Doing the Four-Step Right

Our response to Hayduk and Glaser will principally focus on their critique of the four-step procedure. Hayduk and Glaser project things into the four-step procedure that are not part of its conception. They fail to see the implicit context in which those who use this particular four-step procedure operate, which qualifies its application. They also have misunderstandings about the rationale for the procedure and read too much of exploratory factor analysis into its use. Hayduk (1996) proposed a method for doing structural equation modeling with as few as one or two indicators per latent variable, which he feels is incompatible with the factor-analytic underpinnings of the four-step procedure and which motivates him further to seek its overthrow. He did not clarify this sufficiently on SEMNET, so we have been compelled to read Hayduk (1996) to better understand his position, and we will point out some limitations of it from our own point of view. We further argue that Hayduk’s (1996) advocacy of the use of fixed parameters in sparse measurement models is not a viable general alternative to the use of multiple indicators. Hayduk also believed the usual .05 level of significance in testing the exact fit of models favors the null hypothesis. He recommended that the significance level for a chi-square test be set at .75. We show this recommendation to be incoherent with the idea of a significance test and further show it to be unnecessary because, on the contrary, in most studies the null hypothesis is likely to be rejected. STRUCTURAL EQUATION MODELING,7(1), 36–73 Copyright © 2000, Lawrence Erlbaum Associates, Inc.

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