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Hi - I am estimating a model with all observed variables (nothing latent), but my dependent variables, along with one of the independent variables, have known reliabilities, which I would like to adjust the parameters for in the analysis. How can I do that? Thanks, Lindsay |
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See Slide 44 of the Topic 1 course handout on the website. |
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Thanks, Linda. I have looked at the slide but am concerned that I am misunderstanding something. My goal is to adjust the regression coefficients for the reliability of the variables, but what I have done has not changed the coefficients at all, just forced the residual variances to be equal to the values that I calculated. From Slide 44, I used the syntax y@a, where a = (1-reliability)*sample variance. So, for example, the variable fallpair has a reliability of 0.81 and a sample variance of 0.896, so I calculated (1-0.81)*0.896=0.17024. A sample of my model syntax is below. Can you tell me what I'm doing wrong? Also, why do I no longer get chi-square and RMSEA values when I do this reliability adjustment? Thank you, Lindsay fallpair@0.17024; parisei@0.3387; income@0.10724; fallpair ON parented parisei income gender age minority ; |
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In Slide 44 it shows In Mplus: f BY y@1; y@a; where a = θ You need to put a factor behind each variable and use the factors in the ON statements, for example, f1 BY fallpair; fallpair@0.17024; |
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