occ_hope soc_hope das_dp das_na; |
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