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Dissertation Information for Richard Shafferey Herrington

NAME:
- Richard Shafferey Herrington

DEGREE:
- Ph.D.

DISCIPLINE:
- Psychology

SCHOOL:
- University of North Texas (USA) (2001)

ADVISORS:
- None

COMMITTEE MEMBERS:
- None

MPACT Status: Incomplete - Not_Inspected

Title: Simulating statistical power curves with the bootstrap and robust estimation

Abstract: Power and effect size analysis are important methods in the psychological sciences. It is well known that classical statistical tests are not robust with respect to power and type II error. However, relatively little attention has been paid in the psychological literature to the effect that non-normality and outliers have on the power of a given statistical test (Wilcox, 1998). Robust measures of location exist that provide much more powerful tests of statistical hypotheses, but their usefulness in power estimation for sample size selection, with real data, is largely unknown. Furthermore, practical approaches to power planning (Cohen, 1988) usually focus on normal theory settings and in general do not make available nonparametric approaches to power and effect size estimation. Beran (1986) proved that it is possible to nonparametrically estimate power for a given statistical test using bootstrap methods (Efron, 1993). However, this method is not widely known or utilized in data analysis settings. This research study examined the practical importance of combining robust measures of location with nonparametric power analysis. Simulation and analysis of real world data sets are used. The present study found that: (1) bootstrap confidence intervals using M-estimators gave shorter confidence intervals than the normal theory counterpart whenever the data had heavy tailed distributions; (2) bootstrap empirical power is higher for M-estimators than the normal theory counterpart when the data had heavy tailed distributions; (3) the smoothed bootstrap controls type I error rate (less than 6%) under the null hypothesis for small sample sizes; and (4) robust effect sizes can be used in conjunction with Cohen's (1988) power tables to get more realistic sample sizes given that the data distribution has heavy tails.

MPACT Scores for Richard Shafferey Herrington

A = 0
C = 1
A+C = 1
T = 0
G = 0
W = 0
TD = 0
TA = 0
calculated 2008-01-31 06:31:36

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Students under Richard Shafferey Herrington

ADVISEES:
- None

COMMITTEESHIPS:
- Onaje Omotola Johnston - University of North Texas (2006)