Approximate distributions of the sample coefficient alpha under nonnormality as well as normality are derived by using the single- and two-term Edgeworth expansions up to the term of order 1/n. The case of the standardized coefficient alpha including the weights for the components of a test is also considered. From the numerical illustration with simulation using the normal and typical nonnormal distributions with different types/degrees of nonnormality, it is shown that the variances of the sample coefficient alpha under nonnormality can be grossly different from those under normality. The corresponding biases and skewnesses are shown to be negative under various conditions. The method of developing confidence intervals of the population c...
Abstract: Several test statistics for covariance structure models derived from the normal theory lik...
Because the assumption of normality is common in statistics, the robustness of statistical procedure...
Abstract In this paper, the single sampling plan for variables under measurement error for non-norma...
In this paper, some of the familiar transformations of r are examined for their robustness to nonnor...
AbstractIn this paper, some of the familiar transformations of r are examined for their robustness t...
Coefficient alpha has been a widely used measure by which internal consistency reliability is assess...
AbstractThis paper examines asymptotic distributions of the likelihood ratio criteria, which are pro...
This paper examines asymptotic distributions of the likelihood ratio criteria, which are proposed un...
Geary (Biometrika 34, 1947) has introduced a differential series for the density function of Student...
Regression to the mean is the term used to describe the effect by which individuals selected on the ...
Stratified versions of coefficients for reliability are defined as extensions of the unstratified co...
AbstractCorrelation coefficients have many applications for studying the relationship among multivar...
AbstractAsymptotic expansions of the distributions of typical estimators in canonical correlation an...
Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/147087/1/rssc01350.pd
Statistical inference in the form of hypothesis tests and confidence intervals often assumes that th...
Abstract: Several test statistics for covariance structure models derived from the normal theory lik...
Because the assumption of normality is common in statistics, the robustness of statistical procedure...
Abstract In this paper, the single sampling plan for variables under measurement error for non-norma...
In this paper, some of the familiar transformations of r are examined for their robustness to nonnor...
AbstractIn this paper, some of the familiar transformations of r are examined for their robustness t...
Coefficient alpha has been a widely used measure by which internal consistency reliability is assess...
AbstractThis paper examines asymptotic distributions of the likelihood ratio criteria, which are pro...
This paper examines asymptotic distributions of the likelihood ratio criteria, which are proposed un...
Geary (Biometrika 34, 1947) has introduced a differential series for the density function of Student...
Regression to the mean is the term used to describe the effect by which individuals selected on the ...
Stratified versions of coefficients for reliability are defined as extensions of the unstratified co...
AbstractCorrelation coefficients have many applications for studying the relationship among multivar...
AbstractAsymptotic expansions of the distributions of typical estimators in canonical correlation an...
Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/147087/1/rssc01350.pd
Statistical inference in the form of hypothesis tests and confidence intervals often assumes that th...
Abstract: Several test statistics for covariance structure models derived from the normal theory lik...
Because the assumption of normality is common in statistics, the robustness of statistical procedure...
Abstract In this paper, the single sampling plan for variables under measurement error for non-norma...