Modeling Evaluation Essay Example | Topics and Well Written Essays - 500 words

Modeling Evaluation - Essay Example , management, business, and applied psychology are often interested in multivariate relationships among some or all of the variables in a specified model. Incidentally, SEM provides a viable statistical tool for exploring all of these relationships. It should be noted, however, that SEM is largely a confirmatory tool rather than an exploratory procedure (Diomantopoulos, Riefler, & Roth, 2008). This means that SEM will most likely be used by researchers in cases when the validity of a certain model is to be established, rather than it being used to find the appropriate model. Typically, the models being investigated depict processes presumed to underlie values obtained with sample data, and these processes are assumed to result in measures of association, like correlation, among the variables in the model (Ringle, Gotz, Wetzels, & Wilson, 2009). By and large, SEM is largely a â€Å"glorified† regression procedure which, unlike ordinary regression, doesn’t assume that measurement error is zero and can simultaneously estimate parameters representing the whole model rather than just pieces of the model (Ringle, Gotz, Wetzels , & Wilson, 2009). In the model proposed by Williams, Vandenberg, & Edwards (2009), it is greatly emphasized that researchers must give due consideration into the validity of a theory embedded or implied in the proposed measurement since there are many cases when indicators could be viewed as causing rather than being caused by the latent variable measured by the indicators. A latent variable is a variable that cannot be directly observed and must be inferred from measured variables (Burnette & Williams, 2010). In many cases, researchers will not be able to detect all possible causes of error because there may be some which have neither been discussed in prior literature nor revealed by exploratory research (Grace & Bollen). Furthermore, Williams, Vandenberg and Edwards argue that some goodness-of-fit indexes, such as chi-square, are meaningless