PPT-Exploratory Factor Analysis

STA431 Spring 2013 See last slide for copyright information Factor Analysis The Measurement Model D 1 D 8 D 7 D 6 D 5 D 4 D 3 D 2 F 1 F 2 Example with 2 factors and 8 observed variables. HURLEY TERRI A SCANDURA CHESTER A SCHRIESHEIM MICHAEL T BRANNICK ANSON SEERS ROBERT J VANDENBERG AND LARRY J WILLIAMS Department of Professional Studies Chapman University USA Department of Management University of Miami USA Department of Psycho AnnMaria De Mars, PhD.. The Julia Group & 7 Generation Games . WHY?. Imagine this. What exactly were you planning on doing with that?. Let’s say you have a massive pile of data …. . You Could:. Prepared by. Ferry . Dzulkifli. Tita. . Borshalina. FACTOR ANALYSIS. Factor Analysis Defined. Factor analysis . . .. is an interdependence technique whose primary purpose is to define the underlying structure among the variables in the analysis.. Lua Augustin, Savannah Guo, and Blair Marquardt. Learning Outcomes. To understand. :. What . is factor analysis.. What is its model.. Latent vs. observable variables; examples of each. .. Potential applications of factor analysis. Principal Component Analysis. Chapter 17. Terminology. Measured variables – the real scores from the experiment. Squares on a diagram. Latent variables – the construct the measured variables are supposed to represent. The purpose of factor analysis is to discover patterns in the relationships among the . variables. Factor Analysis. Form of multiple correlations. Checking for construct validity. Do questions measure the same dimension?. N. icole Zelinsky - . University of California, . Merced . - nzelinsky@ucmerced.edu. Introduction and Motivation. Exploratory Factor Analysis. Analytic . tool which helps researchers develop scales, generate theory, and inform structure for a confirmatory factor . Remark: covers Chapter 3 of the Tan book in Part. Organization. Why Exloratory Data Analysis?. Summary Statistics. Visualization. 1. Why Data Exploration?. Key motivations of data exploration include. STA431: Spring . 2015. See last slide for copyright information. Factor Analysis: The Measurement Model. D. 1. D. 8. D. 7. D. 6. D. 5. D. 4. D. 3. D. 2. F. 1. F. 2. Example with 2 factors and 8 observed variables. Prof. Andy Field. Slide . 2. Aims. Explore factor . a. nalysis and . p. rincipal . c. omponent . a. nalysis (PCA). What . Are . factors. ?. Representing . factors. Graphs and Equations. Extracting factors. The basic objective of Factor Analysis is data reduction or structure detection.. The purpose of . data reduction.  is to remove redundant (highly correlated) variables from the data file, perhaps replacing the entire data file with a smaller number of uncorrelated variables.. N. icole Zelinsky - . University of California, . Merced . - nzelinsky@ucmerced.edu. Introduction and Motivation. Exploratory Factor Analysis. Analytic . tool which helps researchers develop scales, generate theory, and inform structure for a confirmatory factor . Dept. of PHS, Division of . Biostats. & . Bioinf. Biostatistics Shares Resource, Hollings Cancer Center. Cancer Control Journal Club. March 3, 2016. Motivating Example. Goals of paper. 1. See if previously defined measurement model of hopelessness in advanced cancer fits this sample. Confirmatory Factor Analysis.. variables. Factor Analysis. Form of multiple correlations. Checking for construct validity. Do questions measure the same dimension?. For use between or within a test. Identify items which cluster together.