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Comparison of WABA and DETECT to other multilevel data analytic approaches
Responding to misunderstandings and misconceptions about WABA and DETECT
Because misunderstandings, misconceptions, and misperceptions about WABA and DETECT usually come from an attempt to overextend a particular approach, we have included a discussion of how to respond to misconceptions that come from each approach listed below. (Click on the approach below to see the discussion of that topic.) In the discussion for each approach, the approach is first briefly described with references given and second, the ways in which WABA and DETECT complement the approach are presented. The final section for each approach shows how misconceptions, misperceptions, and misunderstandings about WABA and DETECT often come from either expecting WABA and DETECT to be redundant with the approach of interest or expecting WABA and DETECT to have the same limitations of an approach of interest. Please e-mail comments and additions to conceptualizers@LevelsOfAnalysis.com. The focus here is on distinguishing WABA and DETECT from what the other approaches purport to do. There are controversies between these approaches that are not discussed in any detail here. Click below to be taken to the discussion for that topic:
Fisher's one way analysis of variance (ANOVA)
Bliese and Halverston's (1998) Modified (ANOVA) approach
Contextual analysis approach (e.g., James and Williams)
Hierarchical Linear Modeling (HLM) approach (e.g., Bryk and Raudenbush)
Multi-level and regular Structural Equation Modeling (e.g., Heck and Thomas)
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