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2.6. CONTRACTIBILITY MIMIC MODEL (APPENDIX A) 55
Overall, the MIMIC model fits the data. All of the formative and reflective indicators are
significantly different from zero at a confidence level of 5%, as displayed in table 2.17 -
Panel A. This finding implies that all of the indicators need to be included in the index.
Table 2.17 also provides goodness-of-fit statistics for the model. To assess the fit of a SEM,
one must assess multiple measures (Kline 2005). As the indicators of model fit, I use the
chi 2 , the goodness-of-fit index (GFI), the adjusted goodness-of-fit index (AGFI), the comparative
fit index (CFI), the root mean square residual (RMR) and the root mean square
error of approximation (RMSEA). Kline (2005) suggests that the following values indicate
a good fit: an insignificant chi 2 ; a GFI, AGFI, and CFI greater than 0.90; a RMR close to
0; and an RMSEA less than 0.045. As shown in table 2.17 - Panel B, the indicators show
adequate model fit.
Table 2.17: Results of MIMIC Analysis
Panel A - Contractibility MIMIC Coefficient Std. Error Critical Ratio Prob.
Goal clarity > Contractibility 1.000
Measurability
> Contractibility 0.892 0.370 2.413 0.02
of outputs
Transformation
process
Contractibility >
> Contractibility 0.431 0.212 2.027 0.04
Difficulty to
assess work
0.238 0.058 4.129 0.00
Contractibility > Agreement
output quality
0.184 0.046 4.027 0.00
Contractibility >
Job
manceperfor-
0.193 0.052 3.697 0.00
‘a’ : variable based on directional expectation; significance calculated as onetailed
p-value
Panel B - Goodness-of-Fit Statistics Contractibility MIMIC
Chi 2 = 6.064 goodness-of-fit statistics
Degrees of freedom = 6 GFI = 0.994
Probability level = .416 AGFI = 0.978
CFI = 1.000
Multivariate normality RMR = 0.011
Kurtosis 2.046 (c.r. 1.862) RMSEA = 0.006