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Unformatted text preview: STA 4107/5107 Chapter 10: Introduction to Structural Equation Modeling March 27, 2007 1 Key Terms Please review and learn these terms. SEM is extremely jargonladen. I even recommend for this topic that you create flashcards or vocabulary lists that you can memorize and refer to while studying. Below, new and jargon terms will be in italics. Please look them up if you need to. I will be defining these terms to some extent, but life will be easier for all of us if you have some exposure to them before lecture. My admonition to read the chapter before lecture is really crucial for this material. Below are some of the more important terms you will need to be familiar with for this lecture: Causal inference A dependence relationship of two or more variables in which the researcher clearly specifies that one or more variables is the cause of an outcome represented by at least one other variable. Causation The principle by which cause and effect are established between two variables. It requires a sufficient degree of association (covariance), that the cause occurs before the effect, and that no other reasonable causes for the outcome are present. Strictly, causation is almost never proven, but in practice strong theoretical support can make empirical estimation of causation possible. Communality The total amount of variance that a measured variable has in common with the constructs upon which it loads. Good measurement practice suggests that each measured variable should load on only one construct. Hence, it can be thought of as the variance explained in a measured variable by the construct. In confirmatory factor analysis (CFA), it is referred to as the squared multiple correlation for a measured variable. Confirmatory analysis The use of a multivariate technique to test (confirm) a prespecified rela tionship. It is the opposite of exploratory analysis . Construct An unobservable or latent concept that the researcher can define in conceptual terms but that cannot be directly measured (i.e. there is no single measurement that can be made that will totally and perfectly quantify the concept), or cannot be measured without error. 1 Endogenous constructs The latent , multivariate equivalents to dependent variables. It is repre sented by a variate of dependent variables. Exogenous constructs The latent , multivariate equivalents to independent variables. They are constructs determined by factors outside the model. Fixed parameter A parameter that has a value specified by the researcher. Most often the value specified is zero, indicating no relationship, although in some instances a nonzero value can be specified. Free parameter A parameter estimated by the structural equation program to represent the strength of a specified relationship. These parameters may occur in the measurement model (most often denoting loadings of indicators to constructs), as well as in the structural model (relationships among constructs)....
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This note was uploaded on 07/14/2011 for the course STA 4702 taught by Professor Staff during the Spring '08 term at University of Florida.
 Spring '08
 Staff

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