This study investigated the effects of correlated
errors on the person x occasion design in which the
confounding effect of equal time intervals results in
correlated error terms in the linear model. Two specific
error correlation structures were examined: the
first-order stationary autoregressive (SARI), and the
first-order nonstationary autoregressive (NARI) with
increasing variance parameters. The effects of correlated
errors on the existing generalizability and dependability
coefficients were assessed by simulating
data with known variances (six different combinations
of person, occasion, and error variances), occasion
sizes, person sizes, correlation parameters, and increasing
variance parameters. Estimates derived from the
simulated data were compared to their true values. The traditional estimates were acceptable when the error
terms were not correlated and the error variances were
equal. The coefficients were underestimated when the
errors were uncorrelated with increasing error variances.
However, when the errors were correlated with equal
vanances the traditional formulas overestimated both
coefficients. When the errors were correlated with
increasing variances, the traditional formulas both overestimated
and underestimated the coefficients. Finally,
increasing the number of occasions sampled resulted in
more improved generalizability coefficient estimates
than dependability coefficient estimates. Index terms:
changing error variances, computer simulation, correlated
errors, dependability coefficients, generalizability
Bost, James E. (1995). The effects of correlated errors on generalizability and dependability coefficients. Applied Psychological Measurement, 19, 191-203. doi:10.1177/014662169501900206
Bost, James E..
The effects of correlated errors on generalizability and dependability coefficients.
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