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.

journal_name

Behav Res Ther

authors

DeCarlo LT,Tryon WW

doi

10.1016/0005-7967(93)90009-j

subject

Has Abstract

pub_date

1993-11-01 00:00:00

pages

781-8

issue

8

eissn

0005-7967

issn

1873-622X

pii

0005-7967(93)90009-J

journal_volume

31

pub_type

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