RT Journal Article
T1 Bias, Precision, and Accuracy of Skewness and Kurtosis Estimators for Frequently Used Continuous Distributions.
A1 Bono Cabré, Roser
A1 Arnau Gras, Jaume
A1 Alarcón-Postigo, Rafael
A1 Blanca-Mena, María José
K1 Prejuicios
K1 Actitud (Psicología)
K1 Psicometría
AB Several measures of skewness and kurtosis were proposed by Hogg (1974) in order toreduce the bias of conventional estimators when the distribution is non-normal. Here we conducteda Monte Carlo simulation study to compare the performance of conventional and Hogg’s estimators,considering the most frequent continuous distributions used in health, education, and social sciences(gamma, lognormal and exponential distributions). In order to determine the bias, precision andaccuracy of the skewness and kurtosis estimators for each distribution we calculated the relative bias,the coe cient of variation, and the scaled root mean square error. The e ect of sample size on theestimators is also analyzed. In addition, a SAS program for calculating both conventional and Hogg’sestimators is presented. The results indicated that for the non-normal distributions investigated,the estimators of skewness and kurtosis which best reflect the shape of the distribution are Hogg’sestimators. It should also be noted that Hogg’s estimators are not as a ected by sample size as areconventional estimators.
PB MDPI
YR 2019
FD 2019-12-20
LK https://hdl.handle.net/10630/28442
UL https://hdl.handle.net/10630/28442
LA eng
NO Bono, R., Arnau, J., Alarcón, R., & Blanca, M. J. (2020). Bias, Precision, and Accuracy of Skewness and Kurtosis Estimators for Frequently Used Continuous Distributions. Symmetry 12, 19. https://doi.org/10.3390/SYM12010019
NO This research was supported by grant PSI2016-78737-P (AEI/FEDER, UE) from the National ResearchAgency of the Spanish Ministry of Economy, Industry and Competitiveness and the European RegionalDevelopment Fund.Partial funding for open access charge: Universidad de Málaga
DS RIUMA. Repositorio Institucional de la Universidad de Málaga
RD 16 abr 2026