Statistics and Probability Commons^™

Vol. 16, No. 1 (Full Issue), Jmasm Editors

Journal of Modern Applied Statistical Methods

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Robust Ancova: Confidence Intervals That Have Some Specified Simultaneous Probability Coverage When There Is Curvature And Two Covariates, Rand Wilcox

Journal of Modern Applied Statistical Methods

Consider the commonly occurring situation where the goal is to compare two independent groups and there are two covariates. Let Mj(X) be some conditional measure of location for the jth group associated with some random variable Y given X = (X1, X2). The goal is to H0: M1(X) = M2(X) for each X Ω in a manner that controls the probability of one or more Type I errors. An extant technique (method M1 here) addresses this goal without making any parametric assumption about Mj(X). However, a practical concern is that it does not provide enough detail regarding where the regression …

Limitations In The Systematic Analysis Of Structural Equation Model Fit Indices, Sarah A. Rose, Barry Markman, Shlomo Sawilowsky

Journal of Modern Applied Statistical Methods

The purpose of this study was to evaluate the sensitivity of selected fit index statistics in determining model fit in structural equation modeling (SEM). The results indicated a large dependency on correlation magnitude of the input correlation matrix, with mixed results when the correlation magnitudes were low and a primary indication of good model fit. This was due to the default SEM method of Maximum Likelihood that assumes unstandardized correlation values. However, this warning is not well-known, and is only obscurely mentioned in some textbooks. Many SEM computer software programs do not give appropriate error indications that the results are …

A Note On Determination Of Sample Size From The Perspective Of Six Sigma Quality, Joghee Ravichandran

Journal of Modern Applied Statistical Methods

In most empirical studies (clinical, network modeling, and survey-based and aeronautical studies, etc.), sample observations are drawn from population to analyze and draw inferences about the population. Such analysis is done with reference to a measurable quality characteristic of a product or process of interest. However, fixing a sample size is an important task that has to be decided by the experimenter. One of the means in deciding an appropriate sample size is the fixation of error limit and the associated confidence level. This implies that the analysis based on the sample used must guarantee the prefixed error and confidence …

Methodology For Constructing Perceptual Maps Incorporating Measuring Error In Sensory Acceptance Tests, Elisa Norberto Ferreira Santos, Gilberto Rodrigues Liska, Marcelo Angelo Cirillo

Journal of Modern Applied Statistical Methods

A new method is proposed based on construction of perceptual maps using techniques of correspondence analysis and interval algebra that allow specifying the measurement error expected in panel choices in the evaluation form described in unstructured 9-point hedonic scale.

Confidence Intervals For The Scaled Half-Logistic Distribution Under Progressive Type-Ii Censoring, Kiran Ganpati Potdar, D. T. Shirke

Journal of Modern Applied Statistical Methods

Confidence interval construction for the scale parameter of the half-logistic distribution is considered using four different methods. The first two are based on the asymptotic distribution of the maximum likelihood estimator (MLE) and log-transformed MLE. The last two are based on pivotal quantity and generalized pivotal quantity, respectively. The MLE for the scale parameter is obtained using the expectation-maximization (EM) algorithm. Performances are compared with the confidence intervals proposed by Balakrishnan and Asgharzadeh via coverage probabilities, length, and coverage-to-length ratio. Simulation results support the efficacy of the proposed approach.

A New Estimator Based On Auxiliary Information Through Quantitative Randomized Response Techniques, Nilgün Özgül, Hülya Çıngı

Journal of Modern Applied Statistical Methods

An exponential-type estimator is developed for the population mean of the sensitive study variable based on various Randomized Response Techniques (RRT) using a non-sensitive auxiliary variable. The mean squared error (MSE) of the proposed estimator is derived for generalized RRT models. The proposed estimator is compared with competitors in a simulation study and an application. The proposed estimator is found to be more efficient using a non-sensitive auxiliary variable.

Plant Leaf Image Detection Method Using A Midpoint Circle Algorithm For Shape-Based Feature Extraction, B. Vijaya Lakshmi, V. Mohan

Journal of Modern Applied Statistical Methods

Shape-based feature extraction in content-based image retrieval is an important research area at present. An algorithm is presented, based on shape features, to enhance the set of features useful in a leaf identification system.

Multiple Ratio Imputation By The Emb Algorithm: Theory And Simulation, Masayoshi Takahashi

Journal of Modern Applied Statistical Methods

Although multiple imputation is the gold standard of treating missing data, single ratio imputation is often used in practice. Based on Monte Carlo simulation, the Expectation-Maximization with Bootstrapping (EMB) algorithm to create multiple ratio imputation is used to fill in the gap between theory and practice.

Jmasm45: A Computer Program For Bayesian D-Optimal Binary Repeated Measurements Designs (Matlab), Haftom Temesgen Abebe, Frans E. S. Tan, Gerard J. P. Van Breukelen, Martijn P. F. Berger

Journal of Modern Applied Statistical Methods

Planners of longitudinal studies of binary responses in applied sciences have not yet benefitted from optimal designs, which have been shown to improve precision of model parameter estimates, due to absence of a computer program. An interactive computer program for Bayesian optimal binary repeated measurements designs is presented for this purpose.

Weighted Distributions: A Brief Review, Perspective And Characterizations, Aamir Saghir, Gholamhossein G. Hamedani, Sadaf Tazeem, Aneeqa Khadim

Mathematics, Statistics and Computer Science Faculty Research and Publications

The weighted distributions are widely used in many fields such as medicine, ecology and reliability, to name a few, for the development of proper statistical models. Weighted distributions are milestone for efficient modeling of statistical data and prediction when the standard distributions are not appropriate. A good deal of studies related to the weight distributions have been published in the literature. In this article, a brief review of these distributions is carried out. Implications of the differing weight models for future research as well as some possible strategies are discussed. Finally, characterizations of these distributions based on a simple relationship …

Joint Modelling Of Longitudinal Measurements And Time-To-Event Data : Application To Hiv Study, Mirna Walid Halawani

Theses, Dissertations and Culminating Projects

Longitudinal and survival data are frequently collected in biomedical studies. The research questions of interest in these studies often require separate analysis of the outcomes. But in many occasions interest also lies in studying their association structures, such as in biomarker research, where the clinical studies are designed to identify biomarkers with strong prognostic capabilities for event time outcomes. In the separate analyses, a linear mixed-effects model is used for modeling the longitudinal data to study the changing trend of the response overtime when controlling some covariates and a survival model is used to model the time-to-event data. A common …

Topics In Group Testing With Multiple Infections, Peijie Hou

Theses and Dissertations

Group testing, dating back to the early 1940s, was first proposed to screen for syphilis among US inductees during World War II (Dorfman, 1943). Since then, the benefits of reducing testing costs by employing group testing have been demonstrated in many areas, such as drug discovery, genetics, and infectious disease testing. Traditionally, statistical research in group testing has largely been motivated by applications involving a single infection. With the recent development of multiplex assays that can diagnose multiple infections simultaneously, generalizing the existing group testing literature to incorporate multiple infections is a natural and necessary next step. This dissertation consists …

Bayesian Flexible Modeling Of Interval-Censored Failure Time Data, Sheng-Yang Wang

Theses and Dissertations

Interval-censored data are a special type of survival data, in which the survival time is not accurately observed but known to fall within a specific time interval. Interval censored data commonly arise in real-life epidemiological and medical studies that involve periodic examinations. In this dissertation, several semi-parametric regression models are investigated to provide flexible modeling and robust inference for interval censored data from Bayesian perspectives.

Chapter 1 provides a detailed description about interval-censored data and gives several examples. Existing models and methods for analyzing such interval-censored data are reviewed as well. Chapter 2 develops a unified Bayesian estimation approach under …

Statistical Learning Methods For Facial Recognition, Mengyi Jia

Arts & Sciences Graduate Student Theses and Dissertations

Facial recognition techniques have become increasingly popular in recent decades. This thesis investigates the performance of several methods applied to two different face databases, under a variety of poses and illumination settings. PCA, LDA and KNN are compared and contrasted in terms of their accuracy and processing time.

An Extended Weighted Exponential Distribution, Abbas Mahdavi, Leila Jabari

Journal of Modern Applied Statistical Methods

A new class of weighted distributions is proposed by incorporating an extended exponential distribution in Azzalini’s (1985) method. Several statistics and reliability properties of this new class of distribution are obtained. Maximum likelihood estimators of the unknown parameters cannot be obtained in explicit forms; they have to be obtained by solving some numerical methods. Two data sets are analyzed for illustrative purposes, and show that the proposed model can be used effectively in analyzing real data.

A Comparison Of Depth Functions In Maximal Depth Classification Rules, Olusola Samuel Makinde, Adeyinka Damilare Adewumi

Journal of Modern Applied Statistical Methods

Data depth has been described as alternative to some parametric approaches in analyzing many multivariate data. Many depth functions have emerged over two decades and studied in literature. In this study, a nonparametric approach to classification based on notions of different data depth functions is considered and some properties of these methods are studied. The performance of different depth functions in maximal depth classifiers is investigated using simulation and real data with application to agricultural industry.

The Double Prior Selection For The Parameter Of Exponential Life Time Model Under Type Ii Censoring, Ronak M. Patel, Achyut C. Patel

Journal of Modern Applied Statistical Methods

A comparison of double informative priors assumed for the parameter of exponential life time model is considered. Three different sets of double priors are included, and the results are compared with a forth single prior. The data is Type II censored and Bayes estimators for the parameter and reliability are carried out under a squared error loss function in the cases of the four different sets of prior distributions. The predictive distribution was derived for future failure time and also for the remaining ordered failure times after the first r failure times have been observed. Corresponding Bayes credible equal tail …

Jmasm43: Teereg: Trimmed Elemental Estimation (R), Wei Jiang, Matthew S. Mayo

Journal of Modern Applied Statistical Methods

Trimmed elemental regression is robust to outliers and violations of model assumptions. Its properties and statistical inference were evaluated using bias-corrected and accelerated bootstrap confidence intervals. An R package named TEEReg is developed to compute the trimmed elemental estimates and the corresponding bootstrap confidence intervals. Two examples are provided to demonstrate its usage.

Outlier Impact And Accommodation On Power, Hongjing Liao, Yanju Li, Gordon P. Brooks

Journal of Modern Applied Statistical Methods

The outliers’ influence on power rates in ANOVA and Welch tests at various conditions was examined and compared with the effectiveness of nonparametric methods and Winsorizing in minimizing the impact of outliers. Results showed that, considering both power and Type I error, a nonparametric test is the safest choice to control the inflation of Type I error with a decent sample size and yield relatively high power.

Book Review: Multivariate Statistical Methods, A Primer, C. R. Rao

Journal of Modern Applied Statistical Methods

Multivariate Statistical Methods, A Primer, 4th Ed. Bryan F. J. Manly and Jorge A. Navarro Alberto. NY: Chapman & Hall / CRC Press. 2016. 264 p. ISBN 10: 1498728960 / ISBN 13: 978-1498728966

Jmasm44: Implementing Multiple Ratio Imputation By The Emb Algorithm (R), Masayoshi Takahashi

Journal of Modern Applied Statistical Methods

Although single ratio imputation is often used to deal with missing values in practice, there is a paucity of discussion regarding multiple ratio imputation. Code in the R statistical environment is presented to execute multiple ratio imputation by the Expectation-Maximization with Bootstrapping (EMB) algorithm.

Eit Imaging Of Admittivities With A D-Bar Method And Spatial Prior: Experimental Results For Absolute And Difference Imaging, Sarah J. Hamilton

Mathematics, Statistics and Computer Science Faculty Research and Publications

Electrical impedance tomography (EIT) is an emerging imaging modality that uses harmless electrical measurements taken on electrodes at a body's surface to recover information about the internal electrical conductivity and or permittivity. The image reconstruction task of EIT is a highly nonlinear inverse problem that is sensitive to noise and modeling errors making the image reconstruction task challenging. D-bar methods solve the nonlinear problem directly, bypassing the need for detailed and time-intensive forward models, to provide absolute (static) as well as time-difference EIT images. Coupling the D-bar methodology with the inclusion of high confidence a priori data results in a …

Comparison Of Survival Curves Between Cox Proportional Hazards, Random Forests, And Conditional Inference Forests In Survival Analysis, Brandon Weathers

All Graduate Plan B and other Reports, Spring 1920 to Spring 2023

Survival analysis methods are a mainstay of the biomedical fields but are finding increasing use in other disciplines including finance and engineering. A widely used tool in survival analysis is the Cox proportional hazards regression model. For this model, all the predicted survivor curves have the same basic shape, which may not be a good approximation to reality. In contrast the Random Survival Forests does not make the proportional hazards assumption and has the flexibility to model survivor curves that are of quite different shapes for different groups of subjects. We applied both techniques to a number of publicly available …

A Tournament Approach To Price Discovery In The Us Cattle Market, Jeffrey Wright

All Graduate Theses and Dissertations, Spring 1920 to Summer 2023

Cattle price discovery is a process of determining the price in the market through the interactions of cattle buyers (packers) and sellers (ranchers). Locating the price discovery center or market, and estimating price interactions among the regional fed cattle markets and also among feeder cattle markets can help define a relevant fed cattle procurement market. This research identifies that the U.S. cattle markets is discovered in the futures markets, feeder cattle futures and fed futures.

Statistical Methods For Assessing Individual Oocyte Viability Through Gene Expression Profiles, Michael O. Bishop

All Graduate Plan B and other Reports, Spring 1920 to Spring 2023

Abstract

Statistical Methods for Assessing Individual Oocyte Viability Through Gene Expression Profiles

By

Michael O. Bishop

Utah State University, 2017

Major Professor: Dr. John R. Stevens

Department: Mathematics and Statistics

Oocytes are the precursor cells to the female gamete, or egg. While reproduction may vary from species to species, within humans and most domesticated animals, the oocyte maturation process is fairly similar. As an oocyte matures, there are various processes that take place, all of which have an effect on the viability of the individual oocyte. Barring outside damage that may come to the oocyte, one of the primary reasons …

Tuberculosis And Risk Of Acute Myocardial Infarction: A Propensity Score-Matched Analysis, Moises A. Huaman, Richard J. Kryscio, Carl J. Fichtenbaum, David Henson, Elizabeth G. Salt, Timothy R. Sterling, Beth A. Garvy

Biostatistics Faculty Publications

Several pathogens have been associated with increased cardiovascular disease (CVD) risk. Whether this occurs with Mycobacterium tuberculosis infection is unclear. We assessed if tuberculosis disease increased the risk of acute myocardial infarction (AMI). We identified patients with tuberculosis index claims from a large de-identified database of ~15 million adults enrolled in a U.S. commercial insurance policy between 2008 and 2010. Tuberculosis patients were 1:1 matched to patients without tuberculosis claims using propensity scores. We compared the occurrence of index AMI claims between the tuberculosis and non-tuberculosis cohorts using Kaplan–Meier curves and Cox Proportional Hazard models. Data on 2026 patients with …

Novel Statistical Approaches For Missing Values In Truncated High-Dimensional Metabolomics Data With A Detection Threshold., Jasmit Sureshkumar Shah

Electronic Theses and Dissertations

Despite considerable advances in high throughput technology over the last decade, new challenges have emerged related to the analysis, interpretation, and integration of high-dimensional data. The arrival of omics datasets has contributed to the rapid improvement of systems biology, which seeks the understanding of complex biological systems. Metabolomics is an emerging omics field, where mass spectrometry technologies generate high dimensional datasets. As advances in this area are progressing, the need for better analysis methods to provide correct and adequate results are required. While in other omics sectors such as genomics or proteomics there has and continues to be critical understanding …

Trend And Return Level Of Extreme Snow Events In New York City, Mintaek Lee

Boise State University Theses and Dissertations

A major winter storm brought up to 42 inches of snow in parts of the Mid-Atlantic and Northeast United States for January 22-24, 2016. The blizzard of January 2016 impacted about 102.8 million people, where at least 55 people died due to the snowstorm and it caused economic losses in a range of $500 million to $3 billion. This thesis studies two important aspects of extreme snow events: maximum snowfall and maximum snow depth. We apply extreme value methods to extreme snowfall and snow depth data from the New York City area to examine if there are any significant linear …

Price Prediction: Determining Changes In Stock Pricing Through Sentiment Analysis Of Online Consumer Reviews, Daryl F. Boykin

UNLV Theses, Dissertations, Professional Papers, and Capstones

The rapid growth of technology has changed the dynamics in which consumers socialize and make their purchasing decisions. The volume of online reviews has grown rapidly over the past decade, leading the peer groups of consumer to carry a disproportionate weight in the purchasing decision process. The sheer volume of reviews can be a daunting task for an operator to attempt to incorporate the reviews in their analysis. Sentiment analysis allows for large volumes of consumer reviews to be processed in a relatively easy, and time sensitive manner. The information contained in these reviews, the sentiment score, is the same …