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Social and Behavioral Sciences Commons™
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- Monte Carlo simulation (3)
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Articles 61 - 67 of 67
Full-Text Articles in Social and Behavioral Sciences
Jmasm 26: Hettmansperger And Mckean Linear Model Aligned Rank Test For The Single Covariate And One-Way Ancova Case (Sas), Paul A. Nakonezny, Robert D. Shull
Jmasm 26: Hettmansperger And Mckean Linear Model Aligned Rank Test For The Single Covariate And One-Way Ancova Case (Sas), Paul A. Nakonezny, Robert D. Shull
Journal of Modern Applied Statistical Methods
A SAS program (SAS 9.1.3 release, SAS Institute, Cary, N.C.) is presented to implement the Hettmansperger and McKean (1983) linear model aligned rank test (nonparametric ANCOVA) for the single covariate and one-way ANCOVA case. As part of this program, SAS code is also provided to derive the residuals from the regression of Y on X (which is step 1 in the Hettmansperger and McKean procedure) using either ordinary least squares regression (proc reg in SAS) or robust regression with MM estimation (proc robustreg in SAS).
On Flexible Tests Of Independence And Homoscedasticity, Rand R. Wilcox
On Flexible Tests Of Independence And Homoscedasticity, Rand R. Wilcox
Journal of Modern Applied Statistical Methods
Consider the nonparametric regression model Y = m(X) + τ(X)ε , where X and ε are independent random variables, ε has a mean of zero and variance σ2, τ is some unknown function used to model heteroscedasticity, and m(X) is an unknown function reflecting some conditional measure of location associated with Y, given X. Detecting dependence, by testing the hypothesis that m(X) does not vary with X, has the potential of being more sensitive to a wider range of associations compared to using Pearson's correlation. This note has two goals. The first is to point …
Reliability And Statistical Power: How Measurement Fallibility Affects Power And Required Sample Sizes For Several Parametric And Nonparametric Statistics, Gibbs Y. Kanyongo, Gordon P. Brook, Lydia Kyei-Blankson, Gulsah Gocmen
Reliability And Statistical Power: How Measurement Fallibility Affects Power And Required Sample Sizes For Several Parametric And Nonparametric Statistics, Gibbs Y. Kanyongo, Gordon P. Brook, Lydia Kyei-Blankson, Gulsah Gocmen
Journal of Modern Applied Statistical Methods
The relationship between reliability and statistical power is considered, and tables that account for reduced reliability are presented. A series of Monte Carlo experiments were conducted to determine the effect of changes in reliability on parametric and nonparametric statistical methods, including the paired samples dependent t test, pooled-variance independent t test, one-way analysis of variance with three levels, Wilcoxon signed-rank test for paired samples, and Mann-Whitney-Wilcoxon test for independent groups. Power tables were created that illustrate the reduction in statistical power from decreased reliability for given sample sizes. Sample size tables were created to provide the approximate sample sizes required …
Using The Fractional Imputation Methodology To Evaluate Variance Due To Hot Deck Imputation In Survey Data, Adriana Pérez
Using The Fractional Imputation Methodology To Evaluate Variance Due To Hot Deck Imputation In Survey Data, Adriana Pérez
Journal of Modern Applied Statistical Methods
This article examines empirically the effect on the variance estimate due to the use of hot deck imputation with a nearest neighbor donor in comparison with the pairwise fractional hot deck imputation methodology in the 1999 Survey of Doctorate Recipients.
A Fano-Huffman Based Statistical Coding Method, Aladdin Shamilov, Senay Asma
A Fano-Huffman Based Statistical Coding Method, Aladdin Shamilov, Senay Asma
Journal of Modern Applied Statistical Methods
Statistical coding techniques have been used for lossless statistical data compression, applying methods such as Ordinary, Shannon, Fano, Enhanced Fano, Huffman and Shannon-Fano-Elias coding methods. A new and improved coding method is presented, the Fano-Huffman Based Statistical Coding Method. It holds the advantages of both the Fano and Huffman coding methods. It is more easily applicable than the Huffman coding methods and it is more optimal than Fano coding method. The optimality with respect to the other methods is realized on the basis of English, German, Turkish, French, Russian and Spanish.
A Comparison Of Two Rank Tests For Repeated Measure Designs, Tian Tian, Rand R. Wilcox
A Comparison Of Two Rank Tests For Repeated Measure Designs, Tian Tian, Rand R. Wilcox
Journal of Modern Applied Statistical Methods
This article compares the small-sample properties of the Agresti-Pendergast and the ATS rank-based method, as described in Brunner, Domh, and Langer (2002), for comparing J dependent groups. The results indicate that the Type I error of the Agresti-Pendergast method is more conservative when J = 2 , but under most conditions, the ATS method performs best in terms of both Type I errors and power.
Hierarchical Linear Modeling In Organizational Research: Longitudinal Data Outside The Context Of Growth Modeling, Irvin Sam Schonfeld, David Rindskopf
Hierarchical Linear Modeling In Organizational Research: Longitudinal Data Outside The Context Of Growth Modeling, Irvin Sam Schonfeld, David Rindskopf
Publications and Research
Organizational researchers, including those carrying out occupational stress research, often conduct longitudinal studies. Hierarchical linear modeling (HLM; also known as multilevel modeling and random regression) can efficiently organize analyses of longitudinal data by including within- and between-person levels of analysis. A great deal of longitudinal research has been conducted in the context of growth studies in which change in the dependent variable is examined in relation to the passage of time. HLM can treat longitudinal data, including data outside the context of the growth study, as nested data, reducing the problem of censoring. Within-person equation coefficients can represent the impact …