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Some Improvements in Confidence Intervals for Standardized Regression Coefficients

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  • Paul Dudgeon

    () (The University of Melbourne)

Abstract

Abstract Yuan and Chan (Psychometrika 76:670–690, 2011. doi: 10.1007/S11336-011-9224-6 ) derived consistent confidence intervals for standardized regression coefficients under fixed and random score assumptions. Jones and Waller (Psychometrika 80:365–378, 2015. doi: 10.1007/S11336-013-9380-Y ) extended these developments to circumstances where data are non-normal by examining confidence intervals based on Browne’s (Br J Math Stat Psychol 37:62–83, 1984. doi: 10.1111/j.2044-8317.1984.tb00789.x ) asymptotic distribution-free (ADF) theory. Seven different heteroscedastic-consistent (HC) estimators were investigated in the current study as potentially better solutions for constructing confidence intervals on standardized regression coefficients under non-normality. Normal theory, ADF, and HC estimators were evaluated in a Monte Carlo simulation. Findings confirmed the superiority of the HC3 (MacKinnon and White, J Econ 35:305–325, 1985. doi: 10.1016/0304-4076(85)90158-7 ) and HC5 (Cribari-Neto and Da Silva, Adv Stat Anal 95:129–146, 2011. doi: 10.1007/s10182-010-0141-2 ) interval estimators over Jones and Waller’s ADF estimator under all conditions investigated, as well as over the normal theory method. The HC5 estimator was more robust in a restricted set of conditions over the HC3 estimator. Some possible extensions of HC estimators to other effect size measures are considered for future developments.

Suggested Citation

  • Paul Dudgeon, 2017. "Some Improvements in Confidence Intervals for Standardized Regression Coefficients," Psychometrika, Springer;The Psychometric Society, vol. 82(4), pages 928-951, December.
    • Handle: RePEc:spr:psycho:v:82:y:2017:i:4:d:10.1007_s11336-017-9563-z
    DOI: 10.1007/s11336-017-9563-z
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    References listed on IDEAS

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