A Primer of LISREL: Basic Applications and Programming for - download pdf or read online

By Barbara M. Byrne

ISBN-10: 1461388856

ISBN-13: 9781461388852

ISBN-10: 1461388872

ISBN-13: 9781461388876

A Primer of LISREL represents the 1st entire consultant to using LISREL desktop programming in analyses of covariance constructions. instead of writing for the professional statistician, Dr. Byrne attracts examples from her personal examine in supplying a pragmatic consultant to functions of LISREL modeling for the unsophisticated consumer. This publication surpasses the opposite theoretically bulky manuals, because the writer describes methods and examples constructing for the person the 1st ebook requiring no complement to the knowledge of causal modeling and LISREL.

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Additional resources for A Primer of LISREL: Basic Applications and Programming for Confirmatory Factor Analytic Models

Sample text

There are 12 observed measures (Xs). These observed measures load onto the factors in the following pattern: X I -X3 load onto Factor 1; XCX6 load onto Factor 2; X,X9 load onto Factor 3; and XIO-Xl2load onto Factor 4. 38 3. 1. Hypothesized Structure of Four-Factor Model of Self-Concept. 5. Each X variable loads on one and only one factor. 6. Measurement error is taken into account for each X variable (8s). 7. the errors of measurement are uncorrelated. Summarizing these observations, we can now present a more formal description of our hypothesized model.

3, if the model to be analyzed is an all-X CFA model, then only the lambda-X (LX), phi (PH), and theta-delta (TD) ma- 4. Model Specification 23 trices are of interest. Alternatively, if an all-Y model is specified, then the lambda-Y (LY), psi (PS), and theta-epsilon (TE) matrices are of interest. In either case, the status of each of the three matrices must be specified. This means that LISREL parameters representing these matrices must be specified according to whether or not they are to be estimated, and if they are, then how they are to be estimated.

For example, it only makes sense to request the standardized solution after you have achieved the final best-fitting model. LISREL Output 1. Standard Output LISREL provides a standard output that is printed whether or not other selected options have been entered. It includes the following information: log of read control cards, the title, the parameter listing, the parameter specifications, the matrix to be analyzed, the initial estimates, the LISREL estimates (ML or ULS), and the overall goodness-of-fit measures.

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A Primer of LISREL: Basic Applications and Programming for Confirmatory Factor Analytic Models by Barbara M. Byrne

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