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- W2083017130 abstract "This paper examines the implications of centering choices when using hierarchical linear modeling. Compared to using a level-1 predictor in its raw metric or as a grand-mean centercept, centering around the group mean can yield different outcomes when estimating and interpreting the level-1 intercept and slope. Additionally, when including level-2 predictors hypothesized to explain the variance in the level-1 intercept and slope, what each coefficient represents differs with the centering choice. As a result, it often but not always becomes possible, that researchers with different centering choices can reach different conclusions about the effects of the predictors and the interactions among them. These implications are illustrated with graphic and numeric examples and conceptual examples." @default.
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- W2083017130 date "2008-12-09" @default.
- W2083017130 modified "2023-09-27" @default.
- W2083017130 title "Centering in Hierarchical Linear Modeling" @default.
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- W2083017130 doi "https://doi.org/10.1080/19312450802310466" @default.
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