Statistics and Probability Commons^™

The Bayes Factor For Case-Control Studies With Misclassified Data, Tzesan Lee

Journal of Modern Applied Statistical Methods

The question of how to test if collected data for a case-control study are misclassified was investigated. A mixed approach was employed to calculate the Bayes factor to assess the validity of the null hypothesis of no-misclassification. A real-world data set on the association between lung cancer and smoking status was used as an example to illustrate the proposed method.

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. …

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 …

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.

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

Journal of Modern Applied Statistical Methods

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Semi-Parametric Non-Proportional Hazard Model With Time Varying Covariate, Kazeem A. Adeleke, Alfred A. Abiodun, R. A. Ipinyomi

Journal of Modern Applied Statistical Methods

The application of survival analysis has extended the importance of statistical methods for time to event data that incorporate time dependent covariates. The Cox proportional hazards model is one such method that is widely used. An extension of the Cox model with time-dependent covariates was adopted when proportionality assumption are violated. The purpose of this study is to validate the model assumption when hazard rate varies with time. This approach is applied to model data on duration of infertility subject to time varying covariate. Validity is assessed by a set of simulation experiments and results indicate that a non proportional …

Bayesian Analysis Under Progressively Censored Rayleigh Data, Gyan Prakash

Journal of Modern Applied Statistical Methods

The one-parameter Rayleigh model is considered as an underlying model for evaluating the properties of Bayes estimator under Progressive Type-II right censored data. The One‑Sample Bayes prediction bound length (OSBPBL) is also measured. Based on two different asymmetric loss functions a comparative study presented for Bayes estimation. A simulation study was used to evaluate their comparative properties.

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.

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.

Approaches For Detection Of Unstable Processes: A Comparative Study, Yerriswamy Wooluru, D. R. Swamy, P. Nagesh

Journal of Modern Applied Statistical Methods

A process is stable only when parameters of the distribution of a process or product characteristic remain same over time. Only a stable process has the ability to perform in a predictable manner over time. Statistical analysis of process data usually assume that data are obtained from stable process. In the absence of control charts, the hypothesis of process stability is usually assessed by visual examination of the pattern in the run chart. In this paper appropriate statistical approaches have been adopted to detect instability in the process and compared their performance with the run chart of considerably shorter length …

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.

Abcc9/Sur2 In The Brain: Implications For Hippocampal Sclerosis Of Aging And A Potential Therapeutic Target, Peter T. Nelson, Gregory A. Jicha, Wang-Xia Wang, Eseosa T. Ighodaro, Sergey C. Artiushin, Colin G. Nichols, David W. Fardo

Sanders-Brown Center on Aging Faculty Publications

The ABCC9 gene and its polypeptide product, SUR2, are increasingly implicated in human neurologic disease, including prevalent diseases of the aged brain. SUR2 proteins are a component of the ATP-sensitive potassium (“K _ATP ”) channel, a metabolic sensor for stress and/or hypoxia that has been shown to change in aging. The K _ATP channel also helps regulate the neurovascular unit. Most brain cell types express SUR2, including neurons, astrocytes, oligodendrocytes, microglia, vascular smooth muscle, pericytes, and endothelial cells. Thus it is not surprising that ABCC9 gene variants are associated with risk for human brain diseases. For example, Cantu syndrome is …

From Subcompact To Domain Representable, William Fleissner, Lynne Yengulalp

Mathematics Faculty Publications

No abstract provided.

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 …

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, …

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 …

Subexponential Solutions Of Linear Volterra Difference Equations, Martin Bohner, Nasrin Sultana

Mathematics and Statistics Faculty Research & Creative Works

We study the asymptotic behavior of the solutions of a scalar convolution sum-difference equation. The rate of convergence of the solution is found by determining the asymptotic behavior of the solution of the transient renewal equation.

Hartogs-Type Extension For Tube-Like Domains In C², Al Boggess, Roman Dwilewicz, Zbigniew Slodkowski

Mathematics and Statistics Faculty Research & Creative Works

In this paper we consider the Hartogs-type extension problem for unbounded domains in C². An easy necessary condition for a domain to be of Hartogs-type is that there is not a closed (in C²) complex variety of codimension one in the domain which is given by a holomorphic function smooth up to the boundary. The question is, how far this necessary condition is from the sufficient one? To show how complicated this question is, we give a class of tube-like domains which contain a complex line in the boundary which are either of Hartogs-type or not, …

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 …