Literature DB >> 20161453

A New Analytic Framework for Moderation Analysis --- Moving Beyond Analytic Interactions.

Wan Tang1, Qin Yu, Paul Crits-Christoph, Xin M Tu.   

Abstract

Conceptually, a moderator is a variable that modifies the effect of a predictor on a response. Analytically, a common approach as used in most moderation analyses is to add analytic interactions involving the predictor and moderator in the form of cross-variable products and test the significance of such terms. The narrow scope of such a procedure is inconsistent with the broader conceptual definition of moderation, leading to confusion in interpretation of study findings. In this paper, we develop a new approach to the analytic procedure that is consistent with the concept of moderation. The proposed framework defines moderation as a process that modifies an existing relationship between the predictor and the outcome, rather than simply a test of a predictor by moderator interaction. The approach is illustrated with data from a real study.

Entities:  

Year:  2009        PMID: 20161453      PMCID: PMC2790290     

Source DB:  PubMed          Journal:  J Data Sci        ISSN: 1680-743X


  11 in total

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Authors:  P Crits-Christoph; L Siqueland; J Blaine; A Frank; L Luborsky; L S Onken; L R Muenz; M E Thase; R D Weiss; D R Gastfriend; G E Woody; J P Barber; S F Butler; D Daley; I Salloum; S Bishop; L M Najavits; J Lis; D Mercer; M L Griffin; K Moras; A T Beck
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  2 in total

1.  Moderation analysis using a two-level regression model.

Authors:  Ke-Hai Yuan; Ying Cheng; Scott Maxwell
Journal:  Psychometrika       Date:  2013-12-12       Impact factor: 2.500

2.  Double-smoothing for Varying Coefficient Models.

Authors:  Wan Tang; Guoxin Zuo; Hua He
Journal:  J Nonparametr Stat       Date:  2011-12       Impact factor: 1.231

  2 in total

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