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Articles 1201 - 1230 of 1395

Full-Text Articles in Applied Statistics

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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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.

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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 …

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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 …

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Letter To The Editor, Jmasm Editors May 2005

Letter To The Editor, Jmasm Editors

Journal of Modern Applied Statistical Methods

No abstract provided.

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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.

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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 …

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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, …

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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 …

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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 …

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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.

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Assessing Treatment Effects In Randomized Longitudinal Two-Group Designs With Missing Observations, James Algina, H. J. Keselman Nov 2004

Assessing Treatment Effects In Randomized Longitudinal Two-Group Designs With Missing Observations, James Algina, H. J. Keselman

Journal of Modern Applied Statistical Methods

SAS’s PROC MIXED can be problematic when analyzing data from randomized longitudinal two-group designs when observations are missing over time. Overall (1996, 1999) and colleagues found a number of procedures that are effective in controlling the number of false positives (Type I errors) and are yet sensitive (powerful) to detect treatment effects. Two favorable methods incorporate time in study and baseline scores to model the missing data mechanism; one method was a single-stage PROC MIXED ANCOVA solution and the other was a two-stage endpoint analysis using the change scores as dependent scores. Because the twostage approach can lack sensitivity to …

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Type I Error Rates For A One Factor Within-Subjects Design With Missing Values, Miguel A. Padilla, James Algina Nov 2004

Type I Error Rates For A One Factor Within-Subjects Design With Missing Values, Miguel A. Padilla, James Algina

Journal of Modern Applied Statistical Methods

Missing data are a common problem in educational research. A promising technique, that can be implemented in SAS PROC MIXED and is therefore widely available, is to use maximum likelihood to estimate model parameters and base hypothesis tests on these estimates. However, it is not clear which test statistic in PROC MIXED performs better with missing data. The performance of the Hotelling- Lawley-McKeon and Kenward-Roger omnibus test statistics on the means for a single factor withinsubject ANOVA are compared. The results indicate that the Kenward-Roger statistic performed better in terms of keeping the Type I error close to the nominal …

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Size And Power Of The Reset Test As Applied To Systems Of Equations: A Bootstrap Approach, Ghazi Shukur, Panagiotis Mantalos Nov 2004

Size And Power Of The Reset Test As Applied To Systems Of Equations: A Bootstrap Approach, Ghazi Shukur, Panagiotis Mantalos

Journal of Modern Applied Statistical Methods

The size and power of various generalization of the RESET test for functional misspecification are investigated, using the “Bootsrap critical values”, in systems ranging from one to ten equations. The properties of 8 versions of the test are studied using Monte Carlo methods. The results are then compared with another study of Shukur and Edgerton (2002), in which they used the asymptotic critical values instead and found that in general only one version of the tests works well regarding size properties. In our study, when applying the bootstrap critical values, we find that all the tests exhibits correct size even …

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Variance Stabilizing Power Transformation For Time Series, Victor M. Guerrero, Rafael Perera Nov 2004

Variance Stabilizing Power Transformation For Time Series, Victor M. Guerrero, Rafael Perera

Journal of Modern Applied Statistical Methods

A confidence interval was derived for the index of a power transformation that stabilizes the variance of a time-series. The process starts from a model-independent procedure that minimizes a coefficient of variation to yield a point estimate of the transformation index. The confidence coefficient of the interval is calibrated through a simulation.

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Multivariate Contrasts For Repeated Measures Designs Under Assumption Violations, Lisa M. Lix, Aynslie M. Hinds Nov 2004

Multivariate Contrasts For Repeated Measures Designs Under Assumption Violations, Lisa M. Lix, Aynslie M. Hinds

Journal of Modern Applied Statistical Methods

Conventional and approximate degrees of freedom procedures for testing multivariate interaction contrasts in groups by trials repeated measures designs were compared under assumption violation conditions. Procedures were based on either least-squares or robust estimators. Power generally favored test procedures based on robust estimators for non-normal distributions, but was influenced by the degree of departure from non-normality, definition of power, and magnitude of the multivariate effect size.

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Interval Estimation For The Scale Parameter Of Burr Type X Distribution Based On Grouped Data, Amjad D. Al-Nasser, Ayman Baklizi Nov 2004

Interval Estimation For The Scale Parameter Of Burr Type X Distribution Based On Grouped Data, Amjad D. Al-Nasser, Ayman Baklizi

Journal of Modern Applied Statistical Methods

The application of some bootstrap type intervals for the scale parameter of the Burr type X distribution with grouped data is proposed. The general asymptotic confidence interval procedure (Chen & Mi, 2001) is studied. The performance of these intervals is investigated and compared. Some of the bootstrap intervals give better performance for situations of small sample size and heavy censoring.

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An Algorithm And Code For Computing Exact Critical Values For The Kruskal-Wallis Nonparametric One-Way Anova, Sikha Bagui, Subhash Bagui Nov 2004

An Algorithm And Code For Computing Exact Critical Values For The Kruskal-Wallis Nonparametric One-Way Anova, Sikha Bagui, Subhash Bagui

Journal of Modern Applied Statistical Methods

In this article, an algorithm and code to compute exact critical values (or percentiles) for Kruskal-Wallis test on k independent treatment populations with equal or unequal sample sizes using Visual Basic (VB.NET) is provided. This program has the ability to calculate critical values for any k , sample sizes (ni ) , and significance level (α ) . An exact critical value table for k = 4 is also developed. The 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 other …

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Pseudo-Random Number Generation In R For Commonly Used Multivariate Distributions, Hakan Demirtas Nov 2004

Pseudo-Random Number Generation In R For Commonly Used Multivariate Distributions, Hakan Demirtas

Journal of Modern Applied Statistical Methods

An increasing number of practitioners and applied statisticians have 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 multivariate distributions. In this article, R routines for widely used multivariate distributions are presented.

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Confidence Intervals On Subsets May Be Misleading, Juliet Popper Shaffer Nov 2004

Confidence Intervals On Subsets May Be Misleading, Juliet Popper Shaffer

Journal of Modern Applied Statistical Methods

A combination of hypothesis testing and confidence interval construction is often used in social and behavioral science studies. Sometimes confidence intervals are computed or reported only if a null hypothesis is rejected, perhaps to see whether the range of values is of practical importance. Sometimes they are constructed or reported only if a null hypothesis is accepted, in order to assess the range of plausible nonnull values due to inadequate power to detect them. Even if always computed, they are interpreted differently, depending on whether the null value is or is not included. Furthermore, many studies in which the null …

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Mentoring Doctoral Students: A Personal Perspective, Bruce W. Hall Nov 2004

Mentoring Doctoral Students: A Personal Perspective, Bruce W. Hall

Journal of Modern Applied Statistical Methods

In this brief essay, I reflect on the mentoring process based on advising over thirty doctoral students in measurement, evaluation, and research. There is considerable cause for optimism, and it is among the professors’ highest honor to mentor the doctoral student.

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On A Simple Method For Analyzing Multivariate Survival Data Using Sample Survey Methods, Pingfu Fu, J. Sunil Rao Nov 2004

On A Simple Method For Analyzing Multivariate Survival Data Using Sample Survey Methods, Pingfu Fu, J. Sunil Rao

Journal of Modern Applied Statistical Methods

A simple technique is illustrated for analyzing multivariate survival data. The data situation arises when an individual records multiple survival events, or when individuals recording single survival events are grouped into clusters. Past work has focused on developing new methods to handle such data. Here, we use a connection between Poisson regression and survival modeling and a cluster sampling approach to adjust the variance estimates. The approach requires parametric assumption for the marginal hazard function, but avoids specification of a joint multivariate survival distribution. A simulation study demonstrates the proposed approach is a competing method of recent developed marginal approaches …

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Monte Carlo Evaluation Of Ordinal D With Improved Confidence Interval, Du Feng, Norman Cliff Nov 2004

Monte Carlo Evaluation Of Ordinal D With Improved Confidence Interval, Du Feng, Norman Cliff

Journal of Modern Applied Statistical Methods

This article reports a Monte Carlo evaluation of ordinal statistic d with modified confidence intervals (CI) for location comparison of two independent groups under various conditions. Type I error rate, power, and coverage of CI of d were compared to those of the Welch's t-test.

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Confidence Elicitation And Anchoring In The Respondent-Generated Intervals (Rgi) Protocol, Liping Chu, S. James Press, Judith M. Tanur Nov 2004

Confidence Elicitation And Anchoring In The Respondent-Generated Intervals (Rgi) Protocol, Liping Chu, S. James Press, Judith M. Tanur

Journal of Modern Applied Statistical Methods

The Respondent-Generated Intervals protocol (RGI) has been used to have respondents recall the answer to a factual question by giving not only a point estimate but also bounds within which they feel it is almost certain that the true value of the quantity being reported upon falls. The RGI protocol is elaborated in this article with the goal of improving the accuracy of the estimators by introducing cueing mechanisms to direct confident (and thus presumably accurate) respondents to give shorter intervals and less confident (and thus presumably less accurate) respondents to give longer ones.

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A Note On Extending Scheffé’S Modified Multiple-Comparison Procedure To Other Analysis Situations, Xinyue Zhou, Joel R. Levin Nov 2004

A Note On Extending Scheffé’S Modified Multiple-Comparison Procedure To Other Analysis Situations, Xinyue Zhou, Joel R. Levin

Journal of Modern Applied Statistical Methods

This article extends Scheffé’s modified (sequential) multiple-comparison procedure in one-way analysisof- variance to other analysis situations, including interaction comparisons in factorial ANOVA designs, tests of partial regression coefficients in multiple-regression analysis, and comparisons of means in onefactor multivariate analyses of variance. Researchers who are concerned with maintaining familywise Type I error rates while increasing statistical power relative to the original (simultaneous) Scheffé-based procedures are encouraged to consider these improved multiple-comparison methods.

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A Modification Of The Em Algorithm To Estimate An Andersen-Gill Gamma Frailty Model For Multivariate Failure Time Data, Maria Antònia Barceló, Marc Saez Nov 2004

A Modification Of The Em Algorithm To Estimate An Andersen-Gill Gamma Frailty Model For Multivariate Failure Time Data, Maria Antònia Barceló, Marc Saez

Journal of Modern Applied Statistical Methods

A modification of the Andersen-Gill gamma shared frailty model is presented. The variance of the frailty is directly modeled by means of a generalized linear model, the EM algorithm is modified in order to simultaneously estimate a semiparametric model for the failure times and a model for the variance of the frailty. A simulation study is conducted to evaluate the performance of the proposed algorithm (EMB algorithm) and compared with other methods, a marginal model, and a conditional model. Multivariate data from a nosocomial infection study is used to illustrate the methods. The EMB fit turned out to be better …

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An Overview Of The Respondent-Generated Intervals (Rgi) Approach To Sample Surveys, S. James Press, Judith M. Tanur Nov 2004

An Overview Of The Respondent-Generated Intervals (Rgi) Approach To Sample Surveys, S. James Press, Judith M. Tanur

Journal of Modern Applied Statistical Methods

This article brings together many years of research on the Respondent-Generated Intervals (RGI) approach to recall in factual sample surveys. Additionally presented is new research on the use of RGI in opinion surveys and the use of RGI with gamma-distributed data. The research combines Bayesian hierarchical modeling with various cognitive aspects of sample surveys.

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