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Articles 871 - 900 of 1091
Full-Text Articles in Statistical Theory
Selection Of Independent Binary Features Using Probabilities: An Example From Veterinary Medicine, Ludmila I. Kuncheva, Zoë S.J. Hoare, Peter D. Cockcroft
Selection Of Independent Binary Features Using Probabilities: An Example From Veterinary Medicine, Ludmila I. Kuncheva, Zoë S.J. Hoare, Peter D. Cockcroft
Journal of Modern Applied Statistical Methods
Supervised classification into c mutually exclusive classes based on n binary features is considered. The only information available is an n×c table with probabilities. Knowing that the best d features are not the d best, simulations were run for 4 feature selection methods and an application to diagnosing BSE in cattle and Scrapie in sheep is presented.
Training Statisticians To Be Alert To The Dangers Of Misapplying Statistical Methods, Vance W. Berger
Training Statisticians To Be Alert To The Dangers Of Misapplying Statistical Methods, Vance W. Berger
Journal of Modern Applied Statistical Methods
Statisticians are faced with a variety of challenges. Their ability to cope successfully with these challenges depends, in large part, on the quality of their training. It is not the purpose of this article to present a comprehensive training plan that will overhaul the standard curriculum a statistician might follow under current training regimens (i.e., in a degree program). Rather, the objective is to point out important areas that appear to be under-represented in standard curricula and correspondingly overlooked too often in practice. The hope is that these areas might be better integrated into the training of the next generation …
Power Of The T Test For Normal And Mixed Normal Distributions, Marilyn S. Thompson, Samuel B. Green, Yi-Hsin Chen, Shawn Stockford, Wen-Juo Lo
Power Of The T Test For Normal And Mixed Normal Distributions, Marilyn S. Thompson, Samuel B. Green, Yi-Hsin Chen, Shawn Stockford, Wen-Juo Lo
Journal of Modern Applied Statistical Methods
Previous research suggests that the power of the independent-samples t test decreases when population distributions are mixed normal rather than normal, and that robust methods have superior power under these conditions. However, under some conditions, the power for the independent-samples t test can be greater when the population distributions for the independent groups are mixed normal rather than normal. The implications of these results are discussed.
Misconceptions Leading To Choosing The T Test Over The Wilcoxon Mann-Whitney Test For Shift In Location Parameter, Shlomo S. Sawilowsky
Misconceptions Leading To Choosing The T Test Over The Wilcoxon Mann-Whitney Test For Shift In Location Parameter, Shlomo S. Sawilowsky
Journal of Modern Applied Statistical Methods
There exist many misconceptions in choosing the t over the Wilcoxon Rank-Sum test when testing for shift. Examples are given in the following three groups: (1) false statement, (2) true premise, but false conclusion, and (3) true statement irrelevant in choosing between the t test and the Wilcoxon Rank Sum test.
Jmasm21: Pcic_Sas: Best Subsets Using Information Criteria, C. Mitchell Dayton, Xuemei Pan
Jmasm21: Pcic_Sas: Best Subsets Using Information Criteria, C. Mitchell Dayton, Xuemei Pan
Journal of Modern Applied Statistical Methods
PCIC_SAS is a SAS program for identifying optimal subsets of means based on independent groups. All possible configurations of ordered subsets of groups are considered and a best model is identified using both the AIC and BIC information criteria. Results for models with homogeneous variances as well as models with heterogeneity of variance in the same pattern as the means are reported.
End Matter, Jmasm Editors
End Matter, Jmasm Editors
Journal of Modern Applied Statistical Methods
No abstract provided.
Second-Order Accurate Inference On Simple, Partial, And Multiple Correlations, Robert J. Boik, Ben Haaland
Second-Order Accurate Inference On Simple, Partial, And Multiple Correlations, Robert J. Boik, Ben Haaland
Journal of Modern Applied Statistical Methods
This article develops confidence interval procedures for functions of simple, partial, and squared multiple correlation coefficients. It is assumed that the observed multivariate data represent a random sample from a distribution that possesses infinite moments, but there is no requirement that the distribution be normal. The coverage error of conventional one-sided large sample intervals decreases at rate 1√n as n increases, where n is an index of sample size. The coverage error of the proposed intervals decreases at rate 1/n as n increases. The results of a simulation study that evaluates the performance of the proposed intervals is …
A Method For Analyzing Unreplicated Experiments Using Information On The Intraclass Correlation Coefficient, Jamis J. Perrett
A Method For Analyzing Unreplicated Experiments Using Information On The Intraclass Correlation Coefficient, Jamis J. Perrett
Journal of Modern Applied Statistical Methods
Many studies are performed on units that cannot be replicated; however, there is often an abundance of subsampling. By placing a reasonable upper bound on the intraclass correlation coefficient (ICC), it is possible to carry out classical tests of significance that have conservative levels of significance.
Ab/Ba Crossover Trials - Binary Outcome, James F. Reed Iii
Ab/Ba Crossover Trials - Binary Outcome, James F. Reed Iii
Journal of Modern Applied Statistical Methods
On occasion, the response to treatment in an AB/BA crossover trial is measured on a binary variable - success or failure. It is assumed that response to treatment is measured on an outcome variable with (+) representing a treatment success and a (-) representing a treatment failure. Traditionally, three tests for comparing treatment effect have been used (McNemar’s, Mainland-Gart, and Prescott’s). An issue arises concerning treatment comparisons when there may be a residual effect (carryover effect) of a previous treatment affecting the current treatment. A general consensus as to which procedure is preferable is debatable. However, if both group and …
Joseph Liouville’S ‘Mathematical Works Of Évariste Galois’, Shlomo S. Sawilowsky, John L. Cuzzocrea
Joseph Liouville’S ‘Mathematical Works Of Évariste Galois’, Shlomo S. Sawilowsky, John L. Cuzzocrea
Journal of Modern Applied Statistical Methods
Liouville’s 1846 introduction to the mathematical works of Galois is translated from French to flowing (American) English. It gave an overview of the tragic circumstances of the undergraduate mathematician whose originality led to major advances in abstract Algebra.
Interaction Graphs For 4R2N-P Fractional Factorial Designs, M. L. Aggarwal, S. Roy Chowdhury, Anita Bansal, Neena Mital
Interaction Graphs For 4R2N-P Fractional Factorial Designs, M. L. Aggarwal, S. Roy Chowdhury, Anita Bansal, Neena Mital
Journal of Modern Applied Statistical Methods
Interaction graphs have been developed for two-level and three-level fractional factorial designs under different design criteria. A catalogue is presented of all possible non-isomorphic interaction graphs for 4r2n-p (r=1; n=2,…, 10; p=1,…,8 and r=2; n=1,…, 7; p=1,…,7) fractional factorial designs, and nonisomorphic interaction graphs for asymmetric fractional factorial designs under the concept of combined array.
Jmasm24: Numerical Computing For Third-Order Power Method Polynomials (Excel), Todd C. Headrick
Jmasm24: Numerical Computing For Third-Order Power Method Polynomials (Excel), Todd C. Headrick
Journal of Modern Applied Statistical Methods
The power method polynomial transformation is a popular procedure used for simulating univariate and multivariate non-normal distributions. It requires software that solves simultaneous nonlinear equations. Potential users of the power method may not have access to commercial software packages (e.g., Mathematica, Fortran). Therefore, algorithms are presented in the more commonly available Excel 2003 spreadsheets. The algorithms solve for (1) coefficients for polynomials of order three, (2) intermediate correlations and Cholesky factorizations for multivariate data generation, and (3) the values of skew and kurtosis for determining if a transformation will produce a valid power method probability density function (pdf). The Excel …
A Discretized Approach To Flexibly Fit Generalized Lambda Distributions To Data, Steve Su
A Discretized Approach To Flexibly Fit Generalized Lambda Distributions To Data, Steve Su
Journal of Modern Applied Statistical Methods
This article presents a flexible approach to fit statistical distribution to data. It optimizes the bin-width of data histogram to find a suitable generalized lambda distribution. In addition to the default optimization, this approach provides additional flexibility akin to the concepts of loess and kernel smoothing, which allow the users to determine the amount of details they would like to smooth over the data. The approach presented in this article will allow users to visually compare and choose the parameters of generalized lambda distribution that best suit their purposes of study.
A Single, Powerful, Nonparametric Statistic For Continuous-Data Telecommunications Parity Testing, J. D. Opdyke
A Single, Powerful, Nonparametric Statistic For Continuous-Data Telecommunications Parity Testing, J. D. Opdyke
Journal of Modern Applied Statistical Methods
Since the enactment of the Telecommunications Act of 1996, extensive expert testimony has justified use of the modified t statistic (Brownie et al., 1990) for performing two-sample hypothesis tests comparing Bell companies’ CLEC and ILEC performance measurement data (known as parity testing). However, Opdyke (Telecommunications Policy, 2004) demonstrated this statistic to be potentially manipulable and to have literally zero power to detect inferior CLEC service provision under a wide range of relevant data conditions. This article develops a single, nonparametric statistic that is easily implemented (i.e., not computationally intensive) and typically provides dramatic power gains over the modified t while …
Testing Goodness Of Fit Of The Geometric Distribution: An Application To Human Fecundability Data, Sudhir R. Paul
Testing Goodness Of Fit Of The Geometric Distribution: An Application To Human Fecundability Data, Sudhir R. Paul
Journal of Modern Applied Statistical Methods
A measure of reproduction in human fecundability studies is the number of menstrual cycles required to achieve pregnancy which is assumed to follow a geometric distribution with parameter p. Tests of heterogeneity in the fecundability data through goodness of fit tests of the geometric distribution are developed, along with a likelihood ratio test statistic and a score test statistic. Simulations show both are liberal, and empirical level of the likelihood ratio statistic is larger than that of the score test statistic. A power comparison shows that the likelihood ratio test has a power advantage. A bootstrap p-value procedure using the …
Estimation Of Process Variances In Robust Parameter Designs, T. K. Mak, Fassil Nebebe
Estimation Of Process Variances In Robust Parameter Designs, T. K. Mak, Fassil Nebebe
Journal of Modern Applied Statistical Methods
The modeling of variation through interactions is appealing in crossed array design as it leads to greater robustness to certain type of model misspecification. As an alternative to signal-to-noise analysis, a new, systematic method based on Taguchi type crossed array design is given. It is shown in this article that when fractional factorial design is used for the outer array, the crossed array design is not robust to the presence of noise-noise interactions and a method of rectifying the problem is suggested.
Simulation Procedure In Periodic Cancer Screening Trials, Ioana Barnicescu, Ricolindo L. Cariño
Simulation Procedure In Periodic Cancer Screening Trials, Ioana Barnicescu, Ricolindo L. Cariño
Journal of Modern Applied Statistical Methods
A general simulation procedure is described to validate model fitting algorithms for complex likelihood functions that are utilized in periodic cancer screening trials. Although screening programs have existed for a few decades, there are still many unsolved problems, such as how age or hormone affects the screening sensitivity, the sojourn time in the preclinical state, and the transition probability from diseasefree state to the preclinical state. Simulations are needed to check reliability or validity of the likelihood function combined with the associated effect functions. One bottleneck in the simulation procedure is the very time consuming calculations of the maximum likelihood …
Inference On (Y < X) In A Pareto Distribution, M. Masoom Ali, Jungsoo Woo
Inference On (Y < X) In A Pareto Distribution, M. Masoom Ali, Jungsoo Woo
Journal of Modern Applied Statistical Methods
Inference on the reliability R = P(Y < X) in a Pareto distribution with a known scale parameter is considered. Point estimates and confidence intervals of R are obtained a test of hypothesis is also considered.
Nonparametric Pooling And Testing Of Preference Ratings For Full-Profile Conjoint Analysis Experiments, Rosa Arboretti G., Marco Marozzi, Luigi Salmaso
Nonparametric Pooling And Testing Of Preference Ratings For Full-Profile Conjoint Analysis Experiments, Rosa Arboretti G., Marco Marozzi, Luigi Salmaso
Journal of Modern Applied Statistical Methods
The problem of pooling customer preference ratings within a conjoint analysis experiment has been addressed. A method based on the nonparametric combination of rankings has been proposed to compete with the usual method based on the arithmetic mean. This method is nonparametric with respect to the underlying dependence structure and so no dependence model must be assumed. The two methods have been compared using Spearman’s rank correlation coefficient and related test. Moreover, a further nonparametric testing method has been considered and proposed; this method takes both correlation and distance between ranks into account. By means of a simulation study it …
Statistical Pronouncements Iv, Jmasm Editors
Statistical Pronouncements Iv, Jmasm Editors
Journal of Modern Applied Statistical Methods
No abstract provided.
Jmasm20: Exact Permutation Critical Values For The Kruskal-Wallis One-Way Anova, Justice I. Odiase, Sunday M. Ogbonmwan
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 …
Statistical Model And Estimation Of The Optimum Price For A Chain Of Price Setting Firms, Chengjie Xiong, Kejun Zhu
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.
The Influence Of Reliability On Four Rules For Determining The Number Of Components To Retain, Gibbs Y. Kanyongo
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 …
Corrections For Type I Error In Social Science Research: A Disconnect Between Theory And Practice, Kenneth Lachlan, Patric R. Spence
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.
Model Selection Of Meat Demand System Using The Rotterdam Model And The Almost Ideal Demand System (Aids), Maria Divina S. Paraguas, Anton Abdulbasah Kamil
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 …
Statistical Methods And Artificial Neural Networks, Mammadagha Mammadov, Berna Yazici, Şenay Yolaçan, Atilla Aslanargun, Ali Fuat YüZer, Embiya Ağaoğlu
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.
Jmasm25: Computing Percentiles Of Skew-Normal Distributions, Sikha Bagui, Subhash Bagui
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.
Applications Of Some Improved Estimators In Linear Regression, B. M. Golam Kibria
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.
On The Power Function Of Bayesian Tests With Application To Design Of Clinical Trials: The Fixed-Sample Case, Lyle Broemeling, Dongfeng Wu
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 …
Two Sides Of The Same Coin: Bootstrapping The Restricted Vs. Unrestricted Model, Panagiotis Mantalos
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 …