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Best-Practice Recommendations for Estimating Cross-Level Interaction Effects Using Multilevel Modeling

Aguinis, Herman - ; Gottfredson, Ryan K. - ; Culpepper, Steven Andrew - ;

Multilevel modeling allows researchers to understand whether relationships between lower-level variables (e.g., individual job satisfaction and individual performance, firm capabilities and performance) change as a function of higher-order moderator variables (e.g., leadership climate, market-based conditions). We describe how to estimate such cross-level interaction effects and distill the technical literature for a general readership of management researchers, including a description of the multilevel model building process and an illustration of analyses and results with a data set grounded in substantive theory. In addition, we provide 10 specific best-practice recommendations regarding persistent and important challenges that researchers face before and after data collection to improve the accuracy of substantive conclusions involving cross-level interaction effects. Our recommendations provide guidance on how to define the cross-level interaction effect, compute statistical power and make research design decisions, test hypotheses with various types of moderator variables (e.g., continuous, categorical), rescale (i.e., center) predictors, graph the cross-level interaction effect, interpret interactions given the symmetrical nature of such effects, test multiple cross-level interaction hypotheses, test cross-level interactions involving more than two levels of nesting, compute effect-size estimates and interpret the practical importance of a cross-level interaction effect, and report results regarding the multilevel model building process.


Ketersediaan

Call NumberLocationAvailable
JOM3906PSB lt.dasar - Pascasarjana (Majalah)1
PenerbitUnited States: Sage Publication 2013
EdisiVol. 39 No. 6, Sep 2013
SubjekCross
level
moderation
multilevel modeling
interaction
ISBN/ISSN1557-1211
KlasifikasiNONE
Deskripsi Fisik1724 p.
Info Detail SpesifikJournal of Management
Other Version/RelatedTidak tersedia versi lain
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  • Best-Practice Recommendations for Estimating Cross-Level Interaction Effects Using Multilevel Modeling

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