1 / 6

Warsaw Summer School 2019, OSU S tudy A broad P rogram

Learn the fundamentals of factor analysis and how it can be used to describe variability among observed variables while reducing data. Explore techniques such as Principal Component and Principal Factor Analyses to summarize correlated indicators and gain insights into latent constructs.

aeccleston
Download Presentation

Warsaw Summer School 2019, OSU S tudy A broad P rogram

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. Warsaw Summer School 2019, OSUStudy Abroad Program Factor Analysis

  2. General definition • Factor analysis is a method used to describe variability among observed variables in terms of a potentially lower number of unobserved variables called factors. • Eg., variations in three or four observed variables mainly reflect the variations in a single unobserved (latent) variable. • The observed variables are modeled as linear combination of the potential factors, plus “error" terms.

  3. Reduction of data

  4. Reduction of data Different techniques Principal Component and Principal Factor Analyses

  5. PCA PCA is a statistical methodology for summarizing correlated indicators into one or more PCs. Each PC is a weighted average of the underlying indicators. Weights are chosen so as to maximize the explained proportion of the variance in the original set of indicators.

  6. Latent construct = Σ Weight*Variable • Differences between PC and PA

More Related