title: Estimating and testing autocorrelation with small samples: a comparison of the C-statistic to a modified estimator.
abstract: Huitema and McKean (Psychological Bulletin, 110, 291-304, 1991) recently showed, in a Monte-Carlo study, that five conventional estimators of first-order autocorrelation perform poorly for small (< 50) sample sizes. They suggested a modified estimator and a test for autocorrelation. We examine an estimator not considered by Huitema and McKean: the C-statistic (Young, Annals of Mathematical Statistics, 12, 293-300, 1941). A Monte-Carlo study of the small sample properties of the C-statistic shows that it performs as well or better than the modified estimator suggested by Huitema and McKean (1991). The C-statistic is also shown to be closely related to the d-statistic of the widely used Durbin-Watson test.
authors.affiliation: Department of Psychology, Fordham University, Bronx, NY 10458.
authors.forename: L T
authors.initials: LT
authors.lastname: DeCarlo
authors.forename: W W
authors.initials: WW
authors.lastname: Tryon
mesh_terms: D001699:Biometry; D005260:Female; D006801:Humans; D016013:Likelihood Functions; D008297:Male; D015233:Models, Statistical; D008962:Models, Theoretical