Paper Info
Title
Bootstrap power of the generalized correlation coefficient
Abstract
We present a bootstrap Monte Carlo algorithm for computing the power function of the generalized correlation coefficient. The proposed method makes no assumptions about the form of the underlying probability distribution and may be used with observed data to approximate the power function and pilot data for sample size determination. In particular, the bootstrap power functions of the Pearson product moment correlation and the Spearman rank correlation are examined. Monte Carlo experiments indicate that the proposed algorithm is reliable and compares well with the asymptotic values. An example which demonstrates how this method can be used for sample size determination and power calculations is provided.
Year
DOI
Venue
1996
10.1007/BF00162525
Statistics and Computing
Keywords
Field
DocType
Bootstrap,correlation,power,sample size
Correlation coefficient,Pearson product-moment correlation coefficient,Mathematical optimization,Monte Carlo method,Monte Carlo algorithm,Markov chain Monte Carlo,Hybrid Monte Carlo,Fisher transformation,Statistics,Spearman's rank correlation coefficient,Mathematics
Journal
Volume
Issue
ISSN
6
2
0960-3174
Citations 
PageRank 
References 
0
0.34
0
Authors
1
Name
Order
Citations
PageRank
Reza Modarres1409.30