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ArtikelConfidence Intervals for an Effect Size Measure in Multiple Linear Regression  
Oleh: Algina, James ; Keselman, H. J.
Jenis: Article from Journal - ilmiah internasional
Dalam koleksi: Educational and Psychological Measurement vol. 67 no. 02 (Apr. 2007), page 207-218.
Topik: squared semipartial correlation; multiple correlation; effect size; bootstrap; confidence interval
Fulltext: 207.pdf (135.46KB)
Isi artikelThe increase in the squared multiple correlation coefficient (R2) associated with a variable in a regression equation is a commonly used measure of importance in regression analysis. The coverage probability that an asymptotic and percentile bootstrap confidence interval includes ?2 was investigated. As expected, coverage probability for the asymptotic confidence interval was often inadequate (outside the interval .925 to .975 for a 95% confidence interval), even when sample size was quite large (i.e., 200). However, adequate coverage probability for the confidence interval based on a bootstrap interval could typically be obtained with a sample size of 200 or less, and moreover, this accuracy was obtained with relatively small sample sizes (100 or less) with six or fewer predictors.
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