Statistics and Probability Commons^™

A Method For Visualizing Multivariate Time Series Data, Roger D. Peng

Johns Hopkins University, Dept. of Biostatistics Working Papers

Visualization and exploratory analysis is an important part of any data analysis and is made more challenging when the data are voluminous and high-dimensional. One such example is environmental monitoring data, which are often collected over time and at multiple locations, resulting in a geographically indexed multivariate time series. Financial data, although not necessarily containing a geographic component, present another source of high-volume multivariate time series data. We present the mvtsplot function which provides a method for visualizing multivariate time series data. We outline the basic design concepts and provide some examples of its usage by applying it to a …

Empirical Null And False Discovery Rate Inference For Exponential Families, Armin Schwartzman

Harvard University Biostatistics Working Paper Series

No abstract provided.

Marginal Structural Models For Partial Exposure Regimes, Stijn Vansteelandt, Karl Mertens, Carl Suetens, Els Goetghebeur

Harvard University Biostatistics Working Paper Series

Intensive care unit (ICU) patients are ell known to be highly susceptible for nosocomial (i.e. hospital-acquired) infections due to their poor health and many invasive therapeutic treatments. The effects of acquiring such infections in ICU on mortality are however ill understood. Our goal is to quantify these effects using data from the National Surveillance Study of Nosocomial Infections in Intensive Care

Units (Belgium). This is a challenging problem because of the presence of time-dependent confounders (such as exposure to mechanical ventilation)which lie on the causal path from infection to mortality. Standard statistical analyses may be severely misleading in such settings …

Multiple Imputation Of Timing Of Mother-To-Child Transmission Of Hiv, Elizabeth Brown, Ying Qing Chen

UW Biostatistics Working Paper Series

In this paper, we present a model for imputing timing of mother-to- child transmission (MTCT) of HIV. The method re ects the three modes of MTCT of HIV: in utero, during delivery and via breastfeeding and can accomodate shapes for the baseline hazard that vary between infants. Ad- ditionally, it allows that the majority of infants do not experience MTCT of HIV. Final analyses from the imputed data sets are combined in a mul- tiple imputation framework. The methods is illustrated on a large trial designed to assess the use of antibiotics in preventing MTCT of HIV and is validated …

Jointly Modeling Continuous And Binary Outcomes For Boolean Outcomes: An Application To Modeling Hypertension, Xianbin Li, Brian S. Caffo, Elizabeth Stuart

Johns Hopkins University, Dept. of Biostatistics Working Papers

Binary outcomes defined by logical (Boolean) "and" or "or" operations on original continuous and discrete outcomes arise commonly in medical diagnoses and epidemiological research. In this manuscript,we consider applying the “or” operator to two continuous variables above a threshold and a binary variable, a setting that occurs frequently in the modeling of hypertension. Rather than modeling the resulting composite outcome defined by the logical operator, we present a method that models the original outcomes thus utilizing all information in the data, yet continues to yield conclusions on the composite scale. A stratified propensity score adjustment is proposed to account for …

Crop Updates 2008 - Cereals, Christine M. Zaicou-Kunesch, Shahajahan Miyan, Brenda Shackley, Steve Penny, Sarah Ellis, Darshan Sharma, Blakely Paynter, Jeff Russell, Andrea Hills, Glen Riethmuller, Bill Bowden, Paul Blackwell, Harmohinder Dhammu, Vince Lambert, Chris Roberts, David Cox, Sally Cox, Jeremy Lemon, Paul Damon, Zed Rengel, Geoff J. Thomas, Ciara Beard, Anne Smith, Kithsiri Jayasena, Sean Kelly, Rob Loughman, Bill Macleod, Raj Malik, Ravjit Khangura, Vivien Vanstone, Colin Hanbury, Mehreteab Aberra, Gordon Masnish, Brenda A. Coutts, Geoff Strickland, Monica Kehoe, Dustin Severtson, Roger A C Jones, Dominie Wright, Megan Jordan, Xinhua He, Eli Manyol, Song-Ai Nio, Imran Malik, Tina Botwright-Acuña, Len Wade, Nigel Metz, Linda Price, Dean A. Diepeveen, Leisa Armstrong, Peter Clarke, Doug Abrecht, Rudi Appels, Matthew Bellgard

Crop Updates

This session covers twenty four papers from different authors:

WHEAT AGRONOMY

1. Wheat variety performance in the Northern Agricultural Region in 2007, Christine Zaicou, Department of Agriculture and Food

2. Wheat variety performance on the Central Agricultural Region in 2007, Shahajahan Miyan, Department of Agriculture and Food

3. Response of wheat varieties to sowing time in the Great Southern and Lakes Region in 2007, Brenda Shackley and Steve Penny, Department of Agriculture and Food

4. Wheat variety performance in the South Coastal Region in 2007, Sarah Ellis, Department of Agriculture and Food

5. Flowering dates of wheat varieties in Western …

Covariate Adjustment For The Intention-To-Treat Parameter With Empirical Efficiency Maximization, Daniel B. Rubin, Mark J. Van Der Laan

U.C. Berkeley Division of Biostatistics Working Paper Series

In randomized experiments, the intention-to-treat parameter is defined as the difference in expected outcomes between groups assigned to treatment and control arms. There is a large literature focusing on how (possibly misspecified) working models can sometimes exploit baseline covariate measurements to gain precision, although covariate adjustment is not strictly necessary. In Rubin and van der Laan (2008), we proposed the technique of empirical efficiency maximization for improving estimation by forming nonstandard fits of such working models. Considering a more realistic randomization scheme than in our original article, we suggest a new class of working models for utilizing covariate information, show …

Medical Progress Depends On Animal Models - Doesn't It?, Robert A. J. Matthews

Validation of Animal Experimentation Collection

Animal models are widely recognized as being essential to the progress of medical science. In countering the critics’ arguments of the use of animals in medicine, one statement has acquired almost talismanic importance:

‘Virtually every medical achievement of the last century has depended directly or indirectly on research with animals.’

In this essay, the origins and justification of this oft-repeated statement are examined. Despite its endorsement by leading academic bodies, it is far from clear that the statement has been, or even could be, formally validated.

Infant Feeding Decisions Among Pregnant Black Wic Participants And The Role Of Peer Support, Astrid D. Mickens

Loma Linda University Electronic Theses, Dissertations & Projects

The purpose of this study was to identify the important factors that impact infant feeding decisions among Black women, and to determine whether peer support influences the relationship among theoretical constructs of the social learning theory. A convenience sample of 110 Black pregnant women, ages 18-45, attending Women, Infant and Children (WIC) clinics throughout Riverside and San Bernardino Counties were recruited to participate in the study through the Nutrition Services Department. Eligible participants included pregnant Black WIC clients in any stage of pregnancy.

The survey questions contained information about perceived support, cognitive knowledge, abilities and beliefs regarding breastfeeding. The goal …

The Expression Of Microrna Mir-107 Decreases Early In Alzheimer's Disease And May Accelerate Disease Progression Through Regulation Of Β-Site Amyloid Precursor Protein-Cleaving Enzyme 1, Wang-Xia Wang, Bernard W. Rajeev, Arnold J. Stromberg, Na Ren, Guiliang Tang, Qingwei Huang, Isidore Rigoutsos, Peter T. Nelson

Sanders-Brown Center on Aging Faculty Publications

MicroRNAs (miRNAs) are small regulatory RNAs that participate in posttranscriptional gene regulation in a sequence-specific manner. However, little is understood about the role(s) of miRNAs in Alzheimer's disease (AD). We used miRNA expression microarrays on RNA extracted from human brain tissue from the University of Kentucky Alzheimer's Disease Center Brain Bank with near-optimal clinicopathological correlation. Cases were separated into four groups: elderly nondemented with negligible AD-type pathology, nondemented with incipient AD pathology, mild cognitive impairment (MCI) with moderate AD pathology, and AD. Among the AD-related miRNA expression changes, miR-107 was exceptional because miR-107 levels decreased significantly even in patients with …

Rna Genome Annotation With A Focus On T. Brucei, Brett Bucci

Theses

The goal of this project is to identify untranslated regions (UTRs) and UTR-indicating patterns in the genome of T. brucei. T. brucei is an interesting organism, and as the cause of African sleeping sickness -- which infects 300,000-500,000 people and a significant number of cattle annually -- is currently the subject of considerable research. Using existing algorithms, several patterns have been found that may lead to more complete UTR annotations in the T. brucei genome. The most encouraging sequence is the 11-base sequence GAGGGIICG]TGGGG, which appears in five hypothetical genes near the tail. Discovery of several such sequences could guide …

Utr Prediction Programs For Trypanosoma Brucei, Maria Moutafis

Theses

In the past few years, the field of bioinformatics has seen a rapid increase in the need for use of various sequence analysis tools. As we advance in the fields of science and technology, new programs and software are constantly being developed in this field. Rapidly expanding gene sequence databases and rapidly evolving sequence analysis tools are providing researchers with ways to search for highly similar query sequences whether they are nucleotide, protein, or gene databases. This thesis will focus on sequence alignment tools, specifically concentrating on tools that help determine/predict non-coding regions of sequences also known as untranslated regions …

Cluster Mass Inference Method Via Random Field Theory, Hui Zhang, Thomas E. Nichols, Timothy D. Johnson

The University of Michigan Department of Biostatistics Working Paper Series

Cluster extent and voxel intensity are two widely used statistics in neuroimaging inference. Cluster extent is sensitive to spatially extended signals while voxel intensity is better for intense but focal signals. In order to leverage strength from both statistics, several nonparametric permutation methods have been proposed to combine the two methods. Simulation studies have shown that of the different cluster permutation methods, the cluster mass statistic is generally the best. However, to date, there is no parametric cluster mass inference available. In this paper, we propose a cluster mass inference method based on random field theory (RFT). We develop this …

Accommodating Covariates In Roc Analysis, Holly Janes, Gary M. Longton, Margaret Pepe

UW Biostatistics Working Paper Series

Classification accuracy is the ability of a marker or diagnostic test to discriminate between two groups of individuals, cases and controls, and is commonly summarized using the receiver operating characteristic (ROC) curve. In studies of classification accuracy, there are often covariates that should be incorporated into the ROC analysis. We describe three different ways of using covariate informa- tion. For factors that affect marker observations among controls, we present a method for covariate adjustment. For factors that affect discrimination (ie the ROC curve), we describe methods for mod- elling the ROC curve as a function of covariates. Finally, for factors …

Estimation And Comparison Of Receiver Operating Characteristic Curves, Margaret Pepe, Gary M. Longton, Holly Janes

UW Biostatistics Working Paper Series

The receiver operating characteristic (ROC) curve displays the capacity of a marker or diagnostic test to discriminate between two groups of subjects, cases versus controls. We present a comprehensive suite of Stata commands for performing ROC analysis. Non-parametric, semiparametric and parametric estimators are calculated. Comparisons between curves are based on the area or partial area under the ROC curve. Alternatively pointwise comparisons between ROC curves or inverse ROC curves can be made. Options to adjust these analyses for covariates, and to perform ROC regression are described in a companion article. We use a unified framework by representing the ROC curve …

A Bayesian Approach To Effect Estimation Accounting For Adjustment Uncertainty, Chi Wang, Giovanni Parmigiani, Ciprian Crainiceanu, Francesca Dominici

Johns Hopkins University, Dept. of Biostatistics Working Papers

Adjustment for confounding factors is a common goal in the analysis of both observational and controlled studies. The choice of which confounding factors should be included in the model used to estimate an effect of interest is both critical and uncertain. For this reason it is important to develop methods that estimate an effect, while accounting not only for confounders, but also for the uncertainty about which confounders should be included. In a recent article, Crainiceanu et al. (2008) have identified limitations and potential biases of Bayesian Model Averaging (BMA) (Raftery et al., 1997; Hoeting et al., 1999)when applied to …

Estimation Of Controlled Direct Effects, Sylvie Goetgeluk, Stijn Vansteelandt, Els Goetghebeur

Harvard University Biostatistics Working Paper Series

No abstract provided.

Using Regression Models To Analyze Randomized Trials: Asymptotically Valid Hypothesis Tests Despite Incorrectly Specified Models, Michael Rosenblum, Mark J. Van Der Laan

U.C. Berkeley Division of Biostatistics Working Paper Series

Regression models are often used to test for cause-effect relationships from data collected in randomized trials or experiments. This practice has deservedly come under heavy scrutiny, since commonly used models such as linear and logistic regression will often not capture the actual relationships between variables, and incorrectly specified models potentially lead to incorrect conclusions. In this paper, we focus on hypothesis test of whether the treatment given in a randomized trial has any effect on the mean of the primary outcome, within strata of baseline variables such as age, sex, and health status. Our primary concern is ensuring that such …

On The Merits Of Voxel-Based Morphometric Path-Analysis For Investigating Volumetric Mediation Of A Toxicant's Influence On Cognitive Function, Shu-Chih Su, Brian S. Caffo, Lynn E. Eberly, Elizabeth Garrett-Mayer, Walter F. Stewart, Sining Chen, David Yousem, Christos Davatzikos, Brian Schwartz

Johns Hopkins University, Dept. of Biostatistics Working Papers

We previously showed that lifetime cumulative lead dose, measured as lead concentration in the tibia bone by X-ray fluorescence, was associated with persistent and progressive declines in cognitive function and with decreases in MRI-based brain volumes in former lead workers. Moreover, larger region-specific brain volumes were associated with better cognitive function. These findings motivated us to explore a novel application of path analysis to evaluate effect mediation. Voxel-wise path analysis, at face value, represents the natural evolution of voxel-based morphometry methods to answer questions of mediation. Application of these methods to the former lead worker data demonstrated potential limitations in …

Geostatistical Inference Under Preferential Sampling, Peter J. Diggle, Raquel Menezes, Ting-Li Su

Johns Hopkins University, Dept. of Biostatistics Working Papers

Geostatistics involves the fitting of spatially continuous models to spatially discrete data (Chil`es and Delfiner, 1999). Preferential sampling arises when the process that determines the data-locations and the process being modelled are stochastically dependent. Conventional geostatistical methods assume, if only implicitly, that sampling is non-preferential. However, these methods are often used in situations where sampling is likely to be preferential. For example, in mineral exploration samples may be concentrated in areas thought likely to yield high-grade ore. We give a general expression for the likelihood function of preferentially sampled geostatistical data and describe how this can be evaluated approximately using …

Radiometric Clocks, Gary B. Hughes

Statistics

This paper provides and introduction to radioactivity, and how geologists exploit radioactive decay to determine the age of rocks.

Optimal Stopping And Free Boundary Characterizations For Some Brownian Control Problems, Amarjit Budhiraja, Kevin J. Ross

Statistics

A singular stochastic control problem with state constraints in twodimensions is studied. We show that the value function is C1 and its directional derivatives are the value functions of certain optimal stopping problems. Guided by the optimal stopping problem, we then introduce the associated no-action region and the free boundary and show that, under appropriate conditions, an optimally controlled process is a Brownian motion in the noaction region with reflection at the free boundary. This proves a conjecture of Martins, Shreve and Soner [SIAM J. Control Optim. 34 (1996) 2133–2171] on the form of an optimal control for this class …

Property Of Kelley For The Cartesian Products And Hyperspaces, W. J. Charatonik, J. J. Charatonik

Mathematics and Statistics Faculty Research & Creative Works

A continuum X having the property of Kelley is constructed such that neither X × [0, 1], nor the hyperspace C(X), nor small Whitney levels in C(X) have the property of Kelley. This answers several questions asked in the literature.

Iterated Oscillation Criteria For Delay Dynamic Equations Of First Order, B. Karpuz, O. Öcalan, Martin Bohner

Mathematics and Statistics Faculty Research & Creative Works

We obtain new sufficient conditions for the oscillation of all solutions of first-order delay dynamic equations on arbitrary time scales, hence combining and extending results for corresponding differential and difference equations. Examples, some of which coincide with well-known results on particular time scales, are provided to illustrate the applicability of our results.

Maximum Likelihood Estimation Methodology Comparison For The Three-Parameter Weibull Distribution With Applications To Offshore Oil Spills In The Gulf Of Mexico, William V. Harper, Thomas R. James, Ted G. Eschenbach, Leigh Slauson

Mathematics Faculty Scholarship

Maximum Likelihood estimation of the two-parameter Weibull distribution is straightforward; however, there are multiple methods for maximum likelihood estimation of the three-parameter Weibull. This paper presents an evaluation of these methods using four data sets including oil spill data from the Gulf of Mexico. Highlighted are fairly major differences in the estimated parameters between nine statistical packages. A VBA routine has been developed allowing practitioners to implement three-parameter Weibull maximum likelihood estimate within Excel. The code and support documentation are available free at http:faculty.otterbein.edu/WHarper.

Application Of The Probability Distribution Of Distances In A Layered Sphere To Electrostatic Energy, Neal Livesay

Theses & Honors Papers

This thesis works on a problem that involves calculating the total electrostatic interaction energy of two charged particles uniformly distributed in a sphere. It determines that traditional methods and the use of probability techniques yield equivalent results for the electrostatic energy in a charged layered sphere.

Evaluation Of Serotonin As A Feedback Inhibitor Of Lactation In The Bovine, L. L. Hernandez, C. M. Stiening, J. B. Wheelock, L. H. Baumgard, Anne M. Parkhurst, R. J. Collier

Department of Statistics: Faculty Publications

Serotonin (5-HT), a neurotransmitter synthesized from tryptophan, has been proposed as a feedback inhibitor of lactation. We determined that the gene coding for tryptophan hydroxylase 1, the rate-limiting enzyme for 5-HT synthesis, is expressed in bovine mammary epithelial cells in vitro and is upregulated by prolactin. In addition, 5-HT reduced the expression of α-lactalbumin and casein genes in vitro. Furthermore, inhibiting 5-HT synthesis with p-chlorophenylalanine or blocking the 5-HT receptor with methysergide (METH) increased milk protein gene expression. We then evaluated effects of intramammary 5-HT or METH infusion on production and milk composition in 6 multiparous Holstein cows. Cows …

J. K. Ghosh’S Contribution To Statistics: A Brief Outline, Bertrand Clarke, Subhashis Ghosal

Department of Statistics: Faculty Publications

Professor Jayanta Kumar Ghosh has contributed massively to various areas of Statistics over the last five decades. Here, we survey some of his most important contributions. In roughly chronological order, we discuss his major results in the areas of sequential analysis, foundations, asymptotics, and Bayesian inference. It is seen that he progressed from thinking about data points, to thinking about data summarization, to the limiting cases of data summarization in as they relate to parameter estimation, and then to more general aspects of modeling including prior and model selection.

An Ensemble Approach To Improved Prediction From Multitype Data, Jennifer Clarke

Department of Statistics: Faculty Publications

We have developed a strategy for the analysis of newly available binary data to improve outcome predictions based on existing data (binary or non-binary). Our strategy involves two modeling approaches for the newly available data, one combining binary covariate selection via LASSO with logistic regression and one based on logic trees. The results of these models are then compared to the results of a model based on existing data with the objective of combining model results to achieve the most accurate predictions. The combination of model predictions is aided by the use of support vector machines to identify subspaces of …

A Bayesian Test For Excess Zeros In A Zero-Inflated Power Series Distribution, Archan Bhattacharya, Bertrand S. Clarke, Gauri S. Datta

Department of Statistics: Faculty Publications

Power series distributions form a useful subclass of one-parameter discrete exponential families suitable for modeling count data. A zero-inflated power series distribution is a mixture of a power series distribution and a degenerate distribution at zero, with a mixing probability p for the degenerate distribution. This distribution is useful for modeling count data that may have extra zeros. One question is whether the mixture model can be reduced to the power series portion, corresponding to p = 0, or whether there are so many zeros in the data that zero inflation relative to the pure power series distribution must be …