Відео

Thanks for this and the first video. I understand that your data was a repeated measurements, which demands that you use random effect instead if fixed effect. Why then did you refer to "fixed effect" when you added the predictors?

Is there a link to access the data frame you used. It could be so nice helping me practice alongside.

Thank uu so much

Really helpful :-)

Does this analysis perform data estimation or casewise deletion?

Thank you!!!!! Saved me from LOADS of work

i have adoubt 1) the covariance between error terms in measurement model need to be maintained in sem analysis?

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Thanks Paul. Just want to confirm something re the random-intercept term. The point of adding this term is to soak up the between-subject variance. In other words, if we didn’t add this term, the model would still run, but the p-value would be much larger. The addition of the random-intercept term is not related to the fact that each participant is measured multiple times (in violation of the assumption of independence of observations). I’m asking because I think you said both of the above: we add the random-intercept term (1) to account for the fact that the participants will differ from each other in their responses to the predictor variable, and/or (2) because each participant is measured multiple times.

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Thank you very much, Prof Paul. Your video has helped me immensely.

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What if your between subject variable is continuous?

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