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Sample size requirements for multiple regression interval estimation
Author(s) -
Bonett Douglas G.,
Wright Thomas A.
Publication year - 2011
Publication title -
journal of organizational behavior
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.938
H-Index - 177
eISSN - 1099-1379
pISSN - 0894-3796
DOI - 10.1002/job.717
Subject(s) - sample size determination , statistics , rule of thumb , confidence interval , sample (material) , mathematics , regression , simple (philosophy) , regression analysis , interval estimation , simple linear regression , linear regression , interval (graph theory) , algorithm , philosophy , chemistry , epistemology , chromatography , combinatorics
Sample size planning is one of the most important issues in the design of a study. Simple and accurate sample size formulas for a desired confidence interval width have been developed for many statistical procedures, but a simple and accurate sample size formula for the squared multiple correlation has been a notable exception. Several rule‐of‐thumb sample size recommendations for a multiple regression analysis have been proposed over the years but none are satisfactory. Other approaches have focused on the construction of elaborate tables of sample size requirements, but these tables are both unwieldy and inadequate. We present a simple, accurate, and general method of approximating the sample size requirement for obtaining a squared multiple correlation confidence interval with desired precision. We also present a simple method for approximating the sample size needed to estimate unstandardized regression coefficients with desired precision. Copyright © 2010 John Wiley & Sons, Ltd.