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Articles 61 - 90 of 93
Full-Text Articles in Social and Behavioral Sciences
Inferences About The Components Of A Generalized Additive Model, Rand R. Wilcox
Inferences About The Components Of A Generalized Additive Model, Rand R. Wilcox
Journal of Modern Applied Statistical Methods
A method for making inferences about the components of a generalized additive model is described. It is found that a variation of the method, based on means, performs well in simulations. Unlike many other inferential methods, switching from a mean to a 20% trimmed mean was found to offer little or no advantage in terms of both power and controlling the probability of a Type I error.
The Individuals Control Chart In Case Of Non-Normality, BetüL Kan, Berna Yazici
The Individuals Control Chart In Case Of Non-Normality, BetüL Kan, Berna Yazici
Journal of Modern Applied Statistical Methods
This article examines the effects of non-normality as measured by skewness and provides an alternative method of designing individuals control chart with non-normal distributions. A skewness correction method for constructing the individuals control chart is provided. An example of thickness of biscuit process is presented to illustrate the individuals control chart limits.
Within By Within Anova Based On Medians, Rand R. Wilcox
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 …
Regression By Data Segments Via Discriminant Analysis, Stan Lipovetsky, Michael Conklin
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 …
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
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.
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
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 …
Bias Of The Cox Model Hazard Ratio, Inger Persson, Harry Khamis
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.
Testing The Casual Relation Between Sunspots And Temperature Using Wavelets Analysis, Abdullah Almasri, Ghazi Shukur
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.
Bayesian Wavelet Estimation Of Long Memory Parameter, Leming Qu
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.
Model-Selection-Based Monitoring Of Structural Change, Kosei Fukuda
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.
Bayesian Reliability Modeling Using Monte Carlo Integration, Vincent A. R. Camara, Chris P. Tsokos
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.
Using Scale Mixtures Of Normals To Model Continuously Compounded Returns, Hasan Hamdan, John Nolan, Melanie Wilson, Kristen Dardia
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 …
Enhancing The Performance Of A Short Run Multivariate Control Chart For The Process Mean, Michael B. C. Khoo, T. F. Ng
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.
An Empirical Evaluation Of The Retrospective Pretest: Are There Advantages To Looking Back?, Paul A. Nakonezny, Joseph Lee Rodgers
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, …
An Exploration Of Using Data Mining In Educational Research, Yonghong Jade Xu
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.
Exploratory Factor Analysis In Two Measurement Journals: Hegemony By Default, J. Thomas Kellow
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.
Jmasm16: Pseudo-Random Number Generation In R For Some Univariate Distributions, Hakan Demirtas
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
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 …
An Algorithm For Generating Unconditional Exact Permutation Distribution For A Two-Sample Experiment, Justice I. Odiase, Sunday M. Ogbonmwan
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
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.
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
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.
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 …
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 …
Inferences About Regression Interactions Via A Robust Smoother With An Application To Cannabis Problems, Rand R. Wilcox, Mitchell Earleywine
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 …
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 …
Right-Tailed Testing Of Variance For Non-Normal Distributions, Michael C. Long, Ping Sa
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.
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
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 …
Some Guidelines For Using Nonparametric Methods For Modeling Data From Response Surface Designs, Christine M. Anderson-Cook, Kathryn Prewitt
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.
Multiple Imputation For Missing Ordinal Data, Ling Chen, Marian Toma-Drane, Robert F. Valois, J. Wanzer Drane
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.
Letter To The Editor, Jmasm Editors
Letter To The Editor, Jmasm Editors
Journal of Modern Applied Statistical Methods
No abstract provided.