Journal ArticleDOI
The effect of kurtosis in the estimation of the parameters of the one-way random effects model from familial data
TLDR
In this paper, the estimation of the components of variance of the one-way random effects model is considered when the assumption of normality is removed, and the asymptotic relative efficiency of the estimators, derived by minimizing the mean squared error, is evaluated.About:
This article is published in Computational Statistics & Data Analysis.The article was published on 1990-11-01. It has received 6 citations till now. The article focuses on the topics: Estimator & Kurtosis.read more
Citations
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A bibliography on variance components an introduction and an update: 1984-2002
Hardeo Sahai,Anwer Khurshid +1 more
TL;DR: In particular, the study of variance through a class of linear models known as random and mixed models is a central topic in statistics with wide ramifications in both theory and applications as discussed by the authors.
Journal ArticleDOI
Confidence intervals for variance components in unbalanced one-way random effects model using non-normal distributions
TL;DR: In this article, the performance of confidence intervals under non-normal distribution assumptions is evaluated using simulation results and an empirical example suggest that the restricted maximum likelihood (REML) based confidence interval is favored over the other two procedures in unbalanced one-way random effects model.
Journal ArticleDOI
Bias and Mean Square Error of Reliability Estimators under the One and Two Random Effects Models: The Effect of Non-Normality
TL;DR: In this paper, the authors derived analytic expressions for the bias and variance of the reliability coefficient in the one-way and two-way random effects models using the multivariate Taylor's expansion under the assumption of normality of the score.
Journal ArticleDOI
On the Index of Repeatability: Estimation and Sample Size Requirements
Maha Al-Eid,Mohamed Shoukri +1 more
TL;DR: In this paper, an index of repeatability based on the ratio of two variance components is derived from the one-way Analysis of Variance table based on a one way random effects model and the large sample variance of the estimator and assess its adequacy using bootstrap methods.
Journal ArticleDOI
Confidence intervals for variance components using non-normal distributions
TL;DR: In this paper, the performance of confidence intervals for variance components under non-normal distribution assumptions was evaluated using simulation results and an empirical example involving arsenic concentrations in oyster tissue, which indicated that the restricted maximum likelihood-based confidence interval is preferred.
References
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Book
Statistical Methods for Research Workers
TL;DR: The prime object of as discussed by the authors is to put into the hands of research workers, and especially of biologists, the means of applying statistical tests accurately to numerical data accumulated in their own laboratories or available in the literature.
Journal ArticleDOI
The estimation of intraclass correlation in the analysis of family data.
Allan Donner,John J. Koval +1 more
TL;DR: The maximum likelihood estimator of the intraclass correlation coefficient rho in samples of unequal size from a multivariate normal distribution has been derived and compared to several other estimators, using Monte Carlo simulation.
Journal ArticleDOI
A Review of Inference Procedures for the Intraclass Correlation Coefficient in the One-Way Random Effects Model
TL;DR: In this paper, a review of recent theory and methodology for inferences concerning the intraclass correlation coefficient are reviewed, under the assumption of an underlying random effects model, including point and interval estimation, significance-testing for nonzero values of the intra-class correlation, and inference procedures in multiple samples.
Journal ArticleDOI
Monte Carlo Comparison of ANOVA, MIVQUE, REML, and ML Estimators of Variance Components
TL;DR: In this article, the among-and within-treatments variance components: analysis of variance (ANOVA), maximum likelihood, restricted maximum likelihood (REML), and two minimum variance quadratic unbiased (MIVQUE) estimators are compared.