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Interpretations of interactions in LGCM |
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Dear Dr Muthens, I am running a parallel process growth model with a time-invariant moderator, but have difficulties on the interpretation. My DV is well-being, my IV is friendship quality (both measured at 3 time points) and have an observed moderator (ethnic identity) measured at T1. I am intersted to see whether the initial levels of friendship quality and ethnic identity and their interaction (defined by the XWITH command) predict the slope of well-being. Results showed a negative effect of quality intercept, a negative effect of identity and a positive interaction on well-being slope. 1) I guess the negative main effects on well-being slope do not show that initial levels of quality and identity lead to decreases in well-being, but rather means that higher initial levels of quality and identity lead to lower levels of change in the slope of well-being? But how do I understand the direction of the change? 2) How can I interpret the positive effect of interaction? 3) For plotting the simple slopes between a latent growth factor and an observed variable, how can I obtain the variances of the IV, moderator and the interaction? Thank you very much. |
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1. When you have a significant interaction. you do not interpret the main effects. You interpret only the interaction. 2-3. Plot the interaction. See the LOOP option of Example 3.18. |
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Thanks Linda, also just a basic question to confirm: My univariate models showed that friendship quality increases over time and well-being is stable over time. If I find a significant and positive covariance between these two slopes, does this mean that increases in quality is associated with the increases in well-being, or increases in quality is associated with more stable well-being? Thank you. |
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It means increases in quality is associated with the increases in well-being. |
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