Physical Sciences and Mathematics Commons^™

Structural Properties Of Transmuted Weibull Distribution, Kaisar Ahmad, S. P. Ahmad, A. Ahmed

Journal of Modern Applied Statistical Methods

The transmuted Weibull distribution, and a related special case, is introduced. Estimates of parameters are obtained by using a new method of moments.

New Entropy Estimators With Smaller Root Mean Squared Error, Amer Ibrahim Al-Omari

Journal of Modern Applied Statistical Methods

New estimators of entropy of continuous random variable are suggested. The proposed estimators are investigated under simple random sampling (SRS), ranked set sampling (RSS), and double ranked set sampling (DRSS) methods. The estimators are compared with Vasicek (1976) and Al-Omari (2014) entropy estimators theoretically and by simulation in terms of the root mean squared error (RMSE) and bias values. The results indicate that the suggested estimators have less RMSE and bias values than their competing estimators introduced by Vasicek (1976) and Al-Omari (2014).

Caution For Software Use Of New Statistical Methods (R), Akiva J. Lorenz, Barry S. Markman, Shlomo Sawilowsky

Journal of Modern Applied Statistical Methods

Open source programming languages such as R allow statisticians to develop and rapidly disseminate advanced procedures, but sometimes at the expense of a proper vetting process. A new example is the least trimmed squares regression available in R’s lqs() in the MASS library. It produces pretty regression lines, particularly in the presence of outliers. However, this procedure lacks a defined standard error, and thus it should be avoided.

Inferences About The Skipped Correlation Coefficient: Dealing With Heteroscedasticity And Non-Normality, Rand Wilcox

Journal of Modern Applied Statistical Methods

A common goal is testing the hypothesis that Pearson’s correlation is zero and typically this is done based on Student’s T test. There are, however, several well-known concerns. First, Student’s T is sensitive to heteroscedasticity. That is, when it rejects, it is reasonable to conclude that there is dependence, but in terms of making a decision about the strength of the association, it is unsatisfactory. Second, Pearson’s correlation is not robust: it can poorly reflect the strength of the association. Even a single outlier can have a tremendous impact on the usual estimate of Pearson’s correlation, which can result in …

In (Partial) Defense Of .05, Thomas R. Knapp

Journal of Modern Applied Statistical Methods

Researchers are frequently chided for choosing the .05 alpha level as the determiner of statistical significance (or non-significance). A partial justification is provided.

The Distribution Of The Inverse Square Root Transformed Error Component Of The Multiplicative Time Series Model, Bright F. Ajibade, Chinwe R. Nwosu, J. I. Mbegdu

Journal of Modern Applied Statistical Methods

The probability density function, mean and variance of the inverse square-root transformed left-truncated N(1,σ²) error component e^*_t(=1/ √e_t) of the multiplicative time series model were established. A comparison of key-statistical properties of e^*_t and e_t confirmed normality with mean 1 but with Var(e^*_t) ≈1/4Var(e_t) when σ≤0.14. Hence σ≤0.14 is the required condition for successful transformation.

Front Matter, Jmasm Editors

Journal of Modern Applied Statistical Methods

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Reversible Peg Solitaire On Graphs, John Engbers, Christopher Stocker

Mathematics, Statistics and Computer Science Faculty Research and Publications

The game of peg solitaire on graphs was introduced by Beeler and Hoilman in 2011. In this game, pegs are initially placed on all but one vertex of a graph G. If xyz forms a path in G and there are pegs on vertices x and y but not z, then a jump places a peg on z and removes the pegs from x and y. A graph is called solvable if, for some configuration of pegs occupying all but one vertex, some sequence of jumps leaves a single peg. We study the game of reversible peg …

Monte Carlo Comparison Of The Parameter Estimation Methods For The Two-Parameter Gumbel Distribution, Demet Aydin, Birdal Şenoğlu

Journal of Modern Applied Statistical Methods

The performances of the seven different parameter estimation methods for the Gumbel distribution are compared with numerical simulations. Estimation methods used in this study are the method of moments (ME), the method of maximum likelihood (ML), the method of modified maximum likelihood (MML), the method of least squares (LS), the method of weighted least squares (WLS), the method of percentile (PE) and the method of probability weighted moments (PWM). Performance of the estimators is compared with respect to their biases, MSE and deficiency (Def) values via Monte-Carlo simulation. A Monte Carlo Simulation study showed that the method of PWM was …

Jmasm34: Two Group Program For Cohen's D, Hedges’ G, Η2, Radj2, Ω2, Ɛ2, Confidence Intervals, And Power, David A. Walker

Journal of Modern Applied Statistical Methods

The purpose of this research is to provide an application for users interested in a SPSS syntax program to determine an array of commonly-employed effect sizes and confidence intervals not readily available in SPSS functionality, such as the standardized mean difference and r-related squared indices, for a between-group design.

Identification And Survival Outcomes Of A Cohort Of Patients With Cancer Of Unknown Primary In Ontario, Canada., Chong S Kim, Malek B Hannouf, Sisira Sarma, George B Rodrigues, Peter K Rogan, Salaheddin M Mahmud, Eric Winquist, Muriel Brackstone, Gregory S Zaric

Epidemiology and Biostatistics Publications

BACKGROUND: Cancer of unknown primary origin (CUP) is defined by the presence of pathologically identified metastatic disease without clinical or radiological evidence of a primary tumour. Our objective was to identify incident cases of CUP in Ontario, Canada, and determine the influence of histology and sites of metastases on overall survival (OS).

MATERIAL AND METHODS: We used the Ontario Cancer Registry (OCR) and the Same-Day Surgery and Discharge Abstract Database (SDS/DAD) to identify patients diagnosed with CUP in Ontario between 1 January 2000, and 31 December 2005. Patient diagnostic information, including histology and survival data, was obtained from the OCR. …

Vol. 14, No. 2 (Full Issue), Jmasm Editors

Journal of Modern Applied Statistical Methods

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Resolving The Issue Of How Reliability Is Related To Statistical Power: Adhering To Mathematical Definitions, Donald W. Zimmerman, Bruno D. Zumbo

Journal of Modern Applied Statistical Methods

Reliability in classical test theory is a population-dependent concept, defined as a ratio of true-score variance and observed-score variance, where observed-score variance is a sum of true and error components. On the other hand, the power of a statistical significance test is a function of the total variance, irrespective of its decomposition into true and error components. For that reason, the reliability of a dependent variable is a function of the ratio of true-score variance and observed-score variance, whereas statistical power is a function of the sum of the same two variances. Controversies about how reliability is related to statistical …

A Robust Panel Unit Root Test In The Presence Of Cross Sectional Dependence, Nurul Sima Mohamad Shariff, Nor Aishah Hamzah

Journal of Modern Applied Statistical Methods

Problems arise in testing the stationarity of the panel in the presence of cross sectional dependence and outliers. The currently available panel unit root tests are very much affected by the presence of outliers. As such, this article introduces an alternative test which is robust to outliers and cross sectional dependence. The performance and robustness of the proposed test is discussed and comparisons are made to the existing tests via simulation studies.

Statistical Modeling Of Migration Attractiveness Of The Eu Member States, Tatiana Tikhomirova, Yulia Lebedeva

Journal of Modern Applied Statistical Methods

Identifying the relationship between the migration attractiveness of the European Union countries and their level of socio-economic development is investigated. An approach is proposed identify influences on migration socio-economic characteristics, by aggregating and reducing their diversity, and substantiating the cause-and-effect relationships of the studied phenomenon. A stable classification of countries scheme is developed according to the attractiveness of migration on aggregate factors, and then an econometric model of a binary choice using panel data for 2008-2010 was applying, quantifying the impact of aggregate designed factors on immigration and emigration.

From Subcompact To Domain Representable, William Fleissner, Lynne Yengulalp

Mathematics Faculty Publications

No abstract provided.

Flexible Penalized Regression For Functional Data...And Other Complex Data Objects, Philip T. Reiss

Philip T. Reiss

No abstract provided.

Mixed Methods Research Designs, Kevin P. Gosselin Phd

Research Day

No abstract provided.

Removing Inter-Subject Technical Variability In Magnetic Resonance Imaging Studies, Jean-Philippe Fortin, Elizabeth M. Sweeney, John Muschelli, Ciprian M. Crainiceanu, Russell T. Shinohara, Alzheimer’S Disease Neuroimaging Initiative

UPenn Biostatistics Working Papers

Magnetic resonance imaging (MRI) intensities are acquired in arbitrary units, making scans non-comparable across sites and between subjects. Intensity normalization is a first step for the improvement of comparability of the images across subjects. However, we show that unwanted inter-scan variability associated with imaging site, scanner effect and other technical artifacts is still present after standard intensity normalization in large multi-site neuroimaging studies. We propose RAVEL (Removal of Artificial Voxel Effect by Linear regression), a tool to remove residual technical variability after intensity normalization. As proposed by SVA and RUV [Leek and Storey, 2007, …

Integrated Bioinformatics, Environmental Epidemiologic And Genomic Approaches To Identify Environmental And Molecular Links Between Endometriosis And Breast Cancer, Deodutta Roy, Marisa L. Morgan, Changwon Yoo, Alok Deoraj, Sandhya Roy, Vijay Kumar Yadav, Mohannad Garoub, Hamza Assaggaf, Mayur Doke

Department of Biostatistics Faculty Publications

We present a combined environmental epidemiologic, genomic, and bioinformatics approach to identify: exposure of environmental chemicals with estrogenic activity; epidemiologic association between endocrine disrupting chemical (EDC) and health effects, such as, breast cancer or endometriosis; and gene-EDC interactions and disease associations. Human exposure measurement and modeling confirmed estrogenic activity of three selected class of environmental chemicals, polychlorinated biphenyls (PCBs), bisphenols (BPs), and phthalates. Meta-analysis showed that PCBs exposure, not Bisphenol A (BPA) and phthalates, increased the summary odds ratio for breast cancer and endometriosis. Bioinformatics analysis of gene-EDC interactions and disease associations identified several hundred genes that were altered by …

Type 2 Diabetes And Its Correlates Among Adults In Bangladesh: A Population Based Stud, Muhammad Abdul Baker Chowdhury, Md Jamal Uddin, Hafiz M.R. Khan, Md Rabiul Haque

Department of Biostatistics Faculty Publications

Type 2 diabetes is one of the most prevalent non-communicable diseases in Bangladesh. However, the correlates of type 2 diabetes among adults in Bangladesh remain unknown. We aimed to investigate the correlates of type 2 diabetes among the adults in Bangladesh.

Methods : We conducted a cross-sectional study using data from the nationally representative 2011 Bangladesh Demographic and Health Survey. A random sample of 7,543 (3,823 women and 3,720 men) adults of age 35 years and older from both urban and rural areas, who participated in the survey was included. Diabetes was defined as having a fasting plasma blood glucose …

Sinkhole Vulnerability Mapping: Results From A Pilot Study In North Central Florida, Clint Kromhout, Alan E. Baker

Sinkhole Conference 2015

At the end of June in 2012, Tropical Storm Debby dropped a record amount of rainfall across Florida which triggered hundreds, if not thousands, of sinkholes to form which resulted in tremendous damage to property. The Florida Division of Emergency Management contracted with the Florida Department of Environmental Protection’s Florida Geological Survey to produce a map depicting the state’s vulnerability to sinkhole formation. The three-year project began with a pilot study in three northern Florida counties: Columbia, Hamilton and Suwannee. Utilizing the statistical modeling method Weights of Evidence, results from the pilot study yielded a 93 percent success rate of …

Prediction: The Quintessential Model Validation Test, Wayne Wakeland

Systems Science Friday Noon Seminar Series

It is essential to objectively test how well policy models predict real world behavior. The method used to support this assertion involves the review of three SD policy models emphasizing the degree to which the model was able to fit the historical outcome data and how well model-predicted outcomes matched real world outcomes as they unfolded. Findings indicate that while historical model agreement is a favorable indication of model validity, the act of making predictions without knowing the actual data, and comparing these predictions to actual data, can reveal model weaknesses that might be overlooked when all of the available …

Computerizing Efficient Estimation Of A Pathwise Differentiable Target Parameter, Mark J. Van Der Laan, Marco Carone, Alexander R. Luedtke

Alex Luedtke

Frangakis et al. (2015) proposed a numerical method for computing the efficient influence function of a parameter in a nonparametric model at a specified distribution and observation (provided such an influence function exists). Their approach is based on the assumption that the efficient influence function is given by the directional derivative of the target parameter mapping in the direction of a perturbation of the data distribution defined as the convex line from the data distribution to a pointmass at the observation. In our discussion paper Luedtke et al. (2015) we propose a regularization of this procedure and establish the validity …

Dynapenic Obesity And The Effect On Long-Term Physical Function And Quality Of Life: Data From The Osteoarthritis Initiative, John A. Batsis, Alicia J. Zbehlik, Dawna Pidgeon, Stephen J. Bartels

Dartmouth Scholarship

Obesity is associated with functional impairment, institutionalization, and increased mortality risk in elders. Dynapenia is defined as reduced muscle strength and is a known independent predictor of adverse events and disability. The synergy between dynapenia and obesity leads to worse outcomes than either independently. We identified the impact of dynapenic obesity in a cohort at risk for and with knee osteoarthritis on function.

Data Science In Statistics Curricula: Preparing Students To “Think With Data”, J. Hardin, R. Hoerl, Nicholas J. Horton, D. Nolan, B. Baumer, O. Hall-Holt, P. Murrell, R. Peng, P. Roback, D. Temple Lang, M. D. Ward

Statistical and Data Sciences: Faculty Publications

A growing number of students are completing undergraduate degrees in statistics and entering the workforce as data analysts. In these positions, they are expected to understand how to use databases and other data warehouses, scrape data from Internet sources, program solutions to complex problems in multiple languages, and think algorithmically as well as statistically. These data science topics have not traditionally been a major component of undergraduate programs in statistics. Consequently, a curricular shift is needed to address additional learning outcomes. The goal of this article is to motivate the importance of data science proficiency and to provide examples and …

The Kumaraswamy Marshal-Olkin Family Of Distributions, Morad Alizadeh, M. H. Tahir, Gauss M. Cordeiro, M. Mansoor, Muhammad Zubair, Gholamhossein Hamedani

Mathematics, Statistics and Computer Science Faculty Research and Publications

We introduce a new family of continuous distributions called the Kumaraswamy Marshal-Olkin generalized family of distributions. We study some mathematical properties of this family. Its density function is symmetrical, left-skewed, right-skewed and reversed-J shaped, and has constant, increasing, decreasing, upside-down bathtub, bathtub and S-shaped hazard rate. We present some special models and investigate the asymptotics and shapes of the family. We derive a power series for the quantile function and obtain explicit expressions for the moments, generating function, mean deviations, two types of entropies and order statistics. Some useful characterizations of the family are also proposed. The method of maximum …

Validation Of A New Predictive Risk Model: Measuring The Impact Of The Major Modifiable Risks Of Death For Patients And Populations, Stephen S. Lim, Emily Carnahan, Eugene C. Nelson, Catherine W. Gillespie, Ali H. Mokdad, Christopher J. L. Murray, Elliott S. Fisher

Dartmouth Scholarship

Background: Modifiable risks account for a large fraction of disease and death, but clinicians and patients lack tools to identify high risk populations or compare the possible benefit of different interventions.

Methods: We used data on the distribution of exposure to 12 major behavioral and biometric risk factors inthe US population, mortality rates by cause, and estimates of the proportional hazards of risk factor exposure from published systematic reviews to develop a risk prediction model that estimates an adult's 10 year mortality risk compared to a population with optimum risk factors. We compared predicted risk to observed mortality in 8,241 …

Wright State University Math And Statistics Department History, Joanne Dombrowski, David Miller

Mathematics and Statistics Faculty Publications

No abstract provided.

Sequencing Of 15 622 Gene-Bearing Bacs Clarifies The Gene-Dense Regions Of The Barley Genome, María Muñoz-Amatriaín, Stefano Lonardi, Mingcheng Luo, Kavitha Madishetty, Jan T. Svensson, Matthew J. Moscou, Steve Wanamaker, Tao Jiang, Andris Kleinhofs, Gary J. Muehlbauer, Roger P. Wise, Nils Stein, Shane Ma, Edmundo Rodriguez, Dave Kudrna, Prasanna R. Bhat, Shiaoman Chao, Pascal Condamine, Shane Heinen, Josh Resnik, Rod Wing, Heather N. Witt, Matthew Alpert, Marco Beccuti, Serdar Bozdag, Francesca Cordero, Hamid Mirebrahim, Rachid Ounit, Yonghui Wu, Frank You, Jie Zheng, Hana Simková, Jaroslav Dolezel, Jane Grimwood, Jeremy Schmutz, Denisa Duma, Lothar Altschmied, Tom Blake, Phil Bregitzer, Laurel Cooper, Muharrem Dilbirligi, Anders Falk, Leila Feiz, Andreas Graner, Perry Gustafson, Patrick M. Hayes, Peggy Lemaux, Jafar Mammadov, Timothy J. Close

Mathematics, Statistics and Computer Science Faculty Research and Publications

Barley (Hordeum vulgare L.) possesses a large and highly repetitive genome of 5.1 Gb that has hindered the development of a complete sequence. In 2012, the International Barley Sequencing Consortium released a resource integrating whole-genome shotgun sequences with a physical and genetic framework. However, because only 6278 bacterial artificial chromosome (BACs) in the physical map were sequenced, fine structure was limited. To gain access to the gene-containing portion of the barley genome at high resolution, we identified and sequenced 15 622 BACs representing the minimal tiling path of 72 052 physical-mapped gene-bearing BACs. This generated ~1.7 Gb of genomic …