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Clearly these data support the notion that the use of latent variable modeling techniques by OBHRM researchers is on the rise.
Mulaik et al.'s (1989) RNFI, PGFI, RP, and RPFI, Marsh et al.'s (1988) IFI1 and IFI2, and Chou and Bentler's (1990) W and ML tests also began to appear in latent variable modeling in OBHRM research.
In addition to these characteristics reflecting model evaluation and fit, several other comparisons can be made between the OBHRM research from 1988 through 1993 and the studies reviewed by James and James (1989).
In summary, during the six-year 1988-1993 period, three times as many latent variable studies were published in OBHRM as in the previous ten year period (1978-1987).
First, there needs to be more consistency in OBHRM studies regarding the sequencing of model comparisons and the assessment of measurement models.
With respect to measurement model issues, we also recommend that OBHRM researchers examine their data for evidence of method variance effects.
A final concern regarding measurement issues and latent variable models with OBHRM studies involves assumptions made about the link between latent factors and their indicators.
Although it was not documented in the previous review, in nearly all of the OBHRM studies examined it was assumed that these residuals were uncorrelated.
Third, many fit measures used by OBHRM researchers, as shown in the present review, are now known to have problems.
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