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Articles 961 - 990 of 1093
Full-Text Articles in Physical Sciences and Mathematics
A Comparison Of Methods For Longitudinal Analysis With Missing Data, James Algina, H. J. Keselman
A Comparison Of Methods For Longitudinal Analysis With Missing Data, James Algina, H. J. Keselman
Journal of Modern Applied Statistical Methods
In a longitudinal two-group randomized trials design, also referred to as randomized parallel-groups design or split-plot repeated measures design, the important hypothesis of interest is whether there are differential rates of change over time, that is, whether there is a group by time interaction. Several analytic methods have been presented in the literature for testing this important hypothesis when data are incomplete. We studied these methods for the case in which the missing data pattern is non-monotone. In agreement with earlier work on monotone missing data patterns, our results on bias, sampling variability, Type I error and power support the …
A Power Comparison Of Robust Test Statistics Based On Adaptive Estimators, H. J. Keselman, Rand R. Wilcox, James Algina, Abdul R. Othman
A Power Comparison Of Robust Test Statistics Based On Adaptive Estimators, H. J. Keselman, Rand R. Wilcox, James Algina, Abdul R. Othman
Journal of Modern Applied Statistical Methods
Seven test statistics known to be robust to the combined effects of nonnormality and variance heterogeneity were compared for their sensitivity to detect treatment effects in a one-way completely randomized design containing four groups. The six Welch-James-type heteroscedastic tests adopted either symmetric or asymmetric trimmed means, were transformed for skewness, and used a bootstrap method to assess statistical significance. The remaining test, due to Wilcox and Keselman (2003), used a modification of the well-known one-step M-estimator of central tendency rather than trimmed means. The Welch-James-type test is recommended because for nonnormal data likely to be encountered in applied research settings …
A Rank-Based Estimation Procedure For Linear Models With Clustered Data, Suzanne R. Dubnicka
A Rank-Based Estimation Procedure For Linear Models With Clustered Data, Suzanne R. Dubnicka
Journal of Modern Applied Statistical Methods
A rank method is presented for estimating regression parameters in the linear model when observations are correlated. This correlation is accounted for by including a random effect term in the linear model. A method is proposed that makes few assumptions about the random effect and error distribution. The main goal of this article is to determine the distributions for which this method performs well relative to existing methods.
Quantifying The Proportion Of Cases Attributable To An Exposure, Camil Fuchs, Vance W. Berger
Quantifying The Proportion Of Cases Attributable To An Exposure, Camil Fuchs, Vance W. Berger
Journal of Modern Applied Statistical Methods
The attributable fraction and the average attributable fractions, which are commonly used to assess the relative effect of several exposures to the prevalence of a disease, do not represent the proportion of cases caused by each exposure. Furthermore, the sum of attributable fractions over all exposures generally exceeds not only the attributable fraction for all exposures taken together, but also 100%. Other measures are discussed here, including the directly attributable fraction and the confounding fraction, that may be more suitable in defining the fraction directly attributable to an exposure.
On Polynomial Transformations For Simulating Multivariate Non-Normal Distributions, Todd C. Headrick
On Polynomial Transformations For Simulating Multivariate Non-Normal Distributions, Todd C. Headrick
Journal of Modern Applied Statistical Methods
Procedures are introduced and discussed for increasing the computational and statistical efficiency of polynomial transformations used in Monte Carlo or simulation studies. Comparisons are also made between polynomials of order three and five in terms of (a) computational and statistical efficiency, (b) the skew and kurtosis boundary, and (c) boundaries for Pearson correlations. It is also shown how ranked data can be simulated for specified Spearman correlations and sample sizes. Potential consequences of nonmonotonic transformations on rank correlations are also discussed.
An Alternative Q Chart Incorporating A Robust Estimator Of Scale, Michael B. C. Khoo
An Alternative Q Chart Incorporating A Robust Estimator Of Scale, Michael B. C. Khoo
Journal of Modern Applied Statistical Methods
In overcoming the shortcomings of the classical control charts in a short runs production, Quesenberry (1991 & 1995a – d) proposed Q charts for attributes and variables data. An approach to enhance the performance of a variable Q chart based on individual measurements using a robust estimator of scale is proposed. Monte carlo simulations are conducted to show that the proposed robust Q chart is superior to the present Q chart.
Beta-Normal Distribution: Bimodality Properties And Application, Felix Famoye, Carl Lee, Nicholas Eugene
Beta-Normal Distribution: Bimodality Properties And Application, Felix Famoye, Carl Lee, Nicholas Eugene
Journal of Modern Applied Statistical Methods
The beta-normal distribution is characterized by four parameters that jointly describe the location, the scale and the shape properties. The beta-normal distribution can be unimodal or bimodal. This paper studies the bimodality properties of the beta-normal distribution. The region of bimodality in the parameter space is obtained. The beta-normal distribution is applied to fit a numerical bimodal data set. The beta-normal fits are compared with the fits of mixture-normal distribution through simulation.
Respondent-Generated Intervals (Rgi) For Recall In Sample Surveys, S. James Press
Respondent-Generated Intervals (Rgi) For Recall In Sample Surveys, S. James Press
Journal of Modern Applied Statistical Methods
Respondents are asked for both a basic response to a recall-type question, their usage quantity, and are asked to provide lower and upper bounds for the (Respondent-Generated) interval in which their true values might possibly lie. A Bayesian hierarchical model for estimating the population mean and its variance is presented.. Telephone: (989) 774-
Estimation Using Bivariate Extreme Ranked Set Sampling With Application To The Bivariate Normal Distribution, Mohammad Fraiwan Al-Saleh, Hani M. Samawi
Estimation Using Bivariate Extreme Ranked Set Sampling With Application To The Bivariate Normal Distribution, Mohammad Fraiwan Al-Saleh, Hani M. Samawi
Journal of Modern Applied Statistical Methods
In this article, the procedure of bivariate extreme ranked set sampling (BVERSS) is introduced and investigated as a procedure of obtaining more accurate samples for estimating the parameters of bivariate populations. This procedure takes its strength from the advantages of bivariate ranked set sampling (BVRSS) over the usual ranked set sampling in dealing with two characteristics simultaneously, and the advantages of extreme ranked set sampling (ERSS) over usual RSS in reducing the ranking errors and hence in being more applicable. The BVERSS procedure will be applied to the case of the parameters of the bivariate normal distributions. Illustration using real …
Kernel-Based Estimation Of P(X Less Than Y)With Paired Data, Omar M. Eidous, Ayman Baklizi
Kernel-Based Estimation Of P(X Less Than Y)With Paired Data, Omar M. Eidous, Ayman Baklizi
Journal of Modern Applied Statistical Methods
A point estimation of P(X < Y) was considered. A nonparametric estimator for P(X < Y) was developed using the kernel density estimator of the joint distribution of X and Y, may be dependent. The resulting estimator was found to be similar to the estimator based on the sign statistic, however it assigns smooth continuous scores to each pair of the observations rather than the zero or one scores of the sign statistic. The asymptotic equivalence of the sign statistic and the proposed estimator is shown and a simulation study is conducted to investigate the performance of the proposed estimator. Results indicate that …
Some Improvements In Kernel Estimation Using Line Transect Sampling, Omar M. Eidous
Some Improvements In Kernel Estimation Using Line Transect Sampling, Omar M. Eidous
Journal of Modern Applied Statistical Methods
Kernel estimation provides a nonparametric estimate of the probability density function from which a set of data is drawn. This article proposes a method to choose a reference density in bandwidth calculation for kernel estimator using line transect sampling. The method based on testing the shoulder condition, if the shoulder condition seems to be valid using as reference the half normal density, while if the shoulder condition does not seem to be valid, we will use exponential reference density. Accordingly, the performances of the resultant estimator are studied under a wide range of underlying models using simulation techniques. The results …
A Generalized Quasi-Likelihood Model Application To Modeling Poverty Of Asian American Women, Jeffrey R. Wilson
A Generalized Quasi-Likelihood Model Application To Modeling Poverty Of Asian American Women, Jeffrey R. Wilson
Journal of Modern Applied Statistical Methods
A generalized quasi-likelihood function that does not require the assumption of an underlying distribution when modeling jointly the mean and the variance, is introduced to examine poverty of Asian American women living in the West coast of the United States, using data from U.S. Census Bureau.
A Visually Adaptive Bayesian Model In Wavelet Regression, Dongfeng Wu
A Visually Adaptive Bayesian Model In Wavelet Regression, Dongfeng Wu
Journal of Modern Applied Statistical Methods
The implementation of a Bayesian approach to wavelet regression that corresponds to the human visual system is examined. Most existing research in this area assumes non-informative priors, that is, a prior with mean zero. A new way is offered to implement prior information that mimics a visual inspection of noisy data, to obtain a first impression about the shape of the function that results in a prior with non-zero mean. This visually adaptive Bayesian (VAB) prior has a simple structure, intuitive interpretation, and is easy to implement. Skorohod topology is suggested as a more appropriate measure in signal recovering than …
Estimation Of Multiple Linear Functional Relationships, Amjad D. Al-Nasser
Estimation Of Multiple Linear Functional Relationships, Amjad D. Al-Nasser
Journal of Modern Applied Statistical Methods
This article deals with multiple linear functional relationships models. Two robust estimations procedure are proposed to estimate the model, based on Generalized Maximum Entropy and Partial Least Square. They are distribution free and do not rely (so much) on classical assumptions. The experiments showed that the GME approach outperforms the PLS in terms of mean squares of errors (MSE). Empirical examples are studied.
Validation Studies: Matters Of Dimensionality, Accuracy, And Parsimony With Predictive Discriminant Analysis And Factor Analysis, David A. Walker
Validation Studies: Matters Of Dimensionality, Accuracy, And Parsimony With Predictive Discriminant Analysis And Factor Analysis, David A. Walker
Journal of Modern Applied Statistical Methods
Two studies were used as examples that examined issues of dimensionality, accuracy, and parsimony in educational research via the use of predictive discriminant analysis and factor analysis. Using a two-group problem, study 1 looked at how accurately group membership could be predicted from subjects’ test scores. Study 2 looked at the dimensionality structure of an instrument and if it developed constructs that would measure theorized domains.
A Test-Retest Transition Matrix: A Modification Of Mcnemar’S Test, J. Wanzer Drane, W. Gregory Thatcher
A Test-Retest Transition Matrix: A Modification Of Mcnemar’S Test, J. Wanzer Drane, W. Gregory Thatcher
Journal of Modern Applied Statistical Methods
McNemar introduced what is known today as a test for symmetry in a two by two contingency tables. The logic of the test is based on a sample of matched pairs with a dichotomous response. In our example, the sample consists of the scores before and after an education program and the responses before and after the program. Each pair of scores is from only one person. The pretest divides the group of responders according to their answers to a dichotomous question. The posttest divides the two groups into two groups of like labels. The result is a two by …
Jmasm11: Comparing Two Small Binomial Proportions, James F. Reed Iii
Jmasm11: Comparing Two Small Binomial Proportions, James F. Reed Iii
Journal of Modern Applied Statistical Methods
A large volume of research has focused on comparing the difference between two small binomial proportions. Statisticians recognize that Fisher’s Exact test and Yates chi-square test are excessively conservative. Likewise, many statisticians feel that Pearson’s Chi-square or the likelihood statistic may be inappropriate for small samples. Viable alternatives exist.
On The Reporting Of Reliability In Content Analysis, Patric R. Spence
On The Reporting Of Reliability In Content Analysis, Patric R. Spence
Journal of Modern Applied Statistical Methods
This article explores one type of misreporting of reliability that has been seen in recent conference papers and articles using the method of content analysis. The reporting of reliability is central to the validity of claims made using this method. A brief overview of content analysis is offered, followed by the exploration of one type of misreporting of reliability. Suggestions are offered to address the problem.
Stratified Extreme Ranked Set Sample With Application To Ratio Estimators, Hani M. Samawai, Laith J. Saeid
Stratified Extreme Ranked Set Sample With Application To Ratio Estimators, Hani M. Samawai, Laith J. Saeid
Journal of Modern Applied Statistical Methods
Stratified extreme ranked set sample (SERSS) is introduced. The performance of the combined and separate ratio estimates using SERSS is investigated. Theoretical and simulation study are presented. Results indicate that using SERSS for estimating the ratios is more efficient than using stratified simple random sample (SSRS) and simple random sample (SRS). In some cases it is more efficient than ranked set sample (RSS) and stratified ranked set sample (SRSS), when the underlying distribution is symmetric. An application to real data on the bilirubin level in jaundice babies is introduced to illustrate the method.
Jmasm10: A Fortran Routine For Sieve Bootstrap Prediction Intervals, Andrés M. Alonso
Jmasm10: A Fortran Routine For Sieve Bootstrap Prediction Intervals, Andrés M. Alonso
Journal of Modern Applied Statistical Methods
A Fortran routine for constructing nonparametric prediction intervals for a general class of linear processes is described. The approach uses the sieve bootstrap procedure of Bühlmann (1997) based on residual resampling from an autoregressive approximation to the given process.
Accurate Binary Decisions For Assessing Coronary Artery Disease, Mehmet Ali Cengiz
Accurate Binary Decisions For Assessing Coronary Artery Disease, Mehmet Ali Cengiz
Journal of Modern Applied Statistical Methods
Generalized linear models offer convenient and highly applicable tools for modeling and predicting the behavior of random variables in terms of observable factors and covariates. This paper investigates applications of a special case of generalized linear model to improve the accuracy of predictions and decisions adopting Bayesian methods, in the specific context of assessing coronary artery disease. The basic model is developed for this application using binary response. The results clearly demonstrate the potential advantages offered by this approach.
Teaching Random Assignment: Do You Believe It Works?, Shlomo S. Sawilowsky
Teaching Random Assignment: Do You Believe It Works?, Shlomo S. Sawilowsky
Journal of Modern Applied Statistical Methods
Textbook authors admonish students to check on the comparability of two randomly assigned groups by conducting statistical tests on pretest means to determine if randomization worked. A Monte Carlo study was conducted on a sample of n = 2 per group, where each participant’s personality profile was represented by 7,500 randomly selected and assigned scores. Independent samples t tests were conducted and the results demonstrated that random assignment was successful in equating the two groups on 7,467 variables. The students’ focus is redirected from the ability of random assignment to create comparable groups to the testing of the claims of …
A Comparison Of Bayesian And Frequentist Statistics As Applied In A Simple Repeated Measures Example, Jan Perkins, Daniel Wang
A Comparison Of Bayesian And Frequentist Statistics As Applied In A Simple Repeated Measures Example, Jan Perkins, Daniel Wang
Journal of Modern Applied Statistical Methods
Clinicians see Bayesian and frequentist analysis in published research papers, and need a basic understanding of both. A repeated measures data set was analyzed using both approaches. Assumptions underlying each method and conclusions reached were contrasted. The Bayesian approach is a viable alternative to frequentist statistical analysis for many clinical projects.
Model Comparisons Using Information Measures, C. Mitchell Dayton
Model Comparisons Using Information Measures, C. Mitchell Dayton
Journal of Modern Applied Statistical Methods
Methodologists have criticized the use of significance tests in the behavioral sciences but have failed to provide alternative data analysis strategies that appeal to applied researchers. For purposes of comparing alternate models for data, information-theoretic measures such as Akaike AIC have advantages in comparison with significance tests. Model-selection procedures based on a min(AIC) strategy, for example, are holistic rather than dependent upon a series of sometimes contradictory binary (accept/reject) decisions.
Fortune Cookies, Measurement Error, And Experimental Design, Greogry R. Hancock
Fortune Cookies, Measurement Error, And Experimental Design, Greogry R. Hancock
Journal of Modern Applied Statistical Methods
This article pertains to the theoretical and practical detriments of measurement error in traditional univariate and multivariate experimental design, and points toward modern methods that facilitate greater accuracy in effect size estimates and power in hypothesis testing.
A Comparison Of Equivalence Testing In Combination With Hypothesis Testing And Effect Sizes, Christopher J. Mecklin
A Comparison Of Equivalence Testing In Combination With Hypothesis Testing And Effect Sizes, Christopher J. Mecklin
Journal of Modern Applied Statistical Methods
Equivalence testing, an alternative to testing for statistical significance, is little used in educational research. Equivalence testing is useful in situations where the researcher wishes to show that two means are not significantly different. A simulation study assessed the relationships between effect size, sample size, statistical significance, and statistical equivalence.
Approximate Bayesian Confidence Intervals For The Variance Of A Gaussian Distribution, Vincent A. R. Camara
Approximate Bayesian Confidence Intervals For The Variance Of A Gaussian Distribution, Vincent A. R. Camara
Journal of Modern Applied Statistical Methods
The aim of the present study is to obtain and compare confidence intervals for the variance of a Gaussian distribution. Considering respectively the square error and the Higgins-Tsokos loss functions, approximate Bayesian confidence intervals for the variance of a normal population are derived. Using normal data and SAS software, the obtained approximate Bayesian confidence intervals will then be compared to the ones obtained with the well known classical method. The Bayesian approach relies only on the observations. It is shown that the proposed approximate Bayesian approach relies only on the observations. The classical method, that uses the Chi-square statistic, does …
Using Zero-Inflated Count Regression Models To Estimate The Fertility Of U. S. Women, Dudley L. Poston Jr., Sherry L. Mckibben
Using Zero-Inflated Count Regression Models To Estimate The Fertility Of U. S. Women, Dudley L. Poston Jr., Sherry L. Mckibben
Journal of Modern Applied Statistical Methods
In the modeling of count variables there is sometimes a preponderance of zero counts. This article concerns the estimation of Poisson regression models (PRM) and negative binomial regression models (NBRM) to predict the average number of children ever born (CEB) to women in the U.S. The PRM and NBRM will often under-predict zeros because they do not consider zero counts of women who are not trying to have children. The fertility of U.S. white and Mexican-origin women show that zero-inflated Poisson (ZIP) and zero-inflated negative binomial (ZINB) models perform better in many respects than the Poisson and negative binomial models. …
Test Of Homogeneity For Umbrella Alternatives In Dose-Response Relationship For Poisson Variables, Chengjie Xiong, Yan Yan, Ming Ji
Test Of Homogeneity For Umbrella Alternatives In Dose-Response Relationship For Poisson Variables, Chengjie Xiong, Yan Yan, Ming Ji
Journal of Modern Applied Statistical Methods
This article concerns the testing and estimation of a dose-response effect in medical studies. We study the statistical test of homogeneity against umbrella alternatives in a sequence of Poisson distributions associated with an ordered dose variable. We propose a test similar to Cochran-Armitage’s trend test and study the asymptotic null distribution and the power of the test. We also propose an estimator to the vertex point when the umbrella pattern is confirmed and study the performance of the estimator. A real data set pertaining to the number of visible revertant colonies associated with different doses of test agents in an …
Alphabet Letter Recognition And Emergent Literacy Abilities Of Rising Kindergarten Children Living In Low-Income Families, Stephanie Wehry
Alphabet Letter Recognition And Emergent Literacy Abilities Of Rising Kindergarten Children Living In Low-Income Families, Stephanie Wehry
Journal of Modern Applied Statistical Methods
Alphabet letter recognition item responses from 1,299 rising kindergarten children from low-income families were used to determine the dimensionality of letter recognition ability. The rising kindergarteners were enrolled in preschool classrooms implementing a research-based early literary curriculum. Item responses from the TERA-3 subtests were also analyzed. Results indicated alphabet letter recognition was unitary. The ability of boys and younger children was less than girls and older children. Child-level letter recognition was highly associated with TERA-3 measures of letter knowledge and conventions of print. Classroom-level mean letter recognition ability accounted for most of variance in classroom mean TERA-3 scores.