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Applied Statistics Commons™

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2003

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Articles 1 - 30 of 108

Full-Text Articles in Applied Statistics

Global Solutions To The Lake Equations With Isolated Vortex Regions, Chaocheng Huang Dec 2003

Global Solutions To The Lake Equations With Isolated Vortex Regions, Chaocheng Huang

Mathematics and Statistics Faculty Publications

The vorticity formulation for the lake equations in R2 is studied.

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Model Comparisons Using Information Measures, C. Mitchell Dayton Nov 2003

Model Comparisons Using Information Measures, C. Mitchell Dayton

Journal of Modern Applied Statistical Methods

Methodologists have criticized the use of significance tests in the behavioral sciences but have failed to provide alternative data analysis strategies that appeal to applied researchers. For purposes of comparing alternate models for data, information-theoretic measures such as Akaike AIC have advantages in comparison with significance tests. Model-selection procedures based on a min(AIC) strategy, for example, are holistic rather than dependent upon a series of sometimes contradictory binary (accept/reject) decisions.

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Fortune Cookies, Measurement Error, And Experimental Design, Greogry R. Hancock Nov 2003

Fortune Cookies, Measurement Error, And Experimental Design, Greogry R. Hancock

Journal of Modern Applied Statistical Methods

This article pertains to the theoretical and practical detriments of measurement error in traditional univariate and multivariate experimental design, and points toward modern methods that facilitate greater accuracy in effect size estimates and power in hypothesis testing.

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A Comparison Of Equivalence Testing In Combination With Hypothesis Testing And Effect Sizes, Christopher J. Mecklin Nov 2003

A Comparison Of Equivalence Testing In Combination With Hypothesis Testing And Effect Sizes, Christopher J. Mecklin

Journal of Modern Applied Statistical Methods

Equivalence testing, an alternative to testing for statistical significance, is little used in educational research. Equivalence testing is useful in situations where the researcher wishes to show that two means are not significantly different. A simulation study assessed the relationships between effect size, sample size, statistical significance, and statistical equivalence.

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Approximate Bayesian Confidence Intervals For The Variance Of A Gaussian Distribution, Vincent A. R. Camara Nov 2003

Approximate Bayesian Confidence Intervals For The Variance Of A Gaussian Distribution, Vincent A. R. Camara

Journal of Modern Applied Statistical Methods

The aim of the present study is to obtain and compare confidence intervals for the variance of a Gaussian distribution. Considering respectively the square error and the Higgins-Tsokos loss functions, approximate Bayesian confidence intervals for the variance of a normal population are derived. Using normal data and SAS software, the obtained approximate Bayesian confidence intervals will then be compared to the ones obtained with the well known classical method. The Bayesian approach relies only on the observations. It is shown that the proposed approximate Bayesian approach relies only on the observations. The classical method, that uses the Chi-square statistic, does …

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Using Zero-Inflated Count Regression Models To Estimate The Fertility Of U. S. Women, Dudley L. Poston Jr., Sherry L. Mckibben Nov 2003

Using Zero-Inflated Count Regression Models To Estimate The Fertility Of U. S. Women, Dudley L. Poston Jr., Sherry L. Mckibben

Journal of Modern Applied Statistical Methods

In the modeling of count variables there is sometimes a preponderance of zero counts. This article concerns the estimation of Poisson regression models (PRM) and negative binomial regression models (NBRM) to predict the average number of children ever born (CEB) to women in the U.S. The PRM and NBRM will often under-predict zeros because they do not consider zero counts of women who are not trying to have children. The fertility of U.S. white and Mexican-origin women show that zero-inflated Poisson (ZIP) and zero-inflated negative binomial (ZINB) models perform better in many respects than the Poisson and negative binomial models. …

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Test Of Homogeneity For Umbrella Alternatives In Dose-Response Relationship For Poisson Variables, Chengjie Xiong, Yan Yan, Ming Ji Nov 2003

Test Of Homogeneity For Umbrella Alternatives In Dose-Response Relationship For Poisson Variables, Chengjie Xiong, Yan Yan, Ming Ji

Journal of Modern Applied Statistical Methods

This article concerns the testing and estimation of a dose-response effect in medical studies. We study the statistical test of homogeneity against umbrella alternatives in a sequence of Poisson distributions associated with an ordered dose variable. We propose a test similar to Cochran-Armitage’s trend test and study the asymptotic null distribution and the power of the test. We also propose an estimator to the vertex point when the umbrella pattern is confirmed and study the performance of the estimator. A real data set pertaining to the number of visible revertant colonies associated with different doses of test agents in an …

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Alphabet Letter Recognition And Emergent Literacy Abilities Of Rising Kindergarten Children Living In Low-Income Families, Stephanie Wehry Nov 2003

Alphabet Letter Recognition And Emergent Literacy Abilities Of Rising Kindergarten Children Living In Low-Income Families, Stephanie Wehry

Journal of Modern Applied Statistical Methods

Alphabet letter recognition item responses from 1,299 rising kindergarten children from low-income families were used to determine the dimensionality of letter recognition ability. The rising kindergarteners were enrolled in preschool classrooms implementing a research-based early literary curriculum. Item responses from the TERA-3 subtests were also analyzed. Results indicated alphabet letter recognition was unitary. The ability of boys and younger children was less than girls and older children. Child-level letter recognition was highly associated with TERA-3 measures of letter knowledge and conventions of print. Classroom-level mean letter recognition ability accounted for most of variance in classroom mean TERA-3 scores.

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A Note On Mles For Normal Distribution Parameters Based On Disjoint Partial Sums Of A Random Sample, W. J. Hurley Nov 2003

A Note On Mles For Normal Distribution Parameters Based On Disjoint Partial Sums Of A Random Sample, W. J. Hurley

Journal of Modern Applied Statistical Methods

Maximum likelihood estimators are computed for the parameters of a normal distribution based on disjoint partial sums of a random sample. It has application in the disaggregation of financial data.

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Deconstructing Arguments From The Case Against Hypothesis Testing, Shlomo S. Sawilowsky Nov 2003

Deconstructing Arguments From The Case Against Hypothesis Testing, Shlomo S. Sawilowsky

Journal of Modern Applied Statistical Methods

The main purpose of this article is to contest the propositions that (1) hypothesis tests should be abandoned in favor of confidence intervals, and (2) science has not benefited from hypothesis testing. The minor purpose is to propose (1) descriptive statistics, graphics, and effect sizes do not obviate the need for hypothesis testing, (2) significance testing (reporting p values and leaving it to the reader to determine significance) is subjective and outside the realm of the scientific method, and (3) Bayesian and qualitative methods should be used for Bayesian and qualitative research studies, respectively.

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Conventional And Robust Paired And Independent-Samples T Tests: Type I Error And Power Rates, Katherine Fradette, H. J. Keselman, Lisa Lix, James Algina, Rand R. Wilcox Nov 2003

Conventional And Robust Paired And Independent-Samples T Tests: Type I Error And Power Rates, Katherine Fradette, H. J. Keselman, Lisa Lix, James Algina, Rand R. Wilcox

Journal of Modern Applied Statistical Methods

Monte Carlo methods were used to examine Type I error and power rates of 2 versions (conventional and robust) of the paired and independent-samples t tests under nonnormality. The conventional (robust) versions employed least squares means and variances (trimmed means and Winsorized variances) to test for differences between groups.

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Fitting Generalized Linear Mixed Models For Point-Referenced Spatial Data, Armin Gemperli, Penelope Vounatsou Nov 2003

Fitting Generalized Linear Mixed Models For Point-Referenced Spatial Data, Armin Gemperli, Penelope Vounatsou

Journal of Modern Applied Statistical Methods

Non-Gaussian point-referenced spatial data are frequently modeled using generalized linear mixed models (GLMM) with location-specific random effects. Spatial dependence can be introduced in the covariance matrix of the random effects. Maximum likelihood-based or Bayesian estimation implemented via Markov chain Monte Carlo (MCMC) for such models is computationally demanding especially for large sample sizes because of the large number of random effects and the inversion of the covariance matrix involved in the likelihood. We review three fitting procedures, the Penalized Quasi Likelihood method, the MCMC, and the Sampling-Importance-Resampling method. They are assessed in terms of estimation accuracy, ease of implementation, and …

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Jmasm9: Converting Kendall’S Tau For Correlational Or Meta-Analytic Analyses, David A. Walker Nov 2003

Jmasm9: Converting Kendall’S Tau For Correlational Or Meta-Analytic Analyses, David A. Walker

Journal of Modern Applied Statistical Methods

Expanding on past research, this study provides researchers with a detailed table for use in meta-analytic applications when engaged in assorted examinations of various r-related statistics, such as Kendall’s tau (τ) and Cohen’s d, that estimate the magnitude of experimental or observational effect. A program to convert from the lesser-used tau coefficient to other effect size indices when conducting correlational or meta-analytic analyses is presented.

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P* Index Of Segregation: Distribution Under Reassignment, Charles F. Bond, F. D. Richard Nov 2003

P* Index Of Segregation: Distribution Under Reassignment, Charles F. Bond, F. D. Richard

Journal of Modern Applied Statistical Methods

Students of intergroup relations have measured segregation with a P* index. In this article, we describe the distribution of this index under a stochastic model. We derive exact, closed-form expressions for the mean, variance, and skewness of P* under random segregation. These yield equivalent expressions for a second segregation index: η2. Our analytic results reveal some of the distributional properties of these indices, inform new standardizations of the indices, and enable small-sample significance testing. Two illustrative examples are presented.

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A Critical Examination Of The Use Of Preliminary Tests In Two-Sample Tests Of Location, Kimberly T. Perry Nov 2003

A Critical Examination Of The Use Of Preliminary Tests In Two-Sample Tests Of Location, Kimberly T. Perry

Journal of Modern Applied Statistical Methods

This paper explores the appropriateness of testing the equality of two means using either a t test, the Welch test, or the Wilcoxon-Mann-Whitney test for two independent samples based on the results of using two classes of preliminary tests (i.e., tests for population variance equality and symmetry in underlying distributions).

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Confidence Intervals For P(X Less Than Y) In The Exponential Case With Common Location Parameter, Ayman Baklizi Nov 2003

Confidence Intervals For P(X Less Than Y) In The Exponential Case With Common Location Parameter, Ayman Baklizi

Journal of Modern Applied Statistical Methods

The problem considered is interval estimation of the stress - strength reliability R = P(Xθ and λ respectively and a common location parameter μ . Several types of asymptotic, approximate and bootstrap intervals are investigated. Performances are investigated using simulation techniques and compared in terms of attainment of the nominal confidence level, symmetry of lower and upper error rates, and expected length. Recommendations concerning their usage are given.

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Random Regression Models Based On The Elliptically Contoured Distribution Assumptions With Applications To Longitudinal Data, Alfred A. Bartolucci, Shimin Zheng, Sejong Bae, Karan P. Singh Nov 2003

Random Regression Models Based On The Elliptically Contoured Distribution Assumptions With Applications To Longitudinal Data, Alfred A. Bartolucci, Shimin Zheng, Sejong Bae, Karan P. Singh

Journal of Modern Applied Statistical Methods

We generalize Lyles et al.’s (2000) random regression models for longitudinal data, accounting for both undetectable values and informative drop-outs in the distribution assumptions. Our models are constructed on the generalized multivariate theory which is based on the Elliptically Contoured Distribution (ECD). The estimation of the fixed parameters in the random regression models are invariant under the normal or the ECD assumptions. For the Human Immunodeficiency Virus Epidemiology Research Study data, ECD models fit the data better than classical normal models according to the Akaike (1974) Information Criterion. We also note that both univariate distributions of the random intercept and …

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Variable Selection For Poisson Regression Model, Felix Famoye, Daniel E. Rothe Nov 2003

Variable Selection For Poisson Regression Model, Felix Famoye, Daniel E. Rothe

Journal of Modern Applied Statistical Methods

Poisson regression is useful in modeling count data. In a study with many independent variables, it is desirable to reduce the number of variables while maintaining a model that is useful for prediction. This article presents a variable selection technique for Poisson regression models. The data used is log-linear, but the methods could be adapted to other relationships. The model parameters are estimated by the method of maximum likelihood. The use of measures of goodness-of-fit to select appropriate variables is discussed. A forward selection algorithm is presented and illustrated on a numerical data set. This algorithm performs as well if …

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Type I Error Rates Of Four Methods For Analyzing Data Collected In A Groups Vs Individuals Design, Stephanie Wehry, James Algina Nov 2003

Type I Error Rates Of Four Methods For Analyzing Data Collected In A Groups Vs Individuals Design, Stephanie Wehry, James Algina

Journal of Modern Applied Statistical Methods

Using previous work on the Behrens-Fisher problem, two approximate degrees of freedom tests, that can be used when one treatment is individually administered and one is administered to groups, were developed. Type I error rates are presented for these tests, an additional approximate degrees of freedom test developed by Myers, Dicecco, and Lorch (1981), and a mixed model test. The results indicate that the test that best controls the Type I error rate depends on the number of groups in the group-administered treatment. The mixed model test should be avoided.

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A Nonparametric Fitted Test For The Behrens-Fisher Problem, Terry Hyslop, Paul J. Lupinacci Nov 2003

A Nonparametric Fitted Test For The Behrens-Fisher Problem, Terry Hyslop, Paul J. Lupinacci

Journal of Modern Applied Statistical Methods

A nonparametric test for the Behrens-Fisher problem that is an extension of a test proposed by Fligner and Policello was developed. Empirical level and power estimates of this test are compared to those of alternative nonparametric and parametric tests through simulations. The results of our test were better than or comparable to all tests considered.

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Example Of The Impact Of Weights And Design Effects On Contingency Tables And Chi-Square Analysis, David A. Walker, Denise Y. Young Nov 2003

Example Of The Impact Of Weights And Design Effects On Contingency Tables And Chi-Square Analysis, David A. Walker, Denise Y. Young

Journal of Modern Applied Statistical Methods

Many national data sets used in educational research are not based on simple random sampling schemes, but instead are constructed using complex sampling designs characterized by multi-stage cluster sampling and over-sampling of some groups. Incorrect results are obtained from statistical analysis if adjustments are not made for the sampling design. This study demonstrates how the use of weights and design effects impact the results of contingency tables and chi-square analysis of data from complex sampling designs.

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Correcting Publication Bias In Meta-Analysis: A Truncation Approach, Guillermo Montes, Bohdan S. Lotyczewski Nov 2003

Correcting Publication Bias In Meta-Analysis: A Truncation Approach, Guillermo Montes, Bohdan S. Lotyczewski

Journal of Modern Applied Statistical Methods

Meta-analyses are increasingly used to support national policy decision making. The practical implications of publications bias in meta-analysis are discussed. Standard approaches to correct for publication bias require knowledge of the selection mechanism that leads to publication. In this study, an alternative approach is proposed based on Cohen’s corrections for a truncated normal. The approach makes less assumptions, is easy to implement, and performs well in simulations with small samples. The approach is illustrated with two published meta-analyses.

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Comparison Of Viral Trajectories In Aids Studies By Using Nonparametric Mixed-Effects Models, Chin-Shang Li, Hua Liang, Ying-Hen Hsieh, Shiing-Jer Twu Nov 2003

Comparison Of Viral Trajectories In Aids Studies By Using Nonparametric Mixed-Effects Models, Chin-Shang Li, Hua Liang, Ying-Hen Hsieh, Shiing-Jer Twu

Journal of Modern Applied Statistical Methods

The efficacy of antiretroviral therapies for human immunodeficiency virus (HIV) infection can be assessed by studying the trajectory of the changing viral load with treatment time, but estimation of viral trajectory parameters by using the implicit function form of linear and nonlinear parametric models can be problematic. Using longitudinal viral load data from a clinical study of HIV-infected patients in Taiwan, we described the viral trajectories by applying a nonparametric mixed-effects model. We were then able to compare the efficacies of highly active antiretroviral therapy (HAART) and conventional therapy by using Young and Bowman’s (1995) test.

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On Treating A Survey Of Convenience Sample As A Simple Random Sample, W. Gregory Thatcher, J. Wanzer Drane Nov 2003

On Treating A Survey Of Convenience Sample As A Simple Random Sample, W. Gregory Thatcher, J. Wanzer Drane

Journal of Modern Applied Statistical Methods

Threat of bias has kept many from using data gathered in less than optimal conditions. We maintain that when convenience sampling represents race and gender at nearly correct proportions and can be beneficial, as these two variables are quite often used as stratification variables. We compared a convenience sample with a proven sample. Race and Sex were nearly proportional as was found in the proven sample. We conclude that the convenience sample can be used as though it is simple random.

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Bootstrapping Confidence Intervals For Robust Measures Of Association, Jason E. King Nov 2003

Bootstrapping Confidence Intervals For Robust Measures Of Association, Jason E. King

Journal of Modern Applied Statistical Methods

A Monte Carlo simulation study compared four bootstrapping procedures in generating confidence intervals for the robust Winsorized and percentage bend correlations. Results revealed the superior resiliency of the robust correlations over r, with neither outperforming the other. Unexpectedly, the bootstrapping procedures achieved roughly equivalent outcomes for each correlation.

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Jmasm8: Using Sas To Perform Two-Way Analysis Of Variance Under Variance Heterogeneity, Scott J. Richter, Mark E. Payton Nov 2003

Jmasm8: Using Sas To Perform Two-Way Analysis Of Variance Under Variance Heterogeneity, Scott J. Richter, Mark E. Payton

Journal of Modern Applied Statistical Methods

We present SAS code to implement the method proposed by Brunner et al. (1997) for performing two-way analysis of variance under variance heterogeneity.

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Letters To The Editor, Jmasm Editors Nov 2003

Letters To The Editor, Jmasm Editors

Journal of Modern Applied Statistical Methods

No abstract provided.

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Statistical Pronouncements Ii, Jmasm Editors Nov 2003

Statistical Pronouncements Ii, Jmasm Editors

Journal of Modern Applied Statistical Methods

No abstract provided.

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Assessment Of Model Development Techniques And Evaluation Methods For Binary Classification In The Credit Industry, Satish Nargundkar, Jennifer Priestley Oct 2003

Assessment Of Model Development Techniques And Evaluation Methods For Binary Classification In The Credit Industry, Satish Nargundkar, Jennifer Priestley

Jennifer L. Priestley

We examine and compare the most prevalent modeling techniques in the credit industry, Linear Discriminant Analysis, Logistic Analysis and the emerging technique of Neural Network modeling. K-S Tests and Classification Rates are typically used in the industry to measure the success in predictive classification. We examine those two methods and a third, ROC Curves, to determine if the method of evaluation has an influence on the perceived performance of the modeling technique. We found that each modeling technique has its own strengths, and a determination of the “best” depends upon the evaluation method utilized and the costs associated with misclassification.

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Absorptive Capacity, Causal Ambiguity And Outcome Ambiguity: The Network Effect And Knowledge Transfer Difficulty Among Four Network Forms, Subhashish Samaddar, Jennifer Priestley Oct 2003

Absorptive Capacity, Causal Ambiguity And Outcome Ambiguity: The Network Effect And Knowledge Transfer Difficulty Among Four Network Forms, Subhashish Samaddar, Jennifer Priestley

Jennifer L. Priestley

No abstract is currently available.

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