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Some Improvements in Confidence Intervals for Standardized Regression Coefficients
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.
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Metadata
- Authors
- Dudgeon, P.
- ORCID
- Dudgeon, Paul
- Venue
- Psychometrika
- Publisher
- Cambridge University Press (CUP)
- Published
- 2017-12
- Volume
- 82
- Issue
- 4
- Pages
- 928-951
- ISSN
- 0033-3123
- 1860-0980
- Cited by
- 15
- References
- 2
- Language
- en
- Licence
- www.cambridge.org/core/terms (unspecified, 2588 d)
- www.springer.com/tdm (tdm)
- www.springer.com/tdm (vor)
- Funders
- Australian Research Council (DP120101402, LP130100314)
- National Health and Medical Research Council (1027076, APP1082668)
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