Showing papers on "Fisher transformation published in 1983"
TL;DR: In this article, a coefficient to measure association between angular variables is discussed, its asymptotic distribution is found, and its properties are compared with other statistics in current use.
Abstract: SUMMARY A coefficient to measure association between angular variables is discussed, its asymptotic distribution found, and its properties developed. Comparisons with other statistics in current use are made, and some examples given.
195 citations
TL;DR: For the unbalanced analysis of covariance model with one covariate, a simple formula is given for the intraclass correlation coefficient estimator that results from Henderson's Method 3 estimation of variance components as discussed by the authors.
Abstract: For the unbalanced analysis of covariance model with one covariate, a simple formula is given for the intraclass correlation coefficient estimator that results from Henderson's Method 3 estimation of variance components. Example calculations and the corresponding interpretations are given for a study of the correlation of iron content among brothers. The example illustrates the manner in which the estimator depends on the pattern of correlation between the covariate and the variable under investigation.
66 citations
TL;DR: In this article, the conclusions of Warren (1982) are shown to result from the confusion of two definitions for the sample coefficient of variation, and some clarification of statistics based on McKay's x2 approximation for the distribution of the sample coefficients of variation is presented.
Abstract: Some clarification of statistics based on McKay's x2 approximation for the distribution of the sample coefficient of variation is presented. The conclusions of Warren (1982) are shown to result from the confusion of two definitions for the sample coefficient of variation.
20 citations
TL;DR: In this article, the adequacy of Fisher's approximation to the large sample variance of an intraclass correlation is investigated in the context of family studies, and it is found that the approximation is highly accurate in samples of moderately large size (≧ 30 families), and can also be used for significance testing under a broad range of circumstances.
Abstract: The adequacy of Fisher's approximation to the large sample variance of an intraclass correlation is investigated in the context of family studies. It is found that the approximation is highly accurate in samples of moderately large size (≧ 30 families), and can also be used for significance-testing under a broad range of circumstances. The exact sampling of distribution of the intraclass correlation coefficient is also derived.
14 citations
TL;DR: In this article, a Gaussian approximation to the non-null (ρ≠0) distribution of R is developed using the transformation (T/E(T))h where T =−log(l−R2), and h is determined from the first three cumulants of T.
Abstract: Let X1,X2, …, Xp be jointly distributed according to a multivariate normal distribution, and let ? denote the multiple correlation coefficient between X1 and X2, X3,…, Xp Let Xli,…, Xpi, i =1, … N, be a random sample from the distribution. The logarithm of the likelihood ratio statistic for testing the hypothesis that ρ is zero is −(N/2)log(l−R2), where R is the sample multiple correlation coefficient. A Gaussian approximation to the non-null (ρ≠0) distribution of R is developed using the transformation (T/E(T))hwhere T =−log(l−R2), and h is determined from the first three cumulants of T. The approximation is simple and accurate over a wide range of the parameters p, N, and ρ.
10 citations
8 citations
01 Sep 1983
TL;DR: In this paper, a multiple correlation coefficient is proposed to measure the degree of association between a random variable Y and a set of random variables X sub l,..., X sub p. The coefficient is defined in terms of weighted Kendall's tau, suitably normalized.
Abstract: : A multiple correlation coefficient is discussed to measure the degree of association between a random variable Y and a set of random variables X sub l, ..., X sub p. The coefficient is defined in terms of weighted Kendall's tau, suitably normalized. It is directly compatible with the rank statistic approach of analyzing linear models in a regression, prediction context. The population parameter equals the classical multiple correlation coefficient if the multivariate normal model holds but would be more robust for departures from this model. Some results are given on the consistency of the sample estimate and on a test for independence. (Author)
3 citations
TL;DR: In this article, the estimation of a real-valued function of the parameter by minimizing the expected value of the quadratic loss function relative to the structural distribution of the parameters is proposed; this is called structural estimation.
Abstract: In this paper, the estimation of a real-valued function of the parameter by minimizing the expected value of the quadratic loss function relative to the structural distribution of the parameter is proposed; this is called structural estimation. The general formulae developed have been used to obtain the structural estimate of the bivariate correlation coefficient and of the intraclass correlation coefficient.
3 citations
TL;DR: In this paper, five transformations of the correlation coefficient, namely, Fisher's z, Nair's u, Sankaran's v, Ruben's y and Samiuddin's t are compared numerically using confidence intervals.
Abstract: Five transformations of the correlation coefficient, namely, Fisher's z, Nair's u, Sankaran's v, Ruben's y and Samiuddin's t are compared numerically using confidence intervals. Samiuddin's ts transformation is close to the exact nominal confidence level for a small sample size ≤ 25 from a bivariate normal density. For a sample size > 25 both Samiuddin's ts and Fisher's z can be used. In the presence of an outlier (on a minor axis), both Fisher's z and Samiuddin's ts are not affected as long as |p| ≤ 0.3 but are seriously affected when |p&| > 0.3.
3 citations
TL;DR: In this paper, a connection between the partial correlation coefficient and the correlation coefficient of certain residuals is made, based on the correlation of partial correlation coefficients of residuals with the residuals.
Abstract: (1983). A connection between the partial correlation coefficient and the correlation coefficient of certain residuals. Communications in Statistics - Simulation and Computation: Vol. 12, No. 5, pp. 639-641.
1 citations
01 Jan 1983
TL;DR: A program for computing one-tail probabilities associated with a z statistic for determining the statistical significance of various types of correlation coefficients or difference between two coefficients is described.
Abstract: A program for computing one-tail probabilities associated with a z statistic for determining the statistical significance of various types of correlation coefficients or difference between two coefficients is described. The program, which was designed especially for use on small computers, is modular, in that 1-8 subprograms accompanying the main program may be combined individually or collectively with it. The obtained probabilities are accurate to the second decimal place.