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Articles 931 - 960 of 1133

Full-Text Articles in Statistical Theory

Statistical Pronouncements Iv, Jmasm Editors Nov 2005

Statistical Pronouncements Iv, Jmasm Editors

Journal of Modern Applied Statistical Methods

No abstract provided.

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Jmasm20: Exact Permutation Critical Values For The Kruskal-Wallis One-Way Anova, Justice I. Odiase, Sunday M. Ogbonmwan Nov 2005

Jmasm20: Exact Permutation Critical Values For The Kruskal-Wallis One-Way Anova, Justice I. Odiase, Sunday M. Ogbonmwan

Journal of Modern Applied Statistical Methods

The exhaustive enumeration of all the permutations of the observations in an experiment is the only possible way of truly constructing exact tests of significance. The permutation paradigm requires no distributional assumptions and works well with values that are normal, almost normal and non-normally distributed. The Kruskal-Wallis test does not require the assumptions that the samples are from normal populations and that the samples have the same standard deviation. In this article, the exact permutation distribution of the Kruskal-Wallis test statistic is generated empirically by actually obtaining all the distinct permutations of an experiment. The tables of exact critical values …

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Statistical Model And Estimation Of The Optimum Price For A Chain Of Price Setting Firms, Chengjie Xiong, Kejun Zhu Nov 2005

Statistical Model And Estimation Of The Optimum Price For A Chain Of Price Setting Firms, Chengjie Xiong, Kejun Zhu

Journal of Modern Applied Statistical Methods

A stochastic approach is used to model the economics of a chain of price setting firms. It is assumed that these firms have fixed capacities in their products, but random demands for their products. The optimum price, the optimum revenue, and the expected marginal revenue at a given price are investigated. The method of maximum likelihood is used to provide both point and confidence interval estimates. The coverage probabilities of confidence interval estimates based on a simulation study are presented.

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The Influence Of Reliability On Four Rules For Determining The Number Of Components To Retain, Gibbs Y. Kanyongo Nov 2005

The Influence Of Reliability On Four Rules For Determining The Number Of Components To Retain, Gibbs Y. Kanyongo

Journal of Modern Applied Statistical Methods

Imperfectly reliable scores impact the performance of factor analytic procedures. A series of Monte Carlo studies was conducted to generate scores with known component structure from population matrices with varying levels of reliability. The scores were submitted to four procedures: Kaiser rule, scree plot, parallel analysis, and modified Horn’s parallel analysis to find if each procedure accurately determines the number of components at the different reliability levels. The performance of each procedure was judged by the percentage of the number of times that the procedure was correct and the mean components that each procedure extracted in each cell. Generally, the …

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Corrections For Type I Error In Social Science Research: A Disconnect Between Theory And Practice, Kenneth Lachlan, Patric R. Spence Nov 2005

Corrections For Type I Error In Social Science Research: A Disconnect Between Theory And Practice, Kenneth Lachlan, Patric R. Spence

Journal of Modern Applied Statistical Methods

Type I errors are a common problem in factorial ANOVA and ANOVA based analyses. Despite decades of literature offering solutions to the Type I error problems associated with multiple significance tests, simple solutions such as Bonferroni corrections have been largely ignored by social scientists. To examine this discontinuity between theory and practice, a content analysis was performed on 5 flagship social science journals. Results indicate that corrections for Type I error are seldom utilized, even in designs so complicated as to almost guarantee erroneous rejection of null hypotheses.

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Model Selection Of Meat Demand System Using The Rotterdam Model And The Almost Ideal Demand System (Aids), Maria Divina S. Paraguas, Anton Abdulbasah Kamil Nov 2005

Model Selection Of Meat Demand System Using The Rotterdam Model And The Almost Ideal Demand System (Aids), Maria Divina S. Paraguas, Anton Abdulbasah Kamil

Journal of Modern Applied Statistical Methods

Aggregated time series data for differentiated meat products namely, beef, pork, poultry, and mutton were used to estimate and analyze Malaysian market demand for meats. The study aimed to select the most appropriate demand model between the equally popular Rotterdam model and the first difference Linear Approximate Almost Ideal Demand System (LA/AIDS) model by using a non-nested test. Both models were accepted, but further diagnostic tests revealed that the first difference LA/AIDS represents more appropriately the Malaysian market demand for meat than the Rotterdam model. Also, the elasticities from the first difference LA/AIDS were found to be more reliable than …

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Statistical Methods And Artificial Neural Networks, Mammadagha Mammadov, Berna Yazici, Şenay Yolaçan, Atilla Aslanargun, Ali Fuat YüZer, Embiya Ağaoğlu Nov 2005

Statistical Methods And Artificial Neural Networks, Mammadagha Mammadov, Berna Yazici, Şenay Yolaçan, Atilla Aslanargun, Ali Fuat YüZer, Embiya Ağaoğlu

Journal of Modern Applied Statistical Methods

Artificial Neural Networks and statistical methods are applied on real data sets for forecasting, classification, and clustering problems. Hybrid models for two components are examined on different data sets; tourist arrival forecasting to Turkey, macro-economic problem on rescheduling of the countries’ international debts, and grouping twenty-five European Union member and four candidate countries according to macro-economic indicators.

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Jmasm25: Computing Percentiles Of Skew-Normal Distributions, Sikha Bagui, Subhash Bagui Nov 2005

Jmasm25: Computing Percentiles Of Skew-Normal Distributions, Sikha Bagui, Subhash Bagui

Journal of Modern Applied Statistical Methods

An algorithm and code is provided for computing percentiles of skew-normal distributions with parameter λ using Monte Carlo methods. A critical values table was created for various parameter values of λ at various probability levels of α . The table will be useful to practitioners as it is not available in the literature.

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Applications Of Some Improved Estimators In Linear Regression, B. M. Golam Kibria Nov 2005

Applications Of Some Improved Estimators In Linear Regression, B. M. Golam Kibria

Journal of Modern Applied Statistical Methods

The problem of estimation of the regression coefficients under multicollinearity situation for the restricted linear model is discussed. Some improve estimators are considered, including the unrestricted ridge regression estimator (URRE), restricted ridge regression estimator (RRRE), shrinkage restricted ridge regression estimator (SRRRE), preliminary test ridge regression estimator (PTRRE), and restricted Liu estimator (RLIUE). The were compared based on the sampling variance-covariance criterion. The RRRE dominates other ridge estimators when the restriction does or does not hold. A numerical example was provided. The RRRE performed equivalently or better than the RLIUE in the sense of having smaller sampling variance.

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On The Power Function Of Bayesian Tests With Application To Design Of Clinical Trials: The Fixed-Sample Case, Lyle Broemeling, Dongfeng Wu May 2005

On The Power Function Of Bayesian Tests With Application To Design Of Clinical Trials: The Fixed-Sample Case, Lyle Broemeling, Dongfeng Wu

Journal of Modern Applied Statistical Methods

Using a Bayesian approach to clinical trial design is becoming more common. For example, at the MD Anderson Cancer Center, Bayesian techniques are routinely employed in the design and analysis of Phase I and II trials. It is important that the operating characteristics of these procedures be determined as part of the process when establishing a stopping rule for a clinical trial. This study determines the power function for some common fixed-sample procedures in hypothesis testing, namely the one and two-sample tests involving the binomial and normal distributions. Also considered is a Bayesian test for multi-response (response and toxicity) in …

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Two Sides Of The Same Coin: Bootstrapping The Restricted Vs. Unrestricted Model, Panagiotis Mantalos May 2005

Two Sides Of The Same Coin: Bootstrapping The Restricted Vs. Unrestricted Model, Panagiotis Mantalos

Journal of Modern Applied Statistical Methods

The properties of the bootstrap test for restrictions are studied in two versions: 1) bootstrapping under the null hypothesis, restricted, and 2) bootstrapping under the alternative hypothesis, unrestricted. This article demonstrates the equivalence of these two methods, and illustrates the small sample properties of the Wald test for testing Granger-Causality in a stable stationary VAR system by Monte Carlo methods. The analysis regarding the size of the test reveals that, as expected, both bootstrap tests have actual sizes that lie close to the nominal size. Regarding the power of the test, the Wald and bootstrap tests share the same power …

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Manifestation Of Differences In Item-Level Characteristics In Scale-Level Measurement Invariance Tests Of Multi-Group Confirmatory Factor Analyses, Bruno D. Zumbo, Kim H. Koh May 2005

Manifestation Of Differences In Item-Level Characteristics In Scale-Level Measurement Invariance Tests Of Multi-Group Confirmatory Factor Analyses, Bruno D. Zumbo, Kim H. Koh

Journal of Modern Applied Statistical Methods

If a researcher applies the conventional tests of scale-level measurement invariance through multi-group confirmatory factor analysis of a PC matrix and MLE to test hypotheses of strong and full measurement invariance when the researcher has a rating scale response format wherein the item characteristics are different for the two groups of respondents, do these scale-level analyses reflect (or ignore) differences in item threshold characteristics? Results of the current study demonstrate the inadequacy of judging the suitability of a measurement instrument across groups by only investigating the factor structure of the measure for the different groups with a PC matrix and …

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Right-Tailed Testing Of Variance For Non-Normal Distributions, Michael C. Long, Ping Sa May 2005

Right-Tailed Testing Of Variance For Non-Normal Distributions, Michael C. Long, Ping Sa

Journal of Modern Applied Statistical Methods

A new test of variance for non-normal distribution with fewer restrictions than the current tests is proposed. Simulation study shows that the new test controls the Type I error rate well, and has power performance comparable to the competitors. In addition, it can be used without restrictions.

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Multiple Imputation For Missing Ordinal Data, Ling Chen, Marian Toma-Drane, Robert F. Valois, J. Wanzer Drane May 2005

Multiple Imputation For Missing Ordinal Data, Ling Chen, Marian Toma-Drane, Robert F. Valois, J. Wanzer Drane

Journal of Modern Applied Statistical Methods

Simulations were used to compare complete case analysis of ordinal data with including multivariate normal imputations. MVN methods of imputation were not as good as using only complete cases. Bias and standard errors were measured against coefficients estimated from logistic regression and a standard data set.

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Coverage Properties Of Optimized Confidence Intervals For Proportions, John P. Wendell, Sharon P. Cox May 2005

Coverage Properties Of Optimized Confidence Intervals For Proportions, John P. Wendell, Sharon P. Cox

Journal of Modern Applied Statistical Methods

Wardell (1997) provided a method for constructing confidence intervals on a proportion that modifies the Clopper-Pearson (1934) interval by allowing for the upper and lower binomial tail probabilities to be set in a way that minimizes the interval width. This article investigates the coverage properties of these optimized intervals. It is found that the optimized intervals fail to provide coverage at or above the nominal rate over some portions of the binomial parameter space but may be useful as an approximate method.

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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 …

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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 …

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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.

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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.

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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 …

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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.

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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.

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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.

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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.

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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.

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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 …

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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.

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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.

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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.

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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.

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