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| Johannes posted on Tuesday, July 14, 2020 - 11:08 am
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Commonality analysis is a statistical technique to decompose explained variance (R2) in a multiple regression into subcomponents accounted for a) uniquely by each predictor and b) jointly with the other predictor variables in the respective model. (e.g., Nimon et al., 2008)
This technique has recently been used in applied psychological research (e.g., Altani et al., 2019; Wolf & Zimprich, 2020)
I was wondering whether there is any way to derive the information required for commonality analysis from an M-Plus output of a (cross-sectional) 3-level structural equation model with one manifest criterion variable and multiple manifest predictors on each level.
Many Thanks!
Altani, A., Protopapas, A., Katopodi, K., & Georgiou, G. K. (2019). From individual word recognition to word list and text reading fluency. Journal of Educational Psychology.
Nimon, K., Lewis, M., Kane, R., & Haynes, R. M. (2008). An R package to compute commonality coefficients in the multiple regression case: An introduction to the package and a practical example. Behavior Research Methods, 40(2), 457-466.
Wolf, T., & Zimprich, D. (2020). What characterizes the reminiscence bump in autobiographical memory? New answers to an old question. Memory & Cognition, 1-16. |
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