Open Access. Powered by Scholars. Published by Universities.®

Statistics and Probability Commons™

Open Access. Powered by Scholars. Published by Universities.®

2013

Discipline
Institution
Keyword
Publication
Publication Type
File Type

Articles 61 - 90 of 555

Full-Text Articles in Statistics and Probability

The Impact Of Continuity Violation On Anova And Alternative Methods, Björn Lantz Nov 2013

The Impact Of Continuity Violation On Anova And Alternative Methods, Björn Lantz

Journal of Modern Applied Statistical Methods

The normality assumption behind ANOVA and other parametric methods implies that response variables are measured on continuous scales. A simulation approach is used to explore the impact of continuity violation on the performance of statistical methods commonly used by applied researchers to compare locations across several groups.

Go to article

The Single-Case Data Analysis Package: Analysing Single-Case Experiments With R Software, Isis Bulté, Patrick Onghena Nov 2013

The Single-Case Data Analysis Package: Analysing Single-Case Experiments With R Software, Isis Bulté, Patrick Onghena

Journal of Modern Applied Statistical Methods

The RcmdrPlugin.SCDA plug-in package is discussed. It integrates three R packages in the R commander interface: SCVA (for Single-Case Visual Analysis), SCRT (for Single-Case Randomization Tests), and SCMA (for Single-Case Meta-Analysis). This way the plug-in package covers three important steps in the analysis of single-case data.

Go to article

A Comparison Between Biased And Unbiased Estimators In Ordinary Least Squares Regression, Ghadban Khalaf Nov 2013

A Comparison Between Biased And Unbiased Estimators In Ordinary Least Squares Regression, Ghadban Khalaf

Journal of Modern Applied Statistical Methods

During the past years, different kinds of estimators have been proposed as alternatives to the Ordinary Least Squares (OLS) estimator for the estimation of the regression coefficients in the presence of multicollinearity. In the general linear regression model, Y = Xβ + e, it is known that multicollinearity makes statistical inference difficult and may even seriously distort the inference. Ridge regression, as viewed here, defines a class of estimators of β indexed by a scalar parameter k. Two methods of specifying k are proposed and evaluated in terms of Mean Square Error (MSE) by …

Go to article

Discriminating Between Generalized Exponential Distribution And Some Life Test Models Based On Population Quantiles, B. Srinivasa Rao, R. R. L Kantam Nov 2013

Discriminating Between Generalized Exponential Distribution And Some Life Test Models Based On Population Quantiles, B. Srinivasa Rao, R. R. L Kantam

Journal of Modern Applied Statistical Methods

A test statistic based on population quantiles using sample order statistics is suggested. The quantiles of the test statistics are evaluated for generalized exponential distribution. Similar test statistic based on moments of sample order statistic is referred and the proposed test formula is compared with it. Between the pairs of the above models it is established that the test formula proposed by us is more effective and useful than the formula based on the moments of order statistics as developed by Sultan (2007).

Go to article

Comparison Of Parameters Of Lognormal Distribution Based On The Classical And Posterior Estimates, Raja Sultan, S. P. Ahmad Nov 2013

Comparison Of Parameters Of Lognormal Distribution Based On The Classical And Posterior Estimates, Raja Sultan, S. P. Ahmad

Journal of Modern Applied Statistical Methods

Lognormal distribution is widely used in scientific field, such as agricultural, entomological, biology etc. If a variable can be thought as the multiplicative product of some positive independent random variables, then it could be modelled as lognormal. In this study, maximum likelihood estimates and posterior estimates of the parameters of lognormal distribution are obtained and using these estimates we calculate the point estimates of mean and variance for making comparisons.

Go to article

On Bayesian Estimation And Predictions For Two-Component Mixture Of The Gompertz Distribution, Navid Feroze, Muhammad Aslam Nov 2013

On Bayesian Estimation And Predictions For Two-Component Mixture Of The Gompertz Distribution, Navid Feroze, Muhammad Aslam

Journal of Modern Applied Statistical Methods

Mixtures models have received sizeable attention from analysts in the recent years. Some work on Bayesian estimation of the parameters of mixture models have appeared. However, the were restricted to the Bayes point estimation The methodology for the Bayesian interval estimation of the parameters for said models is still to be explored. This paper proposes the posterior interval estimation (along with point estimation) for the parameters of a two-component mixture of the Gompertz distribution. The posterior predictive intervals are also derived and evaluated. Different informative and non-informative priors are assumed under a couple of loss functions for the posterior analysis. …

Go to article

A Generalized Class Of Estimators For Finite Population Variance In Presence Of Measurement Errors, Prayas Sharma, Rajesh Singh Nov 2013

A Generalized Class Of Estimators For Finite Population Variance In Presence Of Measurement Errors, Prayas Sharma, Rajesh Singh

Journal of Modern Applied Statistical Methods

The problem of estimating the population variance is presented using auxiliary information in the presence of measurement errors. The estimators in this article use auxiliary information to improve efficiency and assume that measurement error is present both in study and auxiliary variable. A numerical study is carried out to compare the performance of the proposed estimator with other estimators and the variance per unit estimator in the presence of measurement errors.

Go to article

Robust Regression Estimators When There Are Tied Values, Rand R. Wilcox, Florence Clark Nov 2013

Robust Regression Estimators When There Are Tied Values, Rand R. Wilcox, Florence Clark

Journal of Modern Applied Statistical Methods

It is well known that when using the ordinary least squares regression estimator, outliers among the dependent variable can result in relatively poor power. Many robust regression estimators have been derived that address this problem, but the bulk of the results assume that the dependent variable is continuous. It is demonstrated that when there are tied values, several robust regression estimators can perform poorly in terms of controlling the Type I error probability, even with a large sample size. The presence of tied values does not necessarily mean that they perform poorly, but there is the issue of whether there …

Go to article

Testing The Assumption Of Non-Differential Misclassification In Case-Control Studies, Tze-San Lee, Qin Hui Nov 2013

Testing The Assumption Of Non-Differential Misclassification In Case-Control Studies, Tze-San Lee, Qin Hui

Journal of Modern Applied Statistical Methods

One of the not yet solved issues regarding the misclassification in case-control studies is whether the misclassification rates are the same for both cases and controls. Currently, a common practice is to assume that the rates are the same, that is, the non-differential misclassification assumption. However, it has been suspected that this assumption may not be valid in practical applications. Unfortunately, no test is available so far to test the validity of the non-differential misclassification assumption. A method is presented to test the validity of non-differential misclassification assumption in case-control studies with 2 × 2 tables when validation data are …

Go to article

Ordered Logit Regression Modeling Of The Self-Rated Health In Hawai‘I, With Comparisons To The Ols Model, Hosik Min Nov 2013

Ordered Logit Regression Modeling Of The Self-Rated Health In Hawai‘I, With Comparisons To The Ols Model, Hosik Min

Journal of Modern Applied Statistical Methods

Despite the ordinal nature of Self-Rated Health (SRH) variable, logistic regression models or regression models have been used without adequate justification for these applications. It is shown that ordered-logit regression model is the appropriate statistical strategy to estimate SRH, whereas the Ordinary LeastSquares model leads to biased conclusions.

Go to article

Approximation Multivariate Distribution Of Main Indices Of Tehran Stock Exchange With Pair-Copula, G. Parham, A. Daneshkhah, O. Chatrabgoun Nov 2013

Approximation Multivariate Distribution Of Main Indices Of Tehran Stock Exchange With Pair-Copula, G. Parham, A. Daneshkhah, O. Chatrabgoun

Journal of Modern Applied Statistical Methods

The multivariate distribution of five main indices of Tehran stock exchange is approximated using a pair-copula model. A vine graphical model is used to produce an n-dimensional copula. This is accomplished using a flexible copula called a minimum information (MI) copula as a part of pair-copula construction. Obtained results show that the achieved model has a good level of approximation.

Go to article

Molecular Detection Of Culture-Confirmed Bacterial Bloodstream Infections With Limited Enrichment Time, Miranda S. Moore, Chase D. Mccann, Jeanne Jordan Nov 2013

Molecular Detection Of Culture-Confirmed Bacterial Bloodstream Infections With Limited Enrichment Time, Miranda S. Moore, Chase D. Mccann, Jeanne Jordan

Epidemiology Faculty Publications

Conventional blood culturing using automated instrumentation with phenotypic identification requires a significant amount of time to generate results. This study investigated the speed and accuracy of results generated using PCR and pyrosequencing compared to the time required to obtain Gram stain results and final culture identification for cases of culture-confirmed bloodstream infections. Research and physician-ordered blood cultures were drawn concurrently. Aliquots of the incubating research blood culture fluid were removed hourly between 5 and 8 h, at 24 h, and again at 5 days. DNA was extracted from these 6 time point aliquots and analyzed by PCR and pyrosequencing for …

Go to article

Diabetes Care Management During Cancer Treatment, Gregory R. Harper Md, Phd, Janelle M. Sharma Dnp, Crnp, Cara Habeck Rn, Cde, Cathy A. Coyne Phd, Mph, Hope Kincaid Mph, Cph, Roya Hamadani Mph, Ada M. Rivera Mba, Cph, Gretchen Perilli Md, Nicole R. Sully Do Nov 2013

Diabetes Care Management During Cancer Treatment, Gregory R. Harper Md, Phd, Janelle M. Sharma Dnp, Crnp, Cara Habeck Rn, Cde, Cathy A. Coyne Phd, Mph, Hope Kincaid Mph, Cph, Roya Hamadani Mph, Ada M. Rivera Mba, Cph, Gretchen Perilli Md, Nicole R. Sully Do

Department of Family Medicine

No abstract provided.

Go to article

Generalized Modified Ratio Estimator For Estimation Of Finite Population Mean, Jambulingam Subramani Nov 2013

Generalized Modified Ratio Estimator For Estimation Of Finite Population Mean, Jambulingam Subramani

Journal of Modern Applied Statistical Methods

A generalized modified ratio estimator is proposed for estimating the population mean using the known population parameters. It is shown that the simple random sampling without replacement sample mean, the usual ratio estimator, the linear regression estimator and all the existing modified ratio estimators are the particular cases of the proposed estimator. The bias and the mean squared error of the proposed estimator are derived and are compared with that of existing estimators. The conditions for which the proposed estimator performs better than the existing estimators are also derived. The performance of the proposed estimator is assessed with that of …

Go to article

Test For Intraclass Correlation Coefficient Under Unequal Family Sizes, Madhusudan Bhandary, Koji Fujiwara Nov 2013

Test For Intraclass Correlation Coefficient Under Unequal Family Sizes, Madhusudan Bhandary, Koji Fujiwara

Journal of Modern Applied Statistical Methods

Three tests are proposed based on F-distribution, Likelihood Ratio Test (LRT) and large sample Z-test for intraclass correlation coefficient under unequal family sizes based on a single multinormal sample. It has been found that the test based on F-distribution consistently and reliably produces results superior to those of Likelihood Ratio Test (LRT) and large sample Z-test in terms of size for various combinations of intraclass correlation coefficient values. The power of this test based on F-distribution is competitive with the power of the LRT and the power of Z-test is slightly better than the powers of F-test and LRT when …

Go to article

Variables Sampling Plan For Correlated Data, J. R. Singh, R. Sankle, M. Ahmad Khanday Nov 2013

Variables Sampling Plan For Correlated Data, J. R. Singh, R. Sankle, M. Ahmad Khanday

Journal of Modern Applied Statistical Methods

The sampling plan for the mean for correlated data is studied. The Operating Characteristic (OC) of the variable sampling plan for mean for correlated data are calculated and compared with the OC of known σ case.

Go to article

Case-Control Studies With Jointly Misclassified Exposure And Confounding Variables, Tze-San Lee Nov 2013

Case-Control Studies With Jointly Misclassified Exposure And Confounding Variables, Tze-San Lee

Journal of Modern Applied Statistical Methods

The issue of 2 × 2 × 2 case-control studies is addressed when both exposure and confounding variables are jointly misclassified. Two scenarios are considered: the classification errors of exposure and confounding variables are independent or not independent. The bias-adjusted cell probability estimates which account for the misclassification bias are presented. The effect of misclassification on the measure of crude odds ratio either unstratified or stratified by the confounder, Mantel-Haenszel summary odds ratio, the confounding component in the crude odds ratio, the first and second order multiplicative interaction are assessed through the sensitivity analysis from using the data on the …

Go to article

How Good Is Best? Multivariate Case Of Ehrenberg-Weisberg Analysis Of Residual Errors In Competing Regressions, Stan Lipovetsky Nov 2013

How Good Is Best? Multivariate Case Of Ehrenberg-Weisberg Analysis Of Residual Errors In Competing Regressions, Stan Lipovetsky

Journal of Modern Applied Statistical Methods

A.S.C. Ehrenberg first noticed and S. Weisberg then formalized a property of pairwise regression to keep its quality almost at the same level of precision while the coefficients of the model could vary over a wide span of values. This paper generalizes the estimates of the percent change in the residual standard deviation to the case of competing multiple regressions. It shows that in contrast to the simple pairwise model, the coefficients of multiple regression can be changed over a wider range of the values including the opposite by signs coefficients. Consideration of these features facilitates better understanding the properties …

Go to article

Comparison Of Three Calculation Methods For A Bayesian Inference Of P(Π1 > Π2), Yohei Kawasaki, Asanao Shimokawa, Etsuo Miyaoka Nov 2013

Comparison Of Three Calculation Methods For A Bayesian Inference Of P(Π1 > Π2), Yohei Kawasaki, Asanao Shimokawa, Etsuo Miyaoka

Journal of Modern Applied Statistical Methods

In Bayesian inference, some researchers have examined the difference of binominal proportions using θ = P(π1 > π2 − Δ0|X1,X2), where Xi denote binomial random variable with parameter πi. An approximate method and the MCMC method are compared with an exact method for θ, and results of actual clinical trials using θ are presented.

Go to article

Parameter Estimations Based On Kumaraswamy Progressive Type Ii Censored Data With Random Removals, Navid Feroze, Ibrahim El-Batal Nov 2013

Parameter Estimations Based On Kumaraswamy Progressive Type Ii Censored Data With Random Removals, Navid Feroze, Ibrahim El-Batal

Journal of Modern Applied Statistical Methods

The estimation of two parameters of the Kumaraswamy distribution is considered under Type II progressive censoring with random removals, where the number of units removed at each failure time has a binomial distribution. The MLE was used to obtain the estimators of the unknown parameters, and the asymptotic variance - covariance matrix was also obtained. The formula to compute the expected test time was derived. A numerical study was carried out for different combinations of model parameters. Different censoring schemes were used for the estimation, and performance of these schemes was compared.

Go to article

Akaike Information Criterion To Select The Parametric Detection Function For Kernel Estimator Using Line Transect Data, Omar Eidous, Samar Al-Salman Nov 2013

Akaike Information Criterion To Select The Parametric Detection Function For Kernel Estimator Using Line Transect Data, Omar Eidous, Samar Al-Salman

Journal of Modern Applied Statistical Methods

Among different candidate parametric detection functions, it is suggested to use Akaike Information Criterion (AIC) to select the most appropriate one of them to fit line transect data. Four different detection functions are considered in this paper. Two of them are taken to satisfy the shoulder condition assumption and the other two estimators do not satisfy this condition. Once the appropriate detection function is determined, it also can be used to select the smoothing parameter of the nonparametric kernel estimator. For a wide range of target densities, a simulation results show the reasonable and good performances of the …

Go to article

Vol. 12, No. 2 (Full Issue), Jmasm Editors Nov 2013

Vol. 12, No. 2 (Full Issue), Jmasm Editors

Journal of Modern Applied Statistical Methods

No abstract provided.

Go to article

Innovationspotenzialanalyse Für Die Neuen Technologien Für Das Verwalten Und Analysieren Von Großen Datenmengen (Big Data Management), Volker Markl, Alexander Löser, Thomas Hoeren, Helmut Krcmar, Holmer Hemsen, Michael Schermann, Matthias Gottlieb, Christoph Buchmüller, Philip Uecker, Till Bitter Nov 2013

Innovationspotenzialanalyse Für Die Neuen Technologien Für Das Verwalten Und Analysieren Von Großen Datenmengen (Big Data Management), Volker Markl, Alexander Löser, Thomas Hoeren, Helmut Krcmar, Holmer Hemsen, Michael Schermann, Matthias Gottlieb, Christoph Buchmüller, Philip Uecker, Till Bitter

Faculty Book Gallery

Durch die Digitalisierung von Wirtschaft und Gesellschaft ist ein rasantes Anwachsen von Datenbeständen zu beobachten. In fast allen Unternehmenssowie Wissenschaftsbereichen werden bereits heute schon Unmengen an Daten erzeugt, deren Größe, Erfassungsgeschwindigkeit oder Heterogenität die Fähigkeiten gängiger Datenbanksoftwareprodukte zur Verwaltung und zur Analyse übersteigt. Dieses Phänomen, welches unter dem Schlagwort „Big Data“ popularisiert wurde, stellt eine große Chance für Unternehmen, Wissenschaft und Gesellschaft dar. Allerdings ergibt sich aufgrund der neuen Komplexität der Daten und Analysen eine Vielzahl an Herausforderungen technischer, wirtschaftlicher und rechtlicher Natur. Diese Studie analysiert die Chancen und Herausforderungen von Big Data insbesondere im Hinblick auf eine nachhaltige Wettbewerbsfä- …

Go to article

Approximate Techniques In Solving Optimal Camera Placement Problems, Jian Zhao, Ruriko Yoshida, Sen-Ching Samson Cheung, David Haws Nov 2013

Approximate Techniques In Solving Optimal Camera Placement Problems, Jian Zhao, Ruriko Yoshida, Sen-Ching Samson Cheung, David Haws

Statistics Faculty Publications

While the theoretical foundation of the optimal camera placement problem has been studied for decades, its practical implementation has recently attracted significant research interest due to the increasing popularity of visual sensor networks. The most flexible formulation of finding the optimal camera placement is based on a binary integer programming (BIP) problem. Despite the flexibility, most of the resulting BIP problems are NP-hard and any such formulations of reasonable size are not amenable to exact solutions. There exists a myriad of approximate algorithms for BIP problems, but their applications, efficiency, and scalability in solving camera placement are poorly understood. Thus, …

Go to article

Constructing Confidence Intervals For Effect Sizes In Anova Designs, Li-Ting Chen, Chao-Ying Joanne Peng Nov 2013

Constructing Confidence Intervals For Effect Sizes In Anova Designs, Li-Ting Chen, Chao-Ying Joanne Peng

Journal of Modern Applied Statistical Methods

A confidence interval for effect sizes provides a range of plausible population effect sizes (ES) that are consistent with data. This article defines an ES as a standardized linear contrast of means. The noncentral method, Bonett’s method, and the bias-corrected and accelerated bootstrap method are illustrated for constructing the confidence interval for such an effect size. Results obtained from the three methods are discussed and interpretations of results are offered.

Go to article

Bayesian Joinpoint Regression Model For Childhood Brain Cancer Mortality, Ram C. Kafle, Netra Khanal, Chris P. Tsokos Nov 2013

Bayesian Joinpoint Regression Model For Childhood Brain Cancer Mortality, Ram C. Kafle, Netra Khanal, Chris P. Tsokos

Journal of Modern Applied Statistical Methods

The Bayesian approach of joinpoint regression is widely used to analyze trends in cancer mortality, incidence and survival data. The Bayesian joinpoint regression model was used to study the childhood brain cancer mortality rate and its average percentage change (APC) per year. Annual observed mortality counts of children ages 0-19 from 1969-2009 obtained from Surveillance Epidemiology and End Results (SEER) database of National Cancer Institute (NCI) were analyzed. It was assumed that death counts are probabilistically characterized by the Poisson distribution and they were modeled using log link function. Results were compared with the mortality trend obtained using joinpoint software …

Go to article

On Comparison Of Exponential And Hyperbolic Exponential Growth Models In Height/Diameter Increment Of Pines (Pinus Caribaea), S. O. Oyamakin, A. U. Chukwu, T. A. Bamiduro Nov 2013

On Comparison Of Exponential And Hyperbolic Exponential Growth Models In Height/Diameter Increment Of Pines (Pinus Caribaea), S. O. Oyamakin, A. U. Chukwu, T. A. Bamiduro

Journal of Modern Applied Statistical Methods

A new tree growth model called the hyperbolic exponential nonlinear growth model is suggested. Its ability in model prediction was compared with the Malthus or exponential growth model an approach which mimicked the natural variability of heights/diameter increment with respect to age and therefore provides more realistic height/diameter predictions as demonstrated by the results of the Kolmogorov Smirnov test and Shapiro-Wilk test. The mean function of top height/Dbh over age using the two models under study predicted closely the observed values of top height/Dbh in the Hyperbolic exponential nonlinear growth models better than the ordinary exponential growth model without violating …

Go to article

Progressive Reliability Method And Its Application To Offshore Mooring Systems, Mir Emad Mousavi, Paolo Gardoni, Mehdi Maadooliat Nov 2013

Progressive Reliability Method And Its Application To Offshore Mooring Systems, Mir Emad Mousavi, Paolo Gardoni, Mehdi Maadooliat

Mathematics, Statistics and Computer Science Faculty Research and Publications

Assessing the reliability of complex systems (e.g. structures) is essential for a reliability-based optimal design that balances safety and costs of such systems. This paper proposes the Progressive Reliability Method (PRM) for the quantification of the reliability of complex systems. The proposed method is a closed-form solution for calculating the probability of failure. The new method is flexible to the definition of “failure” (i.e., can consider serviceability and ultimate-strength failures) and uses the rules of probability theory to estimate the failure probability of the system or its components. The method is first discussed in general and then illustrated in two …

Go to article

Assessing Protein Conformational Sampling Methods Based On Bivariate Lag-Distributions Of Backbone Angles, Mehdi Maadooliat, Xin Gao, Jianhua Z. Huang Nov 2013

Assessing Protein Conformational Sampling Methods Based On Bivariate Lag-Distributions Of Backbone Angles, Mehdi Maadooliat, Xin Gao, Jianhua Z. Huang

Mathematics, Statistics and Computer Science Faculty Research and Publications

Despite considerable progress in the past decades, protein structure prediction remains one of the major unsolved problems in computational biology. Angular-sampling-based methods have been extensively studied recently due to their ability to capture the continuous conformational space of protein structures. The literature has focused on using a variety of parametric models of the sequential dependencies between angle pairs along the protein chains. In this article, we present a thorough review of angular-sampling-based methods by assessing three main questions: What is the best distribution type to model the protein angles? What is a reasonable number of components in a mixture model …

Go to article

Observed Versus Gcm-Generated Local Tropical Cyclone Frequency: Comparisons Using A Spatial Lattice, Sarah Strazzo, Daniel J. Halperin, James Elsner, Tim Larow, Ming Zhao Nov 2013

Observed Versus Gcm-Generated Local Tropical Cyclone Frequency: Comparisons Using A Spatial Lattice, Sarah Strazzo, Daniel J. Halperin, James Elsner, Tim Larow, Ming Zhao

Publications

Of broad scientific and public interest is the reliability of global climate models (GCMs) to simulate future regional and local tropical cyclone (TC) occurrences. Atmospheric GCMs are now able to generate vortices resembling actual TCs, but questions remain about their fidelity to observed TCs. Here the authors demonstrate a spatial lattice approach for comparing actual with simulated TC occurrences regionally using observed TCs from the International Best Track Archive for Climate Stewardship (IBTrACS) dataset and GCM-generated TCs from the Geophysical Fluid Dynamics Laboratory (GFDL) High Resolution Atmospheric Model (HiRAM) and Florida State University (FSU) Center for Ocean–Atmospheric Prediction Studies (COAPS) …

Go to article

First Prev Next Last