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2005

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Articles 181 - 210 of 279

Full-Text Articles in Statistics and Probability

Testing The Goodness Of Fit Of Multivariate Multiplicative-Intercept Risk Models Based On Case-Control Data, Biao Zhang May 2005

Testing The Goodness Of Fit Of Multivariate Multiplicative-Intercept Risk Models Based On Case-Control Data, Biao Zhang

Journal of Modern Applied Statistical Methods

The validity of the multivariate multiplicative-intercept risk model with I +1 categories based on casecontrol data is tested. After reparametrization, the assumed risk model is equivalent to an (I +1) -sample semiparametric model in which the I ratios of two unspecified density functions have known parametric forms. By identifying this (I +1) -sample semiparametric model, which is of intrinsic interest in general (I +1) -sample problems, with an (I +1) -sample semiparametric selection bias model, we propose a weighted Kolmogorov-Smirnov-type statistic to test the validity of the multivariate multiplicativeintercept risk model. Established are some asymptotic results …


Within By Within Anova Based On Medians, Rand R. Wilcox May 2005

Within By Within Anova Based On Medians, Rand R. Wilcox

Journal of Modern Applied Statistical Methods

This article considers a J by K ANOVA design where all JK groups are dependent and where groups are to be compared based on medians. Two general approaches are considered. The first is based on an omnibus test for no main effects and no interactions and the other tests each member of a collection of relevant linear contrasts. Based on an earlier paper dealing with multiple comparisons, an obvious speculation is that a particular bootstrap method should be used. One of the main points here is that, in general, this is not the case for the problem at hand. The …


Testing The Casual Relation Between Sunspots And Temperature Using Wavelets Analysis, Abdullah Almasri, Ghazi Shukur May 2005

Testing The Casual Relation Between Sunspots And Temperature Using Wavelets Analysis, Abdullah Almasri, Ghazi Shukur

Journal of Modern Applied Statistical Methods

Investigated and tested in this article are the causal nexus between sunspots and temperature by using statistical methodology and causality tests. Because this kind of relationship cannot be properly captured in the short run (daily, monthly or yearly data), the relationship is investigated in the long run using a very low frequency Wavelets-based decomposed data such as D8 (128 - 256 months). Results indicate that during the period 1854-1989, the causality nexus between these two series is as expected of onedirectional form, i.e., from sunspots to temperature.


Model-Selection-Based Monitoring Of Structural Change, Kosei Fukuda May 2005

Model-Selection-Based Monitoring Of Structural Change, Kosei Fukuda

Journal of Modern Applied Statistical Methods

Monitoring structural change is performed not by hypothesis testing but by model selection using a modified Bayesian information criterion. It is found that concerning detection accuracy and detection speed, the proposed method shows better performance than the hypothesis-testing method. Two advantages of the proposed method are also discussed.


Using Scale Mixtures Of Normals To Model Continuously Compounded Returns, Hasan Hamdan, John Nolan, Melanie Wilson, Kristen Dardia May 2005

Using Scale Mixtures Of Normals To Model Continuously Compounded Returns, Hasan Hamdan, John Nolan, Melanie Wilson, Kristen Dardia

Journal of Modern Applied Statistical Methods

A new method for estimating the parameters of scale mixtures of normals (SMN) is introduced and evaluated. The new method is called UNMIX and is based on minimizing the weighted square distance between exact values of the density of the scale mixture and estimated values using kernel smoothing techniques over a specified grid of x-values and a grid of potential scale values. Applications of the method are made in modeling the continuously compounded return, CCR, of stock prices. Modeling this ratio with UNMIX proves promising in comparison with other existing techniques that use only one normal component, or those that …


Bayesian Reliability Modeling Using Monte Carlo Integration, Vincent A. R. Camara, Chris P. Tsokos May 2005

Bayesian Reliability Modeling Using Monte Carlo Integration, Vincent A. R. Camara, Chris P. Tsokos

Journal of Modern Applied Statistical Methods

Bayesian Reliability Modeling Using Monte Carlo IntegrationThe aim of this article is to introduce the concept of Monte Carlo Integration in Bayesian estimation and Bayesian reliability analysis. Using the subject concept, approximate estimates of parameters and reliability functions are obtained for the three-parameter Weibull and the gamma failure models. Four different loss functions are used: square error, Higgins-Tsokos, Harris, and a logarithmic loss function proposed in this article. Relative efficiency is used to compare results obtained under the above mentioned loss functions.


Exploratory Factor Analysis In Two Measurement Journals: Hegemony By Default, J. Thomas Kellow May 2005

Exploratory Factor Analysis In Two Measurement Journals: Hegemony By Default, J. Thomas Kellow

Journal of Modern Applied Statistical Methods

Exploratory factor analysis studies in two prominent measurement journals were explored. Issues addressed were: (a) factor extraction methods, (b) factor retention rules, (c) factor rotation strategies, and (d) saliency criteria for including variables. Many authors continue to use principal components extraction, orthogonal (varimax) rotation, and retain factors with eigenvalues greater than 1.0.


An Algorithm For Generating Unconditional Exact Permutation Distribution For A Two-Sample Experiment, Justice I. Odiase, Sunday M. Ogbonmwan May 2005

An Algorithm For Generating Unconditional Exact Permutation Distribution For A Two-Sample Experiment, Justice I. Odiase, Sunday M. Ogbonmwan

Journal of Modern Applied Statistical Methods

An Algorithm that generates the unconditional exact permutation distribution of a 2 x n experiment is presented. The algorithm is able to handle ranks as well as actual observations. It makes it possible to obtain exact p-values for several statistics, especially when sample sizes are small and the application of large sample approximation is unreliable. An illustrative implementation is achieved and leads to the computation of exact p-values for the Mood test when the sample size is small.


A Comparison Of Nonlinear Regression Codes, Paul Fredrick Mondragon, Brian Borchers May 2005

A Comparison Of Nonlinear Regression Codes, Paul Fredrick Mondragon, Brian Borchers

Journal of Modern Applied Statistical Methods

Five readily available software packages were tested on nonlinear regression test problems from the NIST Statistical Reference Datasets. None of the packages was consistently able to obtain solutions accurate to at least three digits. However, two of the packages were somewhat more reliable than the others.


Fisheries Occasional Paper No. 19 - Management Of Western Rock Lobster Fishery - Proposed Resource Sustainability Management Package For The Northern Zones (A And B), Department Of Fisheries Western Australia May 2005

Fisheries Occasional Paper No. 19 - Management Of Western Rock Lobster Fishery - Proposed Resource Sustainability Management Package For The Northern Zones (A And B), Department Of Fisheries Western Australia

Fisheries Occasional Publications

The proposed effort reduction management package presented in this paper was developed in close co-operation with rock lobster industry to address the short-term sustainability concerns regarding the level of breeding stock in the northern region.

The management package does not address the serious long-term sustainability or socio-economic issues (e.g. cost pressures and related fleet capacity) facing the industry. If the fishery stays with input controls there will need to be regular reviews of the level of exploitation and its impact on the breeding stock. If exploitation increases and the breeding stock continues to decline additional fishing effort reductions in the …


Bias Of The Cox Model Hazard Ratio, Inger Persson, Harry Khamis May 2005

Bias Of The Cox Model Hazard Ratio, Inger Persson, Harry Khamis

Journal of Modern Applied Statistical Methods

The hazard ratio estimated with the Cox model is investigated under proportional and five forms of nonproportional hazards. Results indicate that the highest bias occurs for diverging hazards with early censoring, and for increasing and crossing hazards under a high censoring rate.


Bias Affiliated With Two Variants Of Cohen’S D When Determining U1 As A Measure Of The Percent Of Non-Overlap, David A. Walker May 2005

Bias Affiliated With Two Variants Of Cohen’S D When Determining U1 As A Measure Of The Percent Of Non-Overlap, David A. Walker

Journal of Modern Applied Statistical Methods

Variants of Cohen’s d, in this instance dt and dadj, has the largest influence on U1 measures used with smaller sample sizes, specifically when n1 and n2 = 10. This study indicated that bias for variants of d, which influence U1 measures, tends to subside and become more manageable, in terms of precision of estimation, around 1% to 2% when n1 and n2 = 20. Thus, depending on the direction of the influence, both dt and dadj are likely to manage bias in the U1 measure quite well for smaller to …


Some Guidelines For Using Nonparametric Methods For Modeling Data From Response Surface Designs, Christine M. Anderson-Cook, Kathryn Prewitt May 2005

Some Guidelines For Using Nonparametric Methods For Modeling Data From Response Surface Designs, Christine M. Anderson-Cook, Kathryn Prewitt

Journal of Modern Applied Statistical Methods

Traditional response surface methodology focuses on modeling responses using parametric models with designs chosen to balance cost with adequate estimation of parameters and prediction in the design space. Using nonparametric smoothing to approximate the response surface offers both opportunities as well as problems. This article explores some conditions under which these methods can be appropriately used to increase the flexibility of surfaces modeled. The Box and Draper (1987) printing ink study is considered to illustrate the methods.


Determining The Correct Number Of Components To Extract From A Principal Components Analysis: A Monte Carlo Study Of The Accuracy Of The Scree Plot, Gibbs Y. Kanyongo May 2005

Determining The Correct Number Of Components To Extract From A Principal Components Analysis: A Monte Carlo Study Of The Accuracy Of The Scree Plot, Gibbs Y. Kanyongo

Journal of Modern Applied Statistical Methods

This article pertains to the accuracy of the of the scree plot in determining the correct number of components to retain under different conditions of sample size, component loading and variable-tocomponent ratio. The study employs use of Monte Carlo simulations in which the population parameters were manipulated, and data were generated, and then the scree plot applied to the generated scores.


Bayesian Wavelet Estimation Of Long Memory Parameter, Leming Qu May 2005

Bayesian Wavelet Estimation Of Long Memory Parameter, Leming Qu

Journal of Modern Applied Statistical Methods

A Bayesian wavelet estimation method for estimating parameters of a stationary I(d) process is represented as an useful alternative to the existing frequentist wavelet estimation methods. The effectiveness of the proposed method is demonstrated through Monte Carlo simulations. The sampling from the posterior distribution is through the Markov Chain Monte Carlo (MCMC) easily implemented in the WinBUGS software package.


Enhancing The Performance Of A Short Run Multivariate Control Chart For The Process Mean, Michael B. C. Khoo, T. F. Ng May 2005

Enhancing The Performance Of A Short Run Multivariate Control Chart For The Process Mean, Michael B. C. Khoo, T. F. Ng

Journal of Modern Applied Statistical Methods

No abstract provided.


Jmasm16: Pseudo-Random Number Generation In R For Some Univariate Distributions, Hakan Demirtas May 2005

Jmasm16: Pseudo-Random Number Generation In R For Some Univariate Distributions, Hakan Demirtas

Journal of Modern Applied Statistical Methods

An increasing number of practitioners and applied researchers started using the R programming system in recent years for their computing and data analysis needs. As far as pseudo-random number generation is concerned, the built-in generator in R does not contain some important univariate distributions. In this article, complementary R routines that could potentially be useful for simulation and computation purposes are provided.


Jmasm17: An Algorithm And Code For Computing Exact Critical Values For Friedman’S Nonparametric Anova, Sikha Bagui, Sbuhash Bagui May 2005

Jmasm17: An Algorithm And Code For Computing Exact Critical Values For Friedman’S Nonparametric Anova, Sikha Bagui, Sbuhash Bagui

Journal of Modern Applied Statistical Methods

Provided in this article is an algorithm and code for computing exact critical values (or percentiles) for Friedman’s nonparametric rank test for k related treatment populations using Visual Basic (VB.NET). This program has the ability to calculate critical values for any number of treatment populations ( k ) and block sizes (b) at any significance level (α ) . We developed an exact critical value table for k = 2(1)5 and b = 2(1)15. This table will be useful to practitioners since it is not available in standard nonparametric statistics texts. The program can also be used to compute any …


Jmasm19: A Spss Matrix For Determining Effect Sizes From Three Categories: R And Functions Of R, Differences Between Proportions, And Standardized Differences Between Means, David A. Walker May 2005

Jmasm19: A Spss Matrix For Determining Effect Sizes From Three Categories: R And Functions Of R, Differences Between Proportions, And Standardized Differences Between Means, David A. Walker

Journal of Modern Applied Statistical Methods

The program is intended to provide editors, manuscript reviewers, students, and researchers with an SPSS matrix to determine an array of effect sizes not reported or the correctness of those reported, such as rrelated indices, r-related squared indices, and measures of association, when the only data provided in the manuscript or article are the n, M, and SD (and sometimes proportions and t and F (1) values) for twogroup designs. This program can create an internal matrix table to assist researchers in determining the size of an effect for commonly utilized r-related, mean difference, and difference in proportions indices when …


Letter To The Editor, Jmasm Editors May 2005

Letter To The Editor, Jmasm Editors

Journal of Modern Applied Statistical Methods

No abstract provided.


Fisheries Occasional Paper No. 20 - Management Of Western Rock Lobster Fishery - Advice To Stakeholders - Assessment Of Southern Zone Resource Sustainability Options, Department Of Fisheries, Western Australia May 2005

Fisheries Occasional Paper No. 20 - Management Of Western Rock Lobster Fishery - Advice To Stakeholders - Assessment Of Southern Zone Resource Sustainability Options, Department Of Fisheries, Western Australia

Fisheries Occasional Publications

The management options presented in this paper have been developed in close cooperation with the rock lobster industry to address the short-term sustainability and economic concerns regarding the level of exploitation and its impact on the breeding stock in the southern region. The main focus in the short-term is to consider options that reduce fishing effort during periods that may be economically inefficient to fish and at the same time reduce the level of exploitation.

The management package does not address the serious long-term sustainability or socioeconomic issues (e.g. cost pressures and related fleet capacity) facing the industry. If the …


An Exploration Of Using Data Mining In Educational Research, Yonghong Jade Xu May 2005

An Exploration Of Using Data Mining In Educational Research, Yonghong Jade Xu

Journal of Modern Applied Statistical Methods

Technology advances popularized large databases in education. Traditional statistics have limitations for analyzing large quantities of data. This article discusses data mining by analyzing a data set with three models: multiple regression, data mining, and a combination of the two. It is concluded that data mining is applicable in educational research.


Effect Of Position Of An Outlier On The Influence Curve Of The Measures Of Preferred Direction For Circular Data, B. Sango Otieno, Christine M. Anderson-Cook May 2005

Effect Of Position Of An Outlier On The Influence Curve Of The Measures Of Preferred Direction For Circular Data, B. Sango Otieno, Christine M. Anderson-Cook

Journal of Modern Applied Statistical Methods

Circular or angular data occur in many fields of applied statistics. A common problem of interest in circular data is estimating a preferred direction and its corresponding distribution. It is complicated by the wrap-around effect on the circle, which exists because there is no natural minimum or maximum. The usual statistics employed for linear data are inappropriate for directional data, as they do not account for its circular nature. The robustness of the three common choices for summarizing the preferred direction (the sample circular mean, sample circular median and a circular analog of the Hodges-Lehmann estimator) are evaluated via their …


An Empirical Evaluation Of The Retrospective Pretest: Are There Advantages To Looking Back?, Paul A. Nakonezny, Joseph Lee Rodgers May 2005

An Empirical Evaluation Of The Retrospective Pretest: Are There Advantages To Looking Back?, Paul A. Nakonezny, Joseph Lee Rodgers

Journal of Modern Applied Statistical Methods

This article builds on research regarding response shift effects and retrospective self-report ratings. Results suggest moderate evidence of a response shift bias in the conventional pretest-posttest treatment design in the treatment group. The use of explicitly worded anchors on response scales, as well as the measurement of knowledge ratings (a cognitive construct) in an evaluation methodology setting, helped to mitigate the magnitude of a response shift bias. The retrospective pretest-posttest design provides a measure of change that is more in accord with the objective measure of change than is the conventional pretest-posttest treatment design with the objective measure of change, …


Regression By Data Segments Via Discriminant Analysis, Stan Lipovetsky, Michael Conklin May 2005

Regression By Data Segments Via Discriminant Analysis, Stan Lipovetsky, Michael Conklin

Journal of Modern Applied Statistical Methods

It is known that two-group linear discriminant function can be constructed via binary regression. In this article, it is shown that the opposite relation is also relevant – it is possible to present multiple regression as a linear combination of a main part, based on the pooled variance, and Fisher discriminators by data segments. Presenting regression as an aggregate of the discriminators allows one to decompose coefficients of the model into sum of several vectors related to segments. Using this technique provides an understanding of how the total regression model is composed of the regressions by the segments with possible …


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 …


Local Power For Combining Independent Tests In The Presence Of Nuisance Parameters For The Logistic Distribution, Walid A. Abu-Dayyeh, Z. R. Al-Rawi, M. M. A. Al-Momani May 2005

Local Power For Combining Independent Tests In The Presence Of Nuisance Parameters For The Logistic Distribution, Walid A. Abu-Dayyeh, Z. R. Al-Rawi, M. M. A. Al-Momani

Journal of Modern Applied Statistical Methods

Four combination methods of independent tests for testing a simple hypothesis versus one-sided alternative are considered viz. Fisher, the logistic, the sum of P-values and the inverse normal method in case of logistic distribution. These methods are compared via local power in the presence of nuisance parameters for some values of α using simple random sample.


Special Classification Models For Lichens In The Pacific Northwest, Janeen Ardito May 2005

Special Classification Models For Lichens In The Pacific Northwest, Janeen Ardito

All Graduate Plan B and other Reports, Spring 1920 to Spring 2023

A common problem in ecological studies is that of determining where to look for rare species. This paper shows how statistical models, such as classification trees, may be used to assist in the design of probability-based surveys for rare species using information on more abundant species that are associated with the rare species. This model assisted approach to survey design involves first building models for the more abundant species. The models are then used to determine stratifications for the rare species that are associated with the more abundant species. The goal of this approach is to increase the number of …


A Comparison Of Parametric And Coarsened Bayesian Interval Estimation In The Presence Of A Known Mean-Variance Relationship, Kent Koprowicz, Scott S. Emerson, Peter Hoff Apr 2005

A Comparison Of Parametric And Coarsened Bayesian Interval Estimation In The Presence Of A Known Mean-Variance Relationship, Kent Koprowicz, Scott S. Emerson, Peter Hoff

UW Biostatistics Working Paper Series

While the use of Bayesian methods of analysis have become increasingly common, classical frequentist hypothesis testing still holds sway in medical research - especially clinical trials. One major difference between a standard frequentist approach and the most common Bayesian approaches is that even when a frequentist hypothesis test is derived from parametric models, the interpretation and operating characteristics of the test may be considered in a distribution-free manner. Bayesian inference, on the other hand, is often conducted in a parametric setting where the interpretation of the results is dependent on the parametric model. Here we consider a Bayesian counterpart to …


Quadratic Regression Analysis For Gene Discovery And Pattern Recognition For Non-Cyclic Short Time-Course Microarray Experiments, Hua Liu, Sergey Tarima, Aaron S. Borders, Thomas V. Getchell, Marilyn L. Getchell, Arnold J. Stromberg Apr 2005

Quadratic Regression Analysis For Gene Discovery And Pattern Recognition For Non-Cyclic Short Time-Course Microarray Experiments, Hua Liu, Sergey Tarima, Aaron S. Borders, Thomas V. Getchell, Marilyn L. Getchell, Arnold J. Stromberg

Statistics Faculty Publications

BACKGROUND: Cluster analyses are used to analyze microarray time-course data for gene discovery and pattern recognition. However, in general, these methods do not take advantage of the fact that time is a continuous variable, and existing clustering methods often group biologically unrelated genes together.

RESULTS: We propose a quadratic regression method for identification of differentially expressed genes and classification of genes based on their temporal expression profiles for non-cyclic short time-course microarray data. This method treats time as a continuous variable, therefore preserves actual time information. We applied this method to a microarray time-course study of gene expression at short …