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8 shows how to read the data within a SAS file and how to create new files with a subset of the data saved in a format which can be read easily using the examples provided throughout this chapter. Use the model described in the examples above and adapt them to the data base to perform these tests. 26 Statistical Analysis of Management Data Multivariate Normal Distribution 27 References Basic Technical Readings Tatsuoka, M. M. (1971), Multivariate Analysis: Techniques for Educational and Psychological Research, New York, NY: John Wiley & Sons, Inc.

We discuss each step in turn and then we derive the factor loadings and the factor scores. Estimating commonalities In this first step, we need to remove the unique component of the variance in order to keep the variance explained by the common factors only. , the percentage of explained variance obtained in regressing variable j on the (p – 1) others). U is the residual variances from these regressions. Extracting initial factors The initial factors are obtained by performing a Principal Component Analysis on R Determining the number of factors The issue is to find the number of factors r < p which are necessary to represent the covariance structure.

Long, R. , W. P. Bowers, T. Barnett, et al. (1998), “Research Productivity of Graduates in Management: Effects of Academic Origin and Academic Affiliation,” Academy of Management Journal, 41, 6, 704–714. This page intentionally left blank 3. Measurement Theory: Reliability and Factor Analysis In this chapter, we will discuss the issues involved in building measures or scales. We focus the chapter on two types of analysis: (1) the measurement of reliability with Cronbach’s alpha and (2) the verification of unidimensionality using factor analysis.

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