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Articles 481 - 510 of 2316

Full-Text Articles in Physical Sciences and Mathematics

'Parallel Universe' Or 'Proven Future'? The Language Of Dependent Means T-Test Interpretations, Anthony M. Gould, Jean-Etienne Joullié Dec 2017

'Parallel Universe' Or 'Proven Future'? The Language Of Dependent Means T-Test Interpretations, Anthony M. Gould, Jean-Etienne Joullié

Journal of Modern Applied Statistical Methods

Of the three kinds of two-mean comparisons which judge a test statistic against a critical value taken from a Student t-distribution, one – the repeated measures or dependent-means application – is distinctive because it is meant to assess the value of a parameter which is not part of the natural order. This absence forces a choice between two interpretations of a significant test result and the meaning of the test hypothesis. The parallel universe view advances a conditional, backward-looking conclusion. The more practical proven future interpretation is a non-conditional proposition about what will happen if an intervention is (now) applied …

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Unit Root Test For Panel Data Ar(1) Time Series Model With Linear Time Trend And Augmentation Term: A Bayesian Approach, Jitendra Kumar, Anoop Chaturvedi, Umme Afifa, Shafat Yousuf, Saurabh Kumar Dec 2017

Unit Root Test For Panel Data Ar(1) Time Series Model With Linear Time Trend And Augmentation Term: A Bayesian Approach, Jitendra Kumar, Anoop Chaturvedi, Umme Afifa, Shafat Yousuf, Saurabh Kumar

Journal of Modern Applied Statistical Methods

The univariate time series models, in the case of unit root hypothesis, are more biased towards the acceptance of the Unit Root Hypothesis especially in a short time span. However, the panel data time series model is more appropriate in such situation. The Bayesian analysis of unit root testing for a panel data time series model is considered. An autoregressive panel data AR(1) model with linear time trend and augmentation term has been considered and derived the posterior odds ratio for testing the presence of unit root hypothesis under appropriate prior assumptions. A simulation study and real data analysis are …

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End Matter, Jmasm Editors Dec 2017

End Matter, Jmasm Editors

Journal of Modern Applied Statistical Methods

.

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Characterizations Of Distributions By Expected Values Of Lower Record Statistics With Spacing, M. Faizan, Ziaul Haque, M. A. Ansari Dec 2017

Characterizations Of Distributions By Expected Values Of Lower Record Statistics With Spacing, M. Faizan, Ziaul Haque, M. A. Ansari

Journal of Modern Applied Statistical Methods

The characterizations of a certain class of probability distributions are established through conditional expectation of lower record values when the conditioned record value may not be the adjacent one. Some of its important deductions are also discussed.

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Using Pratt's Importance Measures In Confirmatory Factor Analyses, Amrey D. Wu, Bruno D. Zumbo Dec 2017

Using Pratt's Importance Measures In Confirmatory Factor Analyses, Amrey D. Wu, Bruno D. Zumbo

Journal of Modern Applied Statistical Methods

When running a confirmatory factor analysis (CFA), users specify and interpret the pattern (loading) matrix. It has been recommended that the structure coefficients, indicating the factors’ correlation with the observed indicators, should also be reported when the factors are correlated (Graham, Guthrie, & Thompson, 2003; Thompson, 1997). The aims of this article are: (1) to note the structure coefficient should be interpreted with caution if the factors are specified to correlate. Because the structure coefficient is a zero-order correlation, it may be partially or entirely a reflection of factor correlations. This is elucidated by the matrix algebra of the structure …

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A Double Ewma Control Chart For The Individuals Based On A Linear Prediction, Rafael Perez Abreu, Jay R. Schaffer Dec 2017

A Double Ewma Control Chart For The Individuals Based On A Linear Prediction, Rafael Perez Abreu, Jay R. Schaffer

Journal of Modern Applied Statistical Methods

Industrial process use single and double Exponential Weighted Moving Average control charts to detect small shifts in it. Occasionally there is a need to detect small trends instead of shifts, but the effectiveness to detect small trends. A new control chart is proposed to detect a small drift.

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Study Evaluating The Alterations Caused In An Exploratory Factor Analysis When Multivariate Normal Data Is Dichotomized, Rosilei S. Novak, Jair M. Marques Dec 2017

Study Evaluating The Alterations Caused In An Exploratory Factor Analysis When Multivariate Normal Data Is Dichotomized, Rosilei S. Novak, Jair M. Marques

Journal of Modern Applied Statistical Methods

The relationships resulting from the dichotomization of multivariate normal data is a question that causes concern when using exploratory factor analysis. The relationships in an exploratory factor analysis are examined when multivariate normal data, generated by Monte Carlo methods, is dichotomized.

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Power And Sample Size Estimation For Nonparametric Composite Endpoints: Practical Implementation Using Data Simulations, Paul M. Brown, Justin A. Ezekowitz Dec 2017

Power And Sample Size Estimation For Nonparametric Composite Endpoints: Practical Implementation Using Data Simulations, Paul M. Brown, Justin A. Ezekowitz

Journal of Modern Applied Statistical Methods

Composite endpoints are a popular outcome in controlled studies. However, the required sample size is not easily obtained due to the assortment of outcomes, correlations between them and the way in which the composite is constructed. Data simulations are required. A macro is developed that enables sample size and power estimation.

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The Regression Smoother Lowess: A Confidence Band That Allows Heteroscedasticity And Has Some Specified Simultaneous Probability Coverage, Rand Wilcox Dec 2017

The Regression Smoother Lowess: A Confidence Band That Allows Heteroscedasticity And Has Some Specified Simultaneous Probability Coverage, Rand Wilcox

Journal of Modern Applied Statistical Methods

Many nonparametric regression estimators (smoothers) have been proposed that provide a more flexible method for estimating the true regression line compared to using some of the more obvious parametric models. A basic goal when using any smoother is computing a confidence band for the true regression line. Let M(Y|X) be some conditional measure of location associated with the random variable Y, given X and let x be some specific value of the covariate. When using the LOWESS estimator, an extant method that assumes homoscedasticity can be used to compute a confidence interval for M(Y|X = x). A trivial way of …

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Robust Measures Of Variable Importance For Multivariate Group Designs, Tolulope T. Sajobi, Lisa M. Lix Dec 2017

Robust Measures Of Variable Importance For Multivariate Group Designs, Tolulope T. Sajobi, Lisa M. Lix

Journal of Modern Applied Statistical Methods

Variable importance measures based on discriminant analysis and multivariate analysis of variance are useful for identifying variables that discriminate between two groups in multivariate group designs. Variable importance measures are developed based on trimmed and Winsorized estimators for describing group differences in multivariate non-normal populations.

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Effectively Comparing Differences In Proportions, Lonnie Turpin Jr. Dec 2017

Effectively Comparing Differences In Proportions, Lonnie Turpin Jr.

Journal of Modern Applied Statistical Methods

A single framework of developing and implementing tests about proportions is outlined. It avoids some of the pitfalls of methods commonly put forward in an introductory data analysis course.

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Missing Data In Longitudinal Surveys: A Comparison Of Performance Of Modern Techniques, Paola Zaninotto, Amanda Sacker Dec 2017

Missing Data In Longitudinal Surveys: A Comparison Of Performance Of Modern Techniques, Paola Zaninotto, Amanda Sacker

Journal of Modern Applied Statistical Methods

Using a simulation study, the performance of complete case analysis, full information maximum likelihood, multivariate normal imputation, multiple imputation by chained equations and two-fold fully conditional specification to handle missing data were compared in longitudinal surveys with continuous and binary outcomes, missing covariates, and an interaction term.

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Around Gamma Lindley Distribution, Hamouda Messaadia, Halim Zeghdoudi Dec 2017

Around Gamma Lindley Distribution, Hamouda Messaadia, Halim Zeghdoudi

Journal of Modern Applied Statistical Methods

Some remarks and correction on a new distribution, Gamma Lindley, of which the Lindley distribution is a particular case, are given pertaining to its parameter space.

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The Impact Of Inappropriate Modeling Of Cross-Classified Data Structures On Random-Slope Models, Feifei Ye, Laura Daniel Dec 2017

The Impact Of Inappropriate Modeling Of Cross-Classified Data Structures On Random-Slope Models, Feifei Ye, Laura Daniel

Journal of Modern Applied Statistical Methods

Previous studies that explored the impact of misspecification of cross-classified data structure as strictly hierarchical are limited to random intercept models. This study examined the effects of misspecification of a two-level, cross-classified, random effect model (CCREM) where both the level-1 intercept and slope were allowed to vary randomly. Results suggest that ignoring one of the crossed factors produced considerably underestimated standard errors for: 1) the regression coefficients of the level-1 predictor; 2) the inappropriately modeled predictor associated with the misspecified crossed factor; and 3) and their interaction. This misspecification also resulted in a significant inflation of the level-1 residual variances …

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Experimental Design And Data Analysis In Computer Simulation Studies In The Behavioral Sciences, Michael Harwell, Nidhi Kohli, Yadira Peralta Dec 2017

Experimental Design And Data Analysis In Computer Simulation Studies In The Behavioral Sciences, Michael Harwell, Nidhi Kohli, Yadira Peralta

Journal of Modern Applied Statistical Methods

Treating computer simulation studies as statistical sampling experiments subject to established principles of experimental design and data analysis should further enhance their ability to inform statistical practice and a program of statistical research. Latin hypercube designs to enhance generalizability and meta-analytic methods to analyze simulation results are presented.

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On Variance Balanced Designs, Dilip Kumar Ghosh, Sangeeta Ahuja Dec 2017

On Variance Balanced Designs, Dilip Kumar Ghosh, Sangeeta Ahuja

Journal of Modern Applied Statistical Methods

Balanced incomplete block designs are not always possible to construct because of their parametric relations. In such a situation another balanced design, the variance balanced design, is required. This construction of binary, equal replicated variance balanced designs are discussed using the half fraction of the 2n factorial designs with smaller block sizes. This method was also extended to construct another variance balanced design by deleting the last block of the resulting variance balanced designs. Its efficiency factor compared with randomized block designs was compared and found to be highly efficient.

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Performance Evaluation Of Confidence Intervals For Ordinal Coefficient Alpha, Heather J. Turner, Prathiba Natesan, Robin K. Henson Dec 2017

Performance Evaluation Of Confidence Intervals For Ordinal Coefficient Alpha, Heather J. Turner, Prathiba Natesan, Robin K. Henson

Journal of Modern Applied Statistical Methods

The aim of this study was to investigate the performance of the Fisher, Feldt, Bonner, and Hakstian and Whalen (HW) confidence intervals methods for the non-parametric reliability estimate, ordinal alpha. All methods yielded unacceptably low coverage rates and potentially increased Type-I error rates.

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A Monte Carlo Study Of The Effects Of Variability And Outliers On The Linear Correlation Coefficient, Hussein Yousif Eledum Dec 2017

A Monte Carlo Study Of The Effects Of Variability And Outliers On The Linear Correlation Coefficient, Hussein Yousif Eledum

Journal of Modern Applied Statistical Methods

Monte Carlo simulations are used to investigate the effect of two factors, the amount of variability and an outlier, on the size of the Pearson correlation coefficient. Some simulation algorithms are developed, and two theorems for increasing or decreasing the amount of variability are suggested.

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Parameter Estimation In Weighted Rayleigh Distribution, M. Ajami, S. M. A. Jahanshahi Dec 2017

Parameter Estimation In Weighted Rayleigh Distribution, M. Ajami, S. M. A. Jahanshahi

Journal of Modern Applied Statistical Methods

A weighted model based on the Rayleigh distribution is proposed and the statistical and reliability properties of this model are presented. Some non-Bayesian and Bayesian methods are used to estimate the β parameter of proposed model. The Bayes estimators are obtained under the symmetric (squared error) and the asymmetric (linear exponential) loss functions using non-informative and reciprocal gamma priors. The performance of the estimators is assessed on the basis of their biases and relative risks under the two above-mentioned loss functions. A simulation study is constructed to evaluate the ability of considered estimation methods. The suitability of the proposed model …

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Jmasm 46: Algorithm For Comparison Of Robust Regression Methods In Multiple Linear Regression By Weighting Least Square Regression (Sas), Mohamad Shafiq, Wan Muhamad Amir, Nur Syabiha Zafakali Dec 2017

Jmasm 46: Algorithm For Comparison Of Robust Regression Methods In Multiple Linear Regression By Weighting Least Square Regression (Sas), Mohamad Shafiq, Wan Muhamad Amir, Nur Syabiha Zafakali

Journal of Modern Applied Statistical Methods

The aim of this study is to compare different robust regression methods in three main models of multiple linear regression and weighting multiple linear regression. An algorithm for weighting multiple linear regression by standard deviation and variance for combining different robust method is given in SAS along with an application.

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Bayesian Hypothesis Testing Of Two Normal Samples Using Bootstrap Prior Technique, Oyebayo Ridwan Olaniran, Waheed Babatunde Yahya Dec 2017

Bayesian Hypothesis Testing Of Two Normal Samples Using Bootstrap Prior Technique, Oyebayo Ridwan Olaniran, Waheed Babatunde Yahya

Journal of Modern Applied Statistical Methods

The most important ingredient in Bayesian analysis is prior or prior distribution. A new prior determination method was developed under the framework of parametric empirical Bayes using bootstrap technique. By way of example, Bayesian estimations of the parameters of a normal distribution with unknown mean and unknown variance conditions were considered, as well as its application in comparing the means of two independent normal samples with several scenarios. A Monte Carlo study was conducted to illustrate the proposed procedure in estimation and hypothesis testing. Results from Monte Carlo studies showed that the bootstrap prior proposed is more efficient than the …

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Reviews And Syntheses: On The Role Of Trees In Building And Plumbing The Critical Zone, Susan L. Brantley, David M. Eissenstat, Jill A. Marshall, Sarah E. Godsey, Zsuzsanna Balogh-Brunstad, Diana L. Karwan, Shirley A. Papuga, Joshua Roering, Todd E. Dawson, Jaivime Evaristo, Oliver Chadwick, Jeffrey J. Mcdonnell, Kathleen C. Weathers Nov 2017

Reviews And Syntheses: On The Role Of Trees In Building And Plumbing The Critical Zone, Susan L. Brantley, David M. Eissenstat, Jill A. Marshall, Sarah E. Godsey, Zsuzsanna Balogh-Brunstad, Diana L. Karwan, Shirley A. Papuga, Joshua Roering, Todd E. Dawson, Jaivime Evaristo, Oliver Chadwick, Jeffrey J. Mcdonnell, Kathleen C. Weathers

Environmental Science and Geology Faculty Research Publications

Trees, the most successful biological power plants on earth, build and plumb the critical zone (CZ) in ways that we do not yet understand. To encourage exploration of the character and implications of interactions between trees and soil in the CZ, we propose nine hypotheses that can be tested at diverse settings. The hypotheses are roughly divided into those about the architecture (building) and those about the water (plumbing) in the CZ, but the two functions are intertwined. Depending upon one’s disciplinary background, many of the nine hypotheses listed below may appear obviously true or obviously false. (1) Tree roots …

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Empirical Modeling Of Planetary Boundary Layer Dynamics Under Multiple Precipitation Scenarios Using A Two-Layer Soil Moisture Approach: An Example From A Semiarid Shrubland, Zulia Mayari Sanchez-Mejia, Shirley A. Papuga Nov 2017

Empirical Modeling Of Planetary Boundary Layer Dynamics Under Multiple Precipitation Scenarios Using A Two-Layer Soil Moisture Approach: An Example From A Semiarid Shrubland, Zulia Mayari Sanchez-Mejia, Shirley A. Papuga

Environmental Science and Geology Faculty Research Publications

In semiarid regions, where water resources are limited and precipitation dynamics are changing, understanding land surface-atmosphere interactions that regulate the coupled soil moistureprecipitation system is key for resource management and planning. We present a modeling approach to study soil moisture and albedo controls on planetary boundary layer height (PBLh). We used Santa Rita Creosote Ameriflux and Tucson Airport atmospheric sounding data to generate empirical relationships between soil moisture, albedo, and PBLh. Empirical relationships showed that ~50% of the variation in PBLh can be explained by soil moisture and albedo with additional knowledge gained by …

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Characteristics Of Deep Crustal Seismic Anisotropy From A Compilation Of Rock Elasticity Tensors And Their Expression In Receiver Functions, Sarah J. Brownlee, Vera Schulte-Pelkum, Anissha Raju, Kevin Mahan, Cailey Condit, Omero Felipe Orlandini Sep 2017

Characteristics Of Deep Crustal Seismic Anisotropy From A Compilation Of Rock Elasticity Tensors And Their Expression In Receiver Functions, Sarah J. Brownlee, Vera Schulte-Pelkum, Anissha Raju, Kevin Mahan, Cailey Condit, Omero Felipe Orlandini

Environmental Science and Geology Faculty Research Publications

Rocks in the continental crust are long lived and have the potential to record a wide span of tectonic history in rock fabric. Mapping rock fabric in situ at depth requires the application of seismic methods. Below depths of microcrack closure seismic anisotropy presumably reflects the shape and crystallographic preferred orientations influenced by deformation processes. Interpretation of seismic observables relevant for anisotropy requires assumptions on the symmetry and orientation of the bulk elastic tensor. We compare commonly made assumptions against a compilation of 95 bulk elastic tensors from laboratory measurements, including electron backscatter diffraction and ultrasound, on crustal rocks. The …

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Using Multiple Imputation To Address Missing Values Of Hierarchical Data, Yujia Zhang, Sara Crawford, Sheree Boulet, Michael Monsour, Bruce Cohen, Patricia Mckane, Karen Freeman May 2017

Using Multiple Imputation To Address Missing Values Of Hierarchical Data, Yujia Zhang, Sara Crawford, Sheree Boulet, Michael Monsour, Bruce Cohen, Patricia Mckane, Karen Freeman

Journal of Modern Applied Statistical Methods

Missing data may be a concern for data analysis. If it has a hierarchical or nested structure, the SUDAAN package can be used for multiple imputation. This is illustrated with birth certificate data that was linked to the Centers for Disease Control and Prevention’s National Assisted Reproductive Technology Surveillance System database. The Cox-Iannacchione weighted sequential hot deck method was used to conduct multiple imputation for missing/unknown values of covariates in a logistic model.

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Selection Of Statistical Software For Data Scientists And Teachers, Ceyhun Ozgur, Min Dou, Yang Li, Grace Rogers May 2017

Selection Of Statistical Software For Data Scientists And Teachers, Ceyhun Ozgur, Min Dou, Yang Li, Grace Rogers

Journal of Modern Applied Statistical Methods

The need for analysts with expertise in big data software is becoming more apparent in today’s society. Unfortunately, the demand for these analysts far exceeds the number available. A potential way to combat this shortage is to identify the software sought by employers and to align this with the software taught by universities. This paper will examine multiple data analysis software – Excel add-ins, SPSS, SAS, Minitab, and R – and it will outline the cost, training, statistical methods/tests/uses, and specific uses within industry for each of these software. It will further explain implications for universities and students.

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An Unbiased Estimator Of The Greatest Lower Bound, Nol Bendermacher May 2017

An Unbiased Estimator Of The Greatest Lower Bound, Nol Bendermacher

Journal of Modern Applied Statistical Methods

The greatest lower bound to the reliability of a test, based on a single administration, is the Greatest Lower Bound (GLB). However the estimate is seriously biased. An algorithm is described that corrects this bias.

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Monte Carlo Study Of Some Classification-Based Ridge Parameter Estimators, Adewale Folaranmi Lukman, Kayode Ayinde, Adegoke S. Ajiboye May 2017

Monte Carlo Study Of Some Classification-Based Ridge Parameter Estimators, Adewale Folaranmi Lukman, Kayode Ayinde, Adegoke S. Ajiboye

Journal of Modern Applied Statistical Methods

Ridge estimator in linear regression model requires a ridge parameter, K, of which many have been proposed. In this study, estimators based on Dorugade (2014) and Adnan et al. (2014) were classified into different forms and various types using the idea of Lukman and Ayinde (2015). Some new ridge estimators were proposed. Results shows that the proposed estimators based on Adnan et al. (2014) perform generally better than the existing ones.

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Multivariate Multilevel Modeling Of Age Related Diseases, Kapuruge N. O. Ranathunga, Roshini Sooriyarachchi May 2017

Multivariate Multilevel Modeling Of Age Related Diseases, Kapuruge N. O. Ranathunga, Roshini Sooriyarachchi

Journal of Modern Applied Statistical Methods

The emerging role of modeling multivariate multilevel data in the context of analyzing the risk factors are examined for the severity of cardiovascular disease diabetes, and chronic respiratory conditions. The modeling phase results leads to some important interaction terms between blood glucose, blood pressure, obesity, smoking and alcohol to the mortality rates.

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Analysis Of Robust Parameter Designs, Tak K. Mak, Fassil Nebebe May 2017

Analysis Of Robust Parameter Designs, Tak K. Mak, Fassil Nebebe

Journal of Modern Applied Statistical Methods

The analysis of robust parameter design is discussed via a model incorporating mean-variance relationship which, when ignored as in the classical regression approach, can be problematic. The model is also capable of alleviating the difficulties of the regression approach in the search of the minimum variance occurring region.

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