1 / 9

Multivariate Data Reduction and Meta-analysis

Multivariate Data Reduction and Meta-analysis. RCS6740 6/28/04. Multivariate Analyses. Multivariate Analyses Multivariate analysis permits simultaneous analysis of two or more dependent, independent, predictor, or criterion variables (Grimm & Yarnold, 1995). Univariate Example:

ebrad
Télécharger la présentation

Multivariate Data Reduction and Meta-analysis

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. Multivariate Data Reduction and Meta-analysis RCS6740 6/28/04

  2. Multivariate Analyses Multivariate Analyses • Multivariate analysis permits simultaneous analysis of two or more dependent, independent, predictor, or criterion variables (Grimm & Yarnold, 1995). • Univariate Example: • College GPA is predicted by H.S. GPA • Multivariate Example: • College GPA is predicted by H.S. GPA, class rank, and ACT scores

  3. Multivariate Analyses Cont. Common Types of Multivariate Analyses • Multiple Regression Prediction of one continuous variable from two or more continuous or nominal variables (Grimm & Yarnold, 1995).CGPA = a HSGPA + b ACT + e • Discriminant Analysis Prediction of one categorical variable from two or more continuous variables.Retention = a HSGPA + b ACT

  4. Multivariate Analyses Cont. Common Types of Multivariate Analyses • MANOV: Multivariate Analysis of Variance involves one or more categorical variables and two or more continuous variables (Grimm & Yarnold, 1995).Job Club interventions effect employment and job satisfaction.

  5. Data Reduction Data Reduction • Data reduction techniques group items (for example the items of a questionnaire) according to similarities in response patterns. Following are descriptions of common techniques.

  6. Data Reduction Cont. • Factor Analysis: A collection of continuous variables are grouped together. The groupings account for much of the variance of the original list with fewer variables (Grimm & Yarnold, 1995). • Cluster Analysis: A collection of variables (continuous and/or categorical) are grouped together based on their similarities. Cluster analysis can group items on questionnaires or it can group people according to similar responses on multiple measures (Williams, 1992).

  7. Data Reduction Cont. • When data reduction techniques are used on a questionnaire, they are often followed by a reliability procedure, for example Cronbach’s alpha to see how tightly the factors or clusters hang together.

  8. Meta-Analysis • Meta-Analysis is a type of statistical analysis designed to answer this question: • What is the probability of these multiple results from all these studies, in light of our research hypothesis? • In order to conduct a meta-analysis, the researcher creates a chart of means and effect sizes and then interprets the effect size

  9. Questions and Comments ?

More Related