1 / 9

META-ANALYSIS OF RESEARCH

META-ANALYSIS OF RESEARCH. LECTURE 7 EXPERIMENTAL DESIGN EFFECTS Victor L. Willson, Instructor. MODERATORS. Moderators are typically considered categorical variables for which effects differ across categories or levels

gershom
Download Presentation

META-ANALYSIS OF RESEARCH

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript


  1. META-ANALYSIS OF RESEARCH LECTURE 7 EXPERIMENTAL DESIGN EFFECTS Victor L. Willson, Instructor

  2. MODERATORS • Moderators are typically considered categorical variables for which effects differ across categories or levels • In a limited form, this can be considered a treatment-moderator interaction • Moderator analysis is more general in the sense that any parameters of a within-category analysis may change across categories (multigroup analysis concept in Structural Equation Modeling)

  3. Moderator Analysis- QBetween • Analog to ANOVA- split into Qbetween and Qwithin • QB = wiEi2– (wiEi)2 /wi where Ei is the mean for category i and wi is the total weight function for Ei • Remember that you constructed a mean effect for a study; the weight function for that mean effect is the sum of the weights that made up the mean: Ei = wjgj/wj for J effects in study I wi = wj

  4. Moderator Analysis- QWithin • Analog to ANOVA- split into Qbetween and Qwithin • QW = wj(i)(Ej(i) - MeanEi)2 I j where MeanEi is the mean for each category i, Ej(i) is an effect j in category i and wj(i) is the weight function for the jth effect in category i • This is analogous to the within-subjects term in ANOVA • Lipsey and Wilson do not give a very good equation for this on p. 121- confusing

  5. Computational Issues • The excel file “Meta means working COMPUTATIONS” provides a workbook to compute such effects • An exemplar is shown below, is in your set of materials • Computation of QB and QW are done from the summary data of Hedge’s g and sample sizes

  6. Moderator Example • For our Storybook reading example, we can break the effect into two design types: 1 = no baseline equivalence 2 = baseline equivalence Wasik = 2 Coyne = 1 Justice = 2 Fielding = 1

  7. Moderator Example • Select “Meta means working COMPUTATIONS” excel file • Reduce the number of studies to 2 in Design 1 and 2 in design 2 • Insert the Hedge’s g effects, Cntrl N, Trmt N into the correct boxes, all other effects will be correctly computed

  8. Storybook Reading Design Moderator effect QB sig., two design means are different QW nonsig., homogeneous effects within the two design categories

More Related