This book illustrates the ease with which various features of LISREL 8 and PRELIS 2 can be implemented in addressing research questions that lend themselves to SEM. Its purpose is threefold: (a) to present a nonmathmatical introduction to basic concepts associated with SEM, (b) to demonstrate basic applications of SEM using both the DOS and Windows versions of LISREL 8, as well as both the LISREL and SIMPLIS lexicons, and (c) to highlight particular features of the LISREL 8 and PRELIS 2 progams that address important caveats related to SEM analyses.
This book is intended neither as a text on the topic of SEM, nor as a comprehensive review of the many statistical funcitons available in the LISREL 8 and PRELIS 2 programs. Rather, the intent is to provide a practical guide to SEM using the LISREL approach. As such, the reader is "walked through" a diversity of SEM applications that include both factor analytic and full latent variable models, as well as a variety of data management procedures.
Contents: Preface. Part I: Introduction. Structural Equation Models: The Basics. Using LISREL, PRELIS, and SIMPLIS. Part II: Single-Group Analyses. Application 1: Testing the Factorial Validity of a Theoretical Construct (First-Order CFA Model). Application 2: Testing the Factorial Validity of Scores From a Measuring Instrument (First-Order CFA Model). Application 3: Testing the Factorial Validity of Scores From a Measuring Instrument (Second-Order CFA Model). Application 4: Testing for Construct Validity: The Multitrait-Multimethod Model. Application 5: Testing the Validity of a Causal Structure. Part III: Multiple Group Analyses. Application 6: Testing for the Invariant Factorial Structure of a Theoretical Construct (First-Order CFA Model). Application 7: Testing for Invariant Factorial Structure of Scores From a Measuring Instrument (First-Order CFA Model). Application 8: Testing for Invariant Latent Mean Structures. Application 9: Testing for Invariant Pattern of Causal Structure. Part IV: LISREL, PRELIS, and SIMPLIS Through Windows. Application 10: Testing for Causal Predominance Using a Two-Wave Panel Model.
