TY - JOUR
T1 - Effects of sample size and nonnormality on the estimation of mediated effects in latent variable models
AU - Finch, John F.
AU - West, Stephen
AU - Mackinnon, David
N1 - Funding Information:
This research was funded in part by National Institute of Mental Health Grant P50-MH39246 and Public Health Service Grant DA 06211.
PY - 1997
Y1 - 1997
N2 - A Monte Carlo approach was used to examine bias in the estimation of indirect effects and their associated standard errors. In the simulation design, (a) sample size, (b) the level of nonnormality characterizing the data, (c) the population values of the model parameters, and (d) the type of estimator were systematically varied. Estimates of model parameters were generally unaffected by either nonnormality or small sample size. Under severely nonnormal conditions, normal theory maximum likelihood estimates of the standard error of the mediated effect exhibited less bias (approximately 10% to 20% too small) compared to the standard errors of the structural regression coefficients (20% to 45% too small). Asymptotically distribution free standard errors of both the mediated effect and the structural parameters were substantially affected by sample size, but not nonnormality. Robust standard errors consistently yielded the most accurate estimates of sampling variability.
AB - A Monte Carlo approach was used to examine bias in the estimation of indirect effects and their associated standard errors. In the simulation design, (a) sample size, (b) the level of nonnormality characterizing the data, (c) the population values of the model parameters, and (d) the type of estimator were systematically varied. Estimates of model parameters were generally unaffected by either nonnormality or small sample size. Under severely nonnormal conditions, normal theory maximum likelihood estimates of the standard error of the mediated effect exhibited less bias (approximately 10% to 20% too small) compared to the standard errors of the structural regression coefficients (20% to 45% too small). Asymptotically distribution free standard errors of both the mediated effect and the structural parameters were substantially affected by sample size, but not nonnormality. Robust standard errors consistently yielded the most accurate estimates of sampling variability.
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U2 - 10.1080/10705519709540063
DO - 10.1080/10705519709540063
M3 - Article
AN - SCOPUS:0001885793
SN - 1070-5511
VL - 4
SP - 87
EP - 107
JO - Structural Equation Modeling
JF - Structural Equation Modeling
IS - 2
ER -