By J. (John) Scott Long

ISBN-10: 080392044X

ISBN-13: 9780803920446

A statistical approach that may entice teams particularly - people who are presently utilizing the extra conventional means of exploratory issue research and those that have an interest within the research of covariance buildings, generally called the LISREL version. the 1st team will locate that this system might be extra acceptable to the research in their examine difficulties whereas the second one workforce will locate that confirmatory issue research is an invaluable first step to figuring out the LISREL version. This publication, and its better half quantity, Covariance constitution types, are designed to be learn consecutively. The proofs provided are basic, however the reader needs to believe pleased with matrix algebra with a view to comprehend the version.

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**Additional resources for Confirmatory factor analysis: a preface to LISREL**

**Example text**

Let Q be defined as E(qq'), where the (i,j)th element of Q is labeled qij. For example, assume that q contains three variables (n = 3). Then 6 and Thus, the (i,j)th element of Q, qij, is the expected value of the product of qi and qj. Page 24 Since it was assumed that the qi's are measured as deviations from their means, qij = COV(qi,qj) and qii = COV(qi,qi ) = VAR(qi). , Q = Q'). Matrices such as Q are called variance/covariance matrices, or simply covariance matrices. A number of definitions and assumptions can now be stated.

If x is a vector, then E(x) is a vector whose ith element is the expected value of the random variable xi. Figures, equations, and tables are numbered sequentially within chapters. 3 is the third table in Chapter 2. The same examples are developed throughout the text and are referred to by the same example number. Thus, if Example 2 is discussed in Chapter 4, the reader should realize that it is a continuation of Example 2 from earlier chapters. The literature on the confirmatory factor model uses Greek letters.

If d1 corresponds to random error in the measurement of psychological symptoms at time 1 (variable x1), and d3 corresponds to random error in the measurement of psychological symptoms at time 2 (variable x3), these errors in measurement might be correlated over time. That is, large errors in measurement at time 1 might correspond to large errors at time 2, and small Page 22 errors at time 1 might correspond to small errors at time 2. This possibility is represented by the curved arrow labeled q13 between d1 and d3.

### Confirmatory factor analysis: a preface to LISREL by J. (John) Scott Long

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