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Full-Text Articles in Physical Sciences and Mathematics

Regression When There Are Two Covariates: Some Practical Reasons For Considering Quantile Grids, Rand Wilcox Feb 2020

Regression When There Are Two Covariates: Some Practical Reasons For Considering Quantile Grids, Rand Wilcox

Journal of Modern Applied Statistical Methods

When dealing with the association between some random variable and two covariates, extensive experience with smoothers indicates that often a linear model poorly reflects the nature of the association. A simple approach via quantile grids that reflects the nature of the association is given. The two main goals are to illustrate this approach can make a practical difference, and to describe R functions for applying it. Included are comments on dealing with more than two covariates.


Data Mining Ceo Compensation, Susan M. Adams, Atul Gupta, Dominique M. Haughton, John D. Leeth Nov 2008

Data Mining Ceo Compensation, Susan M. Adams, Atul Gupta, Dominique M. Haughton, John D. Leeth

Journal of Modern Applied Statistical Methods

The need to pre-specify expected interactions between variables is an issue in multiple regression. Theoretical and practical considerations make it impossible to pre-specify all possible interactions. The functional form of the dependent variable on the predictors is unknown in many cases. Two ways are described in which the data mining technique Multivariate Adaptive Regression Splines (MARS) can be utilized: first, to obtain possible improvements in model specification, and second, to test for the robustness of findings from a regression analysis. An empirical illustration is provided to show how MARS can be used for both purposes.


Estimation Of Process Variances In Robust Parameter Designs, T. K. Mak, Fassil Nebebe Nov 2005

Estimation Of Process Variances In Robust Parameter Designs, T. K. Mak, Fassil Nebebe

Journal of Modern Applied Statistical Methods

The modeling of variation through interactions is appealing in crossed array design as it leads to greater robustness to certain type of model misspecification. As an alternative to signal-to-noise analysis, a new, systematic method based on Taguchi type crossed array design is given. It is shown in this article that when fractional factorial design is used for the outer array, the crossed array design is not robust to the presence of noise-noise interactions and a method of rectifying the problem is suggested.


Inferences About Regression Interactions Via A Robust Smoother With An Application To Cannabis Problems, Rand R. Wilcox, Mitchell Earleywine May 2005

Inferences About Regression Interactions Via A Robust Smoother With An Application To Cannabis Problems, Rand R. Wilcox, Mitchell Earleywine

Journal of Modern Applied Statistical Methods

A flexible approach to testing the hypothesis of no regression interaction is to test the hypothesis that a generalized additive model provides a good fit to the data, where the components are some type of robust smoother. A practical concern, however, is that there are no published results on how well this approach controls the probability of a Type I error. Simulation results, reported here, indicate that an appropriate choice for the span of the smoother is required so that the actual probability of a Type I error is reasonably close to the nominal level. The technique is illustrated with …


Six Modifications Of The Aligned Rank Transform Test For Interaction, Kathleen Peterson May 2002

Six Modifications Of The Aligned Rank Transform Test For Interaction, Kathleen Peterson

Journal of Modern Applied Statistical Methods

Testing for interactions in multivariate experiments is an important function. Studies indicate that much data from social studies research is not normally distributed, thus violating that assumption of the AN OVA procedure. The aligned rank transformation test (ART), aligning using the means of columns and rows, has been found, in limited situations, to be robust to Type I error rates and to have greater power than the ANOVA. This study explored a variety of alignments, including the median, Winsorized trimmed means (10%) and (20%), the Huber1.28 M-estimator, and the Harrell-Davis estimator of the median. Results are reported for Type …


Genotype X Weather Interactions In Grain Yields Of Wheat, Arlin M. Feyerherm, Rollin G. Sears, Gary M. Paulsen Apr 1990

Genotype X Weather Interactions In Grain Yields Of Wheat, Arlin M. Feyerherm, Rollin G. Sears, Gary M. Paulsen

Conference on Applied Statistics in Agriculture

The purpose of this paper is to demonstrate the advantage of using weather elements as covariates in studying yield differentials between varieties of wheat over different climatological regions. Using regression methods, the dependence of varietal yield differences on weather elements was demonstrated with a relatively small sample consisting of yield and weather data over a 3-year period from nine locations in Kansas. For each location, the sample-derived regression equation was used to calculate predicted yield differentials and 95% confidence intervals for the mean (CLM) for each year from 1950 through 1989. The proportion of CLMs that covered positive (or negative) …