The Association Between Prenatal Food Insecurity and Breastfeeding Initiation and Exclusive Breastfeeding Duration: A Longitudinal Study Using Oregon PRAMS and PRAMS-2, 2008-2015.

In the United States, 11.1% of households experience food insecurity; however, pregnant women are disproportionately affected. Maternal food insecurity may affect infant feeding practices, for example, through being a source of chronic stress that may alter the decision to initiate and continue breastfeeding.

Evaluation of Risk Prediction with Hierarchical Data: Dependency Adjusted Confidence Intervals for the AUC.

The area under the true ROC curve (AUC) is routinely used to determine how strongly a given model discriminates between the levels of a binary outcome. Standard inference with the AUC requires that outcomes be independent of each other. To overcome this limitation, a method was developed for the estimation of the variance of the AUC in the setting of two-level hierarchical data using probit-transformed prediction scores generated from generalized estimating equation models, thereby allowing for the application of inferential methods.

Estimation and testing for clustered interval-censored bivariate survival data with application using the semi-parametric version of the Clayton-Oakes model.

The Kaplan-Meier estimator is ubiquitously used to estimate survival probabilities for time-to-event data. It is nonparametric, and thus does not require specification of a survival distribution, but it does assume that the risk set at any time t consists of independent observations. This assumption does not hold for data from paired organ systems such as occur in ophthalmology (eyes) or otolaryngology (ears), or for other types of clustered data.

Semiparametric predictive inference for failure data using first-hitting-time threshold regression.

The progression of disease for an individual can be described mathematically as a stochastic process. The individual experiences a failure event when the disease path first reaches or crosses a critical disease level. This happening defines a failure event and a first hitting time or time-to-event, both of which are important in medical contexts.

Accounting for delayed entry into observational studies and clinical trials: length-biased sampling and restricted mean survival time.

Individuals in many observational studies and clinical trials for chronic diseases are enrolled well after onset or diagnosis of their disease. Times to events of interest after enrollment are therefore residual or left-truncated event times. Individuals entering the studies have disease that has advanced to varying extents.

Group sequential design for randomized trials using "first hitting time" model.

Group sequential design (GSD) has become a popular choice in recent clinical trials as it improves trial efficiency by providing options for early termination. The implementation of traditional tests for survival analysis (eg, the log-rank test and the Cox proportional hazard (PH) model) in the GSD setting has been widely discussed. The PH assumption is required for conventional (sequential) design, it is, however, often violated in practice.

Variable Selection in Threshold Regression Model with Applications to HIV Drug Adherence Data.

The threshold regression model is an effective alternative to the Cox proportional hazards regression model when the proportional hazards assumption is not met. This paper considers variable selection for threshold regression. This model has separate regression functions for the initial health status and the speed of degradation in health.

Drug overdose mortality is associated with employment status and occupation in the National Longitudinal Mortality Study.

Background: Since 1999, over 702,000 people in the US have died of a drug overdose, and the drug overdose death rate has increased from 6.2 to 21.8 per 100,000.

Order-restricted inference for clustered ROC data with application to fingerprint matching accuracy.

Receiver operating characteristic (ROC) curve is commonly used to evaluate and compare the accuracy of classification methods or markers. Estimating ROC curves has been an important problem in various fields including biometric recognition and diagnostic medicine. In real applications, classification markers are often developed under two or more ordered conditions, such that a natural stochastic ordering exists among the observations.

Two-sample test for correlated data under outcome-dependent sampling with an application to self-reported weight loss data.

Standard methods for two-sample tests such as the t-test and Wilcoxon rank sum test may lead to incorrect type I errors when applied to longitudinal or clustered data. Recent alternatives of two-sample tests for clustered data often require certain assumptions on the correlation structure and/or noninformative cluster size. In this paper, based on a novel pseudolikelihood for correlated data, we propose a score test without knowledge of the correlation structure or assuming data missingness at random.

RNASeqDesign: A framework for RNA-Seq genome-wide power calculation and study design issues.

Massively parallel sequencing (a.k.a.

Generational trends and patterns in readmission within a statewide cohort of clients receiving heroin use disorder treatment in Maryland, 2007-2013.

The recent rise in opioid-related overdose deaths stresses the importance of understanding how heroin use disorders persist and what interventions are best suited for treating these illnesses. Trends show that there are diverse pathways leading to heroin use disorder that span multiple generations, but little is known about how different generations utilize and respond to treatment. This study provides insight into treatment utilization for young, middle-aged, and older adults by examination of an unusually rich longitudinal dataset of substance use disorder clients in Maryland who were treated for heroin use.

Using threshold regression to analyze survival data from complex surveys: With application to mortality linked NHANES III Phase II genetic data.

The Cox proportional hazards (PH) model is a common statistical technique used for analyzing time-to-event data. The assumption of PH, however, is not always appropriate in real applications. In cases where the assumption is not tenable, threshold regression (TR) and other survival methods, which do not require the PH assumption, are available and widely used.

Meta-analysis of quantitative pleiotropic traits for next-generation sequencing with multivariate functional linear models.

To analyze next-generation sequencing data, multivariate functional linear models are developed for a meta-analysis of multiple studies to connect genetic variant data to multiple quantitative traits adjusting for covariates. The goal is to take the advantage of both meta-analysis and pleiotropic analysis in order to improve power and to carry out a unified association analysis of multiple studies and multiple traits of complex disorders. Three types of approximate F -distributions based on Pillai-Bartlett trace, Hotelling-Lawley trace, and Wilks's Lambda are introduced to test for association between multiple quantitative traits and multiple genetic variants.

A simple and robust method for multivariate meta-analysis of diagnostic test accuracy.

Meta-analysis of diagnostic test accuracy often involves mixture of case-control and cohort studies. The existing bivariate random-effects models, which jointly model bivariate accuracy indices (e.g.

Association between community socioeconomic factors, animal feeding operations, and campylobacteriosis incidence rates: Foodborne Diseases Active Surveillance Network (FoodNet), 2004-2010.

Background: Campylobacter is a leading cause of foodborne illness in the United States. Campylobacter infections have been associated with individual risk factors, such as the consumption of poultry and raw milk. Recently, a Maryland-based study identified community socioeconomic and environmental factors that are also associated with campylobacteriosis rates.

A threshold regression model to predict return to work after traumatic limb injury.

Objective: The study aims to examine the severity of initial impairment and recovery rate of return-to-work (RTW) predictors among workers with traumatic limb injury.

Methods: This 2-year prospective cohort study recruited 1124 workers with traumatic limb injury during the first 2 weeks of hospital admission. Baseline data were obtained by questionnaire and chart review.

Transition outcomes for young adults with disabilities.

Purpose: Transition to adulthood can be very challenging for children with special health care needs (CSHCN) especially for those with disabilities who experience functional limitations in activities at home, in school, and in the community. The study examined the transition outcomes in areas of health, education, and independent living for young adult with special health care needs (YASHCN) with disabilities.

Method: The study is a secondary data analysis of the 2007 Survey of Adult Transition and Health (SATH).

Acceptability and performance of the menstrual cup in South Africa: a randomized crossover trial comparing the menstrual cup to tampons or sanitary pads.

Background: In low-income settings, many women and girls face activity restrictions during menses, owing to lack of affordable menstrual products. The menstrual cup (MC) is a nonabsorbent reusable cup that collects menstrual blood. We assessed the acceptability and performance of the MPower® MC compared to pads or tampons among women in a low-resource setting.

A model for time to fracture with a shock stream superimposed on progressive degradation: the Study of Osteoporotic Fractures.

Osteoporotic hip fractures in the elderly are associated with a high mortality in the first year following fracture and a high incidence of disability among survivors. We study first and second fractures of elderly women using data from the Study of Osteoporotic Fractures. We present a new conceptual framework, stochastic model, and statistical methodology for time to fracture.

Semiparametric varying-coefficient model for interval censored data with a cured proportion.

Varying-coefficient models have claimed an increasing portion of statistical research and are now applied to censored data analysis in medical studies. We incorporate such flexible semiparametric regression tools for interval censored data with a cured proportion. We adopted a two-part model to describe the overall survival experience for such complicated data.

Impact of rurality, broiler operations, and community socioeconomic factors on the risk of campylobacteriosis in Maryland.

Objectives: We evaluated the combined impact of community-level environmental and socioeconomic factors on the risk of campylobacteriosis.

Methods: We obtained Campylobacter case data (2002-2010; n = 3694) from the Maryland Foodborne Diseases Active Surveillance Network. We obtained community-level socioeconomic and environmental data from the 2000 US Census and the 2007 US Census of Agriculture.

Sex-specific effects of exercise ancestry on metabolic, morphological and gene expression phenotypes in multiple generations of mouse offspring.

Early life and preconception environmental stimuli can affect adult health-related phenotypes. Exercise training is an environmental stimulus affecting many systems throughout the body and appears to alter offspring phenotypes. The aim of this study was to examine the influence of parental exercise training, or 'exercise ancestry', on morphological and metabolic phenotypes in two generations of mouse offspring.

Logic minimization and rule extraction for identification of functional sites in molecular sequences.

Background: Logic minimization is the application of algebraic axioms to a binary dataset with the purpose of reducing the number of digital variables and/or rules needed to express it. Although logic minimization techniques have been applied to bioinformatics datasets before, they have not been used in classification and rule discovery problems. In this paper, we propose a method based on logic minimization to extract predictive rules for two bioinformatics problems involving the identification of functional sites in molecular sequences: transcription factor binding sites (TFBS) in DNA and O-glycosylation sites in proteins.