PPT-FACTOR ANALYSIS & SPSS

First lets check the reliability of the scale Go to Analyze Scale and Reliability analysis Select the items and transfer them into. 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. 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:. Min’-chen. ). muenchen@utk.edu. HelpDesk. : 974-9900. Newsletter: http://listserv.utk.edu/archives/rcnews.html. Research Computing Support. To help UT researchers use information technology and analytic methods to:. 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. 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?. http://dss.princeton.edu/training/ Factor analysis: introFactor analysis is used mostly for data reduction purposes:To get a small set of variables (preferably uncorrelated) from a large set of variab 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. 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.. 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.. 5. th . - 9. th. December 2011, Rome. Manage the database . Import / export file. Import variable from another database / merge files. Restructure cases to variables. Merging datasets. For each level of investigation in a survey, there is typically a dataset. Why do we analyze livelihoods?. Food security . analysis aims at informing geographical . and. socio-economic targeting. Livelihood analysis allows us to answer . one of the key basic questions of food security analysis: “who are the food insecure. 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. Karl L. Wuensch. Dept of Psychology. East Carolina University. When to Use PCA. You have a set of . p. continuous variables.. You want to repackage their variance into . m. components.. You will usually want .