Sample Sizes for Confidence Intervals on the Increase in the Squared Multiple Correlation Coefficient
James Algina, Bradley C. Moulder
Abstract
James Algina, Bradley C. Moulder
Abstract
The increase in the squared multiple correlation coefficient (δ R 2 ) associated with a variable in a regression equation is a commonly used measure of importance in regression analysis. The probability that an asymptotic confidence interval will include δρ 2 was investigated. With sample sizes typically used in regression analyses, when δρ 2 = 0.00 and the confidence level is .95 or greater, the probability will be at least .999. For δρ 2 ≥ .01 and a confidence level of .95 or greater, the probability will be smaller than the nominal confidence level. For δρ 2 ≥ .05 and a confidence level of .95, tables are provided for the sample size necessary for the probability to be at least .925 and to be at least .94.
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The increase in the squared multiple correlation coefficient (δ R 2 ) associated with a variable in a regression equation is a commonly used measure of importance in regression analysis. The probability that an asymptotic confidence interval will include δρ 2 was investigated. With sample sizes typically used in regression analyses, when δρ 2 = 0.00 and the confidence level is .95 or greater, the probability will be at least .999. For δρ 2 ≥ .01 and a confidence level of .95 or greater, the probability will be smaller than the nominal confidence level. For δρ 2 ≥ .05 and a confidence level of .95, tables are provided for the sample size necessary for the probability to be at least .925 and to be at least .94.
Key concepts: Statistics, Confidence interval, CDF-based nonparametric confidence interval, Mathematics, Coverage probability, Regression analysis, Robust confidence intervals, Confidence distribution