Estimating and testing autocorrelation with small samples: A comparison of the c-statistic to a modified estimator |
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Authors: | Lawrence T. DeCarlo Warren W. Tryon |
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Affiliation: | Department of Psychology, Fordham University, Bronx, NY 10458, U.S.A. |
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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. |
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