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Full-Text Articles in Applied Statistics

Statistics And Technology: Reflections On 35 Years Of Change, James J. Higgins Nov 2004

Statistics And Technology: Reflections On 35 Years Of Change, James J. Higgins

Journal of Modern Applied Statistical Methods

From the days when statistical calculations were done on mechanical calculators to today, technology has transformed the discipline of statistics. More than just giving statisticians the power to crunch numbers, it has fundamentally changed the way we teach, do research, and consult. In this article, I give some examples of this from my 35 years as an academic statistician.

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“Teaching” In Honor Of Cliff Blair, Howard Stoker Nov 2004

“Teaching” In Honor Of Cliff Blair, Howard Stoker

Journal of Modern Applied Statistical Methods

In this article, I conceptualize teaching as the profession of facilitating and stimulating learning. As “teachers”, we help students acquire learning skills that they may expand on later in their life. I review fifteen principles that facilitate effective learning.

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A New Goodness-Of-Fit Test For Item Response Theory, John H. Neel Nov 2004

A New Goodness-Of-Fit Test For Item Response Theory, John H. Neel

Journal of Modern Applied Statistical Methods

Chi-square techniques for testing goodness-of-fit in item response theory are shown to give incorrect results. A new measure, CB, based on cumulants is proposed which avoids the arbitrary nature of interval creation found in chi-square techniques. The distribution of CB is estimated using Monte Carlo techniques and critical values for testing goodness-of-fit are given.

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Modeling Incomplete Longitudinal Data, Hakan Demirtas Nov 2004

Modeling Incomplete Longitudinal Data, Hakan Demirtas

Journal of Modern Applied Statistical Methods

This article presents a review of popular parametric, semiparametric and ad-hoc approaches for analyzing incomplete longitudinal data.

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Aligned Rank Tests As Robust Alternatives For Testing Interactions In Multiple Group Repeated Measures Designs With Heterogeneous Covariances, Xiaosheng Lei, Janet K. Holt, T. Mark Beasley Nov 2004

Aligned Rank Tests As Robust Alternatives For Testing Interactions In Multiple Group Repeated Measures Designs With Heterogeneous Covariances, Xiaosheng Lei, Janet K. Holt, T. Mark Beasley

Journal of Modern Applied Statistical Methods

Data simulation was used to investigate whether tests performed on aligned ranks (Beasley, 2002) could be used as robust alternatives to parametric methods for testing a split-plot interaction with non-normal data and heterogeneous covariance matrices. Results indicated the aligned rank method do not have any distinct advantage over parametric methods in this situation.

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Multivariate And Multistrata Nonparametric Tests: The Nonparametric Combination Method, Livio Corain, Luigi Salmaso Nov 2004

Multivariate And Multistrata Nonparametric Tests: The Nonparametric Combination Method, Livio Corain, Luigi Salmaso

Journal of Modern Applied Statistical Methods

Researchers and practitioners in many scientific disciplines and industrial fields are often faced with complex problems when dealing with comparisons between two or more groups using classical parametric methods. The data arising from real problems rarely are in agreement with stringent parametric assumptions. The NonParametric Combination (NPC) methodology frees the researcher from stringent assumptions of parametric methods and allows a more flexible analysis, both in terms of specification of multivariate hypotheses and in terms of the nature of the variables involved in the analysis. An outline of NPC methodology is given, along with case studies.

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On Comparison Of Hypothesis Tests In The Bayesian Framework Without Loss Function, Vladimir Gercsik, Mark Kelbert Nov 2004

On Comparison Of Hypothesis Tests In The Bayesian Framework Without Loss Function, Vladimir Gercsik, Mark Kelbert

Journal of Modern Applied Statistical Methods

The problem is how to compare the quality of different hypothesis tests in a Bayesian framework without introducing a loss function. Three different linear orders on the set of all possible hypothesis tests are studied. The most natural order estimates the Fisher information between indicators of event and decision.

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The President’S Problem, Jann-Huei Jinn Nov 2004

The President’S Problem, Jann-Huei Jinn

Journal of Modern Applied Statistical Methods

A solution is offered in response to a complex combination problem challenged by Blom, Englund, and Sandell (1998). The problem is to determine the probability that a random permutation of the word BILLCLINTON has no equal neighbors.

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A Conversation With R. Clifford Blair On The Occasion Of His Retirement, Shlomo S. Sawilowsky Nov 2004

A Conversation With R. Clifford Blair On The Occasion Of His Retirement, Shlomo S. Sawilowsky

Journal of Modern Applied Statistical Methods

An interview was conducted on 23 November 2003 with R. Clifford Blair on the occasion on his retirement from the University of South Florida. This article is based on that interview. Biographical sketches and images of members of his academic genealogy are provided.

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Multivariate Stochastic Volatility Models: Bayesian Estimation And Model Comparison, Jun Yu, Renate Meyer Nov 2004

Multivariate Stochastic Volatility Models: Bayesian Estimation And Model Comparison, Jun Yu, Renate Meyer

Research Collection School Of Economics

In this paper we show that fully likelihood-based estimation and comparison of multivariate stochastic volatility (SV) models can be easily performed via a freely available Bayesian software called WinBUGS. Moreover, we introduce to the literature several new specifications which are natural extensions to certain existing models, one of which allows for time varying correlation coefficients. Ideas are illustrated by fitting, to a bivariate time series data of weekly exchange rates, nine multivariate SV models, including the specifications with Granger causality in volatility, time varying correlations, heavy-tailed error distributions, additive factor structure, and multiplicative factor structure. Empirical results suggest that the …

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Beta-Normal Distribution: Bimodality Properties And Application, Felix Famoye, Carl Lee, Nicholas Eugene May 2004

Beta-Normal Distribution: Bimodality Properties And Application, Felix Famoye, Carl Lee, Nicholas Eugene

Journal of Modern Applied Statistical Methods

The beta-normal distribution is characterized by four parameters that jointly describe the location, the scale and the shape properties. The beta-normal distribution can be unimodal or bimodal. This paper studies the bimodality properties of the beta-normal distribution. The region of bimodality in the parameter space is obtained. The beta-normal distribution is applied to fit a numerical bimodal data set. The beta-normal fits are compared with the fits of mixture-normal distribution through simulation.

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Some Improvements In Kernel Estimation Using Line Transect Sampling, Omar M. Eidous May 2004

Some Improvements In Kernel Estimation Using Line Transect Sampling, Omar M. Eidous

Journal of Modern Applied Statistical Methods

Kernel estimation provides a nonparametric estimate of the probability density function from which a set of data is drawn. This article proposes a method to choose a reference density in bandwidth calculation for kernel estimator using line transect sampling. The method based on testing the shoulder condition, if the shoulder condition seems to be valid using as reference the half normal density, while if the shoulder condition does not seem to be valid, we will use exponential reference density. Accordingly, the performances of the resultant estimator are studied under a wide range of underlying models using simulation techniques. The results …

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A Visually Adaptive Bayesian Model In Wavelet Regression, Dongfeng Wu May 2004

A Visually Adaptive Bayesian Model In Wavelet Regression, Dongfeng Wu

Journal of Modern Applied Statistical Methods

The implementation of a Bayesian approach to wavelet regression that corresponds to the human visual system is examined. Most existing research in this area assumes non-informative priors, that is, a prior with mean zero. A new way is offered to implement prior information that mimics a visual inspection of noisy data, to obtain a first impression about the shape of the function that results in a prior with non-zero mean. This visually adaptive Bayesian (VAB) prior has a simple structure, intuitive interpretation, and is easy to implement. Skorohod topology is suggested as a more appropriate measure in signal recovering than …

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Estimation Using Bivariate Extreme Ranked Set Sampling With Application To The Bivariate Normal Distribution, Mohammad Fraiwan Al-Saleh, Hani M. Samawi May 2004

Estimation Using Bivariate Extreme Ranked Set Sampling With Application To The Bivariate Normal Distribution, Mohammad Fraiwan Al-Saleh, Hani M. Samawi

Journal of Modern Applied Statistical Methods

In this article, the procedure of bivariate extreme ranked set sampling (BVERSS) is introduced and investigated as a procedure of obtaining more accurate samples for estimating the parameters of bivariate populations. This procedure takes its strength from the advantages of bivariate ranked set sampling (BVRSS) over the usual ranked set sampling in dealing with two characteristics simultaneously, and the advantages of extreme ranked set sampling (ERSS) over usual RSS in reducing the ranking errors and hence in being more applicable. The BVERSS procedure will be applied to the case of the parameters of the bivariate normal distributions. Illustration using real …

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Kernel-Based Estimation Of P(X Less Than Y)With Paired Data, Omar M. Eidous, Ayman Baklizi May 2004

Kernel-Based Estimation Of P(X Less Than Y)With Paired Data, Omar M. Eidous, Ayman Baklizi

Journal of Modern Applied Statistical Methods

A point estimation of P(X < Y) was considered. A nonparametric estimator for P(X < Y) was developed using the kernel density estimator of the joint distribution of X and Y, may be dependent. The resulting estimator was found to be similar to the estimator based on the sign statistic, however it assigns smooth continuous scores to each pair of the observations rather than the zero or one scores of the sign statistic. The asymptotic equivalence of the sign statistic and the proposed estimator is shown and a simulation study is conducted to investigate the performance of the proposed estimator. Results indicate that …

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Respondent-Generated Intervals (Rgi) For Recall In Sample Surveys, S. James Press May 2004

Respondent-Generated Intervals (Rgi) For Recall In Sample Surveys, S. James Press

Journal of Modern Applied Statistical Methods

Respondents are asked for both a basic response to a recall-type question, their usage quantity, and are asked to provide lower and upper bounds for the (Respondent-Generated) interval in which their true values might possibly lie. A Bayesian hierarchical model for estimating the population mean and its variance is presented.. Telephone: (989) 774-

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Jmasm11: Comparing Two Small Binomial Proportions, James F. Reed Iii May 2004

Jmasm11: Comparing Two Small Binomial Proportions, James F. Reed Iii

Journal of Modern Applied Statistical Methods

A large volume of research has focused on comparing the difference between two small binomial proportions. Statisticians recognize that Fisher’s Exact test and Yates chi-square test are excessively conservative. Likewise, many statisticians feel that Pearson’s Chi-square or the likelihood statistic may be inappropriate for small samples. Viable alternatives exist.

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A Test-Retest Transition Matrix: A Modification Of Mcnemar’S Test, J. Wanzer Drane, W. Gregory Thatcher May 2004

A Test-Retest Transition Matrix: A Modification Of Mcnemar’S Test, J. Wanzer Drane, W. Gregory Thatcher

Journal of Modern Applied Statistical Methods

McNemar introduced what is known today as a test for symmetry in a two by two contingency tables. The logic of the test is based on a sample of matched pairs with a dichotomous response. In our example, the sample consists of the scores before and after an education program and the responses before and after the program. Each pair of scores is from only one person. The pretest divides the group of responders according to their answers to a dichotomous question. The posttest divides the two groups into two groups of like labels. The result is a two by …

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On The Reporting Of Reliability In Content Analysis, Patric R. Spence May 2004

On The Reporting Of Reliability In Content Analysis, Patric R. Spence

Journal of Modern Applied Statistical Methods

This article explores one type of misreporting of reliability that has been seen in recent conference papers and articles using the method of content analysis. The reporting of reliability is central to the validity of claims made using this method. A brief overview of content analysis is offered, followed by the exploration of one type of misreporting of reliability. Suggestions are offered to address the problem.

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Validation Studies: Matters Of Dimensionality, Accuracy, And Parsimony With Predictive Discriminant Analysis And Factor Analysis, David A. Walker May 2004

Validation Studies: Matters Of Dimensionality, Accuracy, And Parsimony With Predictive Discriminant Analysis And Factor Analysis, David A. Walker

Journal of Modern Applied Statistical Methods

Two studies were used as examples that examined issues of dimensionality, accuracy, and parsimony in educational research via the use of predictive discriminant analysis and factor analysis. Using a two-group problem, study 1 looked at how accurately group membership could be predicted from subjects’ test scores. Study 2 looked at the dimensionality structure of an instrument and if it developed constructs that would measure theorized domains.

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Stratified Extreme Ranked Set Sample With Application To Ratio Estimators, Hani M. Samawai, Laith J. Saeid May 2004

Stratified Extreme Ranked Set Sample With Application To Ratio Estimators, Hani M. Samawai, Laith J. Saeid

Journal of Modern Applied Statistical Methods

Stratified extreme ranked set sample (SERSS) is introduced. The performance of the combined and separate ratio estimates using SERSS is investigated. Theoretical and simulation study are presented. Results indicate that using SERSS for estimating the ratios is more efficient than using stratified simple random sample (SSRS) and simple random sample (SRS). In some cases it is more efficient than ranked set sample (RSS) and stratified ranked set sample (SRSS), when the underlying distribution is symmetric. An application to real data on the bilirubin level in jaundice babies is introduced to illustrate the method.

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Depth Based Permutation Test For General Differences In Two Multivariate Populations, Yonghong Gao May 2004

Depth Based Permutation Test For General Differences In Two Multivariate Populations, Yonghong Gao

Journal of Modern Applied Statistical Methods

For two p-dimensional data sets, interest exists in testing if they come from the common population distribution. Proposed is a practical, effective and easy to implement procedure for the testing problem. The proposed procedure is a permutation test based on the concept of the depth of one observation relative to some population distribution. The proposed test is demonstrated to be consistent. A small Monte Carlo simulation was conducted to evaluate the power of the proposed test. The proposed test is applied to some numerical examples.

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Accurate Binary Decisions For Assessing Coronary Artery Disease, Mehmet Ali Cengiz May 2004

Accurate Binary Decisions For Assessing Coronary Artery Disease, Mehmet Ali Cengiz

Journal of Modern Applied Statistical Methods

Generalized linear models offer convenient and highly applicable tools for modeling and predicting the behavior of random variables in terms of observable factors and covariates. This paper investigates applications of a special case of generalized linear model to improve the accuracy of predictions and decisions adopting Bayesian methods, in the specific context of assessing coronary artery disease. The basic model is developed for this application using binary response. The results clearly demonstrate the potential advantages offered by this approach.

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Statistical Pronouncements Iii, Jmasm Editors May 2004

Statistical Pronouncements Iii, Jmasm Editors

Journal of Modern Applied Statistical Methods

No abstract provided.

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Meta-Analysis Of Results And Individual Patient Data In Epidemiologal Studies, Aurelio Tobías, Marc Saez, Manolis Kogevinas May 2004

Meta-Analysis Of Results And Individual Patient Data In Epidemiologal Studies, Aurelio Tobías, Marc Saez, Manolis Kogevinas

Journal of Modern Applied Statistical Methods

Epidemiological information can be aggregated by combining results through a meta-analysis technique, or by pooling and analyzing primary data. Common approaches to analyzing pooled studies through an example on the effect of occupational exposure to wood dust on sinonasal cancer are described. Results were combined applying a meta-analysis technique. Alternatively, primary data from all studies were pooled and re-analyzed using mixed effect models. The combination of individual information rather than results is desirable to facilitate interpretations of epidemiological findings, leading also to more precise estimations and more powerful statistical tests for study heterogeneity.

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Multivariate Location: Robust Estimators And Inference, Rand R. Wilcox, H. J. Keselman May 2004

Multivariate Location: Robust Estimators And Inference, Rand R. Wilcox, H. J. Keselman

Journal of Modern Applied Statistical Methods

The sample mean can have poor efficiency relative to various alternative estimators under arbitrarily small departures from normality. In the multivariate case, (affine equivariant) estimators have been proposed for dealing with this problem, but a comparison of various estimators by Massé and Plante (2003) indicated that the small-sample efficiency of some recently derived methods is rather poor. This article reports that a skipped mean, where outliers are removed via a projection-type outlier detection method, is found to be more satisfactory. The more obvious method for computing a confidence region based on the skipped estimator (using a slight modification of the …

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A Power Comparison Of Robust Test Statistics Based On Adaptive Estimators, H. J. Keselman, Rand R. Wilcox, James Algina, Abdul R. Othman May 2004

A Power Comparison Of Robust Test Statistics Based On Adaptive Estimators, H. J. Keselman, Rand R. Wilcox, James Algina, Abdul R. Othman

Journal of Modern Applied Statistical Methods

Seven test statistics known to be robust to the combined effects of nonnormality and variance heterogeneity were compared for their sensitivity to detect treatment effects in a one-way completely randomized design containing four groups. The six Welch-James-type heteroscedastic tests adopted either symmetric or asymmetric trimmed means, were transformed for skewness, and used a bootstrap method to assess statistical significance. The remaining test, due to Wilcox and Keselman (2003), used a modification of the well-known one-step M-estimator of central tendency rather than trimmed means. The Welch-James-type test is recommended because for nonnormal data likely to be encountered in applied research settings …

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A Rank-Based Estimation Procedure For Linear Models With Clustered Data, Suzanne R. Dubnicka May 2004

A Rank-Based Estimation Procedure For Linear Models With Clustered Data, Suzanne R. Dubnicka

Journal of Modern Applied Statistical Methods

A rank method is presented for estimating regression parameters in the linear model when observations are correlated. This correlation is accounted for by including a random effect term in the linear model. A method is proposed that makes few assumptions about the random effect and error distribution. The main goal of this article is to determine the distributions for which this method performs well relative to existing methods.

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A Generalized Quasi-Likelihood Model Application To Modeling Poverty Of Asian American Women, Jeffrey R. Wilson May 2004

A Generalized Quasi-Likelihood Model Application To Modeling Poverty Of Asian American Women, Jeffrey R. Wilson

Journal of Modern Applied Statistical Methods

A generalized quasi-likelihood function that does not require the assumption of an underlying distribution when modeling jointly the mean and the variance, is introduced to examine poverty of Asian American women living in the West coast of the United States, using data from U.S. Census Bureau.

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Estimation Of Multiple Linear Functional Relationships, Amjad D. Al-Nasser May 2004

Estimation Of Multiple Linear Functional Relationships, Amjad D. Al-Nasser

Journal of Modern Applied Statistical Methods

This article deals with multiple linear functional relationships models. Two robust estimations procedure are proposed to estimate the model, based on Generalized Maximum Entropy and Partial Least Square. They are distribution free and do not rely (so much) on classical assumptions. The experiments showed that the GME approach outperforms the PLS in terms of mean squares of errors (MSE). Empirical examples are studied.

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