Small Sample Properties of the Spearman Autocorrelation Estimator
- 1 April 1993
- journal article
- research article
- Published by SAGE Publications in Perceptual and Motor Skills
- Vol. 76 (2) , 384-386
- https://doi.org/10.2466/pms.1993.76.2.384
Abstract
The small sample properties of a variant of the Spearman rank correlation coefficient applied in the time-series context were investigated through Monte Carlo methods. The rank method ( r1S) has even greater bias than the highly biased conventional parametric procedure; a traditional test of H0: ρ1 = 0 based on ( r1S) yields unacceptable properties. Empirical small sample distributions associated with the rank coefficient differ markedly from the distributions predicted by asymptotic theory. It is concluded that neither rank nor conventional parametric estimators and hypothesis tests are appropriate for very small samples in applications of time-series analysis that have been recommended in the behavioral and social science literature.Keywords
This publication has 4 references indexed in Scilit:
- Autocorrelation estimation and inference with small samples.Psychological Bulletin, 1991
- Autocorrelation in Behavioral ResearchPublished by Springer Nature ,1986
- Statistical Analysis and Single-Subject DesignsPublished by Springer Nature ,1986
- On the Theoretical Specification and Sampling Properties of Autocorrelated Time-SeriesJournal of the Royal Statistical Society Series B: Statistical Methodology, 1946