Physical Sciences and Mathematics Commons^™

Corn-Soybean And Alternative Cropping Systems Effects On No 3 -N Leaching Losses In Subsurface Drainage Water, Rameshwar S. Kanwar, Richard M. Cruse, Mohammadreza Ghaffarzadeh, Allah Bakhsh, Douglas Karlen, Theodore B. Bailey

Douglas L Karlen

Alternative cropping systems can improve resource use efficiency, increase corn grain yield, and help in reducing negative impacts on the environment. A 6-yr (1993 to 1998) field study was conducted at the Iowa State University’s Northeastern Research Center near Nashua, Iowa, to evaluate the effects of non-traditional cropping systems [strip inter cropping (STR)-corn (Zea mays L.)/soybean (Glycine max L.)/oats (Avina sativa L.)]; alfalfa rotation (ROT)-3-yr (1993 to 1995) alfalfa (Medicago sativa L.) followed by corn in 1996, soybean in 1997, and oats in 1998), and traditional cropping system (corn after soybean (CS) and soybean after corn (SC) on the flow …

Cropping System Effects On No3-N Loss With Subsurface Drainage Water, Allah Bakhsh, Rameshwar S. Kanwar, Theodore B. Bailey, Cynthia A. Cambardella, Douglas Karlen, Thomas S. Colvin

Douglas L Karlen

An appropriate combination of tillage and nitrogen management practices will be necessary to develop sustainable farming practices. A six–year (1993–1998) field study was conducted on subsurface–drained Clyde–Kenyon–Floyd soils to quantify the impact of two tillage systems (chisel plow vs. no tillage) and two N fertilizer management practices (preplant single application vs. late–spring soil test based application) on nitrate–nitrogen (NO3–N) leaching loss with subsurface drain discharge from corn (Zea mays L.) soybean (Glycine max L.) rotation plots. Preplant injected urea ammonium nitrate solution (UAN) fertilizer was applied at the rate of 110 kg ha–1 to chisel plow and no–till corn plots, …

Effects Of Cost Sharing On Seeking Care For Serious And Minor Symptoms. Results Of A Randomized Controlled Trial, Martin Shapiro, John Ware, Cathy Sherbourne

Martin Shapiro

To estimate the effect of cost sharing on seeking care for serious and minor symptoms, we analyzed data for 3539 persons aged 17 to 61 from the Rand Health Insurance Experiment. Participants were randomly assigned to a free-care group or to insurance plans requiring them to pay part of the costs (cost-sharing group). Annual surveys were administered to determine if participants had serious and minor symptoms during the preceding month and whether they saw a physician. Serious symptoms were judged by a panel of physicians to warrant care in most instances; minor symptoms were judged neither to be severe nor …

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

Philip T. Reiss

No abstract provided.

An Omnibus Nonparametric Test Of Equality In Distribution For Unknown Functions, Alexander Luedtke, Marco Carone, Mark Van Der Laan

Alex Luedtke

We present a novel family of nonparametric omnibus tests of the hypothesis that two unknown but estimable functions are equal in distribution when applied to the observed data structure. We developed these tests, which represent a generalization of the maximum mean discrepancy tests described in Gretton et al. [2006], using recent developments from the higher-order pathwise differentiability literature. Despite their complex derivation, the associated test statistics can be expressed rather simply as U-statistics. We study the asymptotic behavior of the proposed tests under the null hypothesis and under both fixed and local alternatives. We provide examples to which our tests …

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 …

Penalized Functional Regression For Next-Generation Sequencing Studies, Olga A. Vsevolozhskaya

Olga A. Vsevolozhskaya

Recent technological advances equipped researchers with capabilities that go beyond traditional genotyping of loci known to be polymorphic in a general population. Genetic sequences of study participants can now be assessed directly. This capability removed technology-driven bias toward scoring predominantly common polymorphisms and let researchers reveal a wealth of rare and sample-specific variants. While the relative contributions of rare and common polymorphisms to trait variation are being debated, researchers are faced with the need for new statistical tools for simultaneous evaluation of all variants within a region. Several research groups demonstrated flexibility and good statistical power of the functional linear …

Neoadjuvant Or Adjuvant Therapy For Resectable Esophageal Cancer: A Systematic Review And Meta-Analysis, Richard Malthaner, Rebecca Wong, R. Rumble, Lisa Zuraw

Richard A. Malthaner

Background: Carcinoma of the esophagus is an aggressive malignancy with an increasing incidence. Its virulence, in terms of symptoms and mortality, justifies a continued search for optimal therapy. The large and growing number of patients affected, the high mortality rates, the worldwide geographic variation in practice, and the large body of good quality research warrants a systematic review with meta-analysis.

Methods: A systematic review and meta-analysis investigating the impact of neoadjuvant or adjuvant therapy on resectable thoracic esophageal cancer to inform evidence-based practice was produced.MEDLINE, CANCERLIT, Cochrane Library, EMBASE, and abstracts from the American Society of Clinical Oncology and the …

Neoadjuvant Or Adjuvant Therapy For Resectable Esophageal Cancer: A Clinical Practice Guideline, Richard Malthaner, Rebecca Wong, R. Rumble, Lisa Zuraw

Richard A. Malthaner

Background: Carcinoma of the esophagus is an aggressive malignancy with an increasing incidence. Its virulence, in terms of symptoms and mortality, justifies a continued search for optimal therapy. A clinical practice guideline was developed based on a systematic review investigating neoadjuvant or adjuvant therapy on resectable thoracic esophageal cancer. Methods: A systematic review with meta-analysis was developed and clinical recommendations were drafted. External review of the practice guideline report by practitioners in Ontario, Canada was obtained through a mailed survey, and incorporated. Final approval of the practice guideline was obtained from the Practice Guidelines Coordinating Committee. Results: The systematic review …

Neoadjuvant Or Adjuvant Therapy For Resectable Esophageal Cancer: A Systematic Review And Meta-Analysis, Richard Malthaner, Rebecca Wong, R. Rumble, Lisa Zuraw

Richard A. Malthaner

Background: Carcinoma of the esophagus is an aggressive malignancy with an increasing incidence. Its virulence, in terms of symptoms and mortality, justifies a continued search for optimal therapy. The large and growing number of patients affected, the high mortality rates, the worldwide geographic variation in practice, and the large body of good quality research warrants a systematic review with meta-analysis.

Methods: A systematic review and meta-analysis investigating the impact of neoadjuvant or adjuvant therapy on resectable thoracic esophageal cancer to inform evidence-based practice was produced.MEDLINE, CANCERLIT, Cochrane Library, EMBASE, and abstracts from the American Society of Clinical Oncology and the …

Neoadjuvant Or Adjuvant Therapy For Resectable Esophageal Cancer: A Clinical Practice Guideline, Richard Malthaner, Rebecca Wong, R. Rumble, Lisa Zuraw

Richard A. Malthaner

Background: Carcinoma of the esophagus is an aggressive malignancy with an increasing incidence. Its virulence, in terms of symptoms and mortality, justifies a continued search for optimal therapy. A clinical practice guideline was developed based on a systematic review investigating neoadjuvant or adjuvant therapy on resectable thoracic esophageal cancer.

Methods: A systematic review with meta-analysis was developed and clinical recommendations were drafted. External review of the practice guideline report by practitioners in Ontario, Canada was obtained through a mailed survey, and incorporated. Final approval of the practice guideline was obtained from the Practice Guidelines Coordinating Committee.

Results: The systematic review …

Nonparametric Methods For Doubly Robust Estimation Of Continuous Treatment Effects, Edward Kennedy, Zongming Ma, Matthew Mchugh, Dylan Small

Edward H. Kennedy

Continuous treatments (e.g., doses) arise often in practice, but available causal effect estimators require either parametric models for the effect curve or else consistent estimation of a single nuisance function. We propose a novel doubly robust kernel smoothing approach, which requires only mild smoothness assumptions on the effect curve and allows for misspecification of either the treatment density or outcome regression. We derive asymptotic properties and also discuss an approach for data-driven bandwidth selection. The methods are illustrated via simulation and in a study of the effect of nurse staffing on hospital readmissions penalties.

Semiparametric Causal Inference In Matched Cohort Studies, Edward Kennedy, Arvid Sjolander, Dylan Small

Edward H. Kennedy

Odds ratios can be estimated in case-control studies using standard logistic regression, ignoring the outcome-dependent sampling. In this paper we discuss an analogous result for treatment effects on the treated in matched cohort studies. Specifically, in studies where a sample of treated subjects is observed along with a separate sample of possibly matched controls, we show that efficient and doubly robust estimators of effects on the treated are computationally equivalent to standard estimators, which ignore the matching and exposure-based sampling. This is not the case for general average effects. We also show that matched cohort studies are often more efficient …

Set-Based Tests For Genetic Association In Longitudinal Studies, Zihuai He, Min Zhang, Seunggeun Lee, Jennifer A. Smith, Xiuqing Guo, Walter Palmas, Sharon L.R. Kardia, Ana V. Diez Roux, Bhramar Mukherjee

Jennifer McMahon

Genetic association studies with longitudinal markers of chronic diseases (e.g., blood pressure, body mass index) provide a valuable opportunity to explore how genetic variants affect traits over time by utilizing the full trajectory of longitudinal outcomes. Since these traits are likely influenced by the joint eff#11;ect of multiple variants in a gene, a joint analysis of these variants considering linkage disequilibrium (LD) may help to explain additional phenotypic variation. In this article, we propose a longitudinal genetic random field model (LGRF), to test the association between a phenotype measured repeatedly during the course of an observational study and a set …

A Latent Variable Transformation Model Approach For Exploring Dysphagia, Anna Snavely, David P. Harrington, Yi Li

David E. Harrington

No abstract provided.

Estimated Probability Of Becoming A Case Of Drug Dependence In Relation To Duration Of Drug-Taking Experience: A Function Approach, Olga A. Vsevolozhskaya, James C. Anthony

Olga A. Vsevolozhskaya

Measured as elapsed time from first use to dependence syndrome onset, the estimated 'induction interval' for cocaine clearly is short relative to the cannabis interval, but little is known about risk of becoming dependent when use persists. Published estimates for this facet of drug dependence epidemiology are from life histories elicited years after first use. To improve estimation, we turn to new data from nationally representative samples of newly incident drug users identified via probability sampling and confidential computer-assisted self-interviews for the National Surveys on Drug Use and Health, 2004-2013. Standardized modules assess first and most recent use, and dependence …

Wavelet-Domain Regression And Predictive Inference In Psychiatric Neuroimaging, Philip T. Reiss, Lan Huo, Yihong Zhao, Clare Kelly, R. Todd Ogden

Philip T. Reiss

An increasingly important goal of psychiatry is the use of brain imaging data to develop predictive models. Here we present two contributions to statistical methodology for this purpose. First, we propose and compare a set of wavelet-domain procedures for fitting generalized linear models with scalar responses and image predictors: sparse variants of principal component regression and of partial least squares, and the elastic net. Second, we consider assessing the contribution of image predictors over and above available scalar predictors, in particular via permutation tests and an extension of the idea of confounding to the case of functional or image predictors. …

Adaptive Pre-Specification In Randomized Trials With And Without Pair-Matching, Laura B. Balzer, Mark J. Van Der Laan, Maya L. Petersen

Laura B. Balzer

In randomized trials, adjustment for measured covariates during the analysis can reduce variance and increase power. To avoid misleading inference, the analysis plan must be pre-specified. However, it is unclear a priori which baseline covariates (if any) should be included in the analysis. Consider, for example, the Sustainable East Africa Research in Community Health (SEARCH) trial for HIV prevention and treatment. There are 16 matched pairs of communities and many potential adjustment variables, including region, HIV prevalence, male circumcision coverage and measures of community-level viral load. In this paper, we propose a rigorous procedure to data-adaptively select the adjustment set …

Assessing The Probability That A Finding Is Genuine For Large-Scale Genetic Association Studies, Chia-Ling Kuo, Olga A. Vsevolozhskaya, Dmitri V. Zaykin

Olga A. Vsevolozhskaya

Genetic association studies routinely involve massive numbers of statistical tests accompanied by P-values. Whole genome sequencing technologies increased the potential number of tested variants to tens of millions. The more tests are performed, the smaller P-value is required to be deemed significant. However, a small P-value is not equivalent to small chances of a spurious finding and significance thresholds may fail to serve as efficient filters against false results. While the Bayesian approach can provide a direct assessment of the probability that a finding is spurious, its adoption in association studies has been slow, due in part to the ubiquity …

Leukoaraiosis Predicts Poor 90-Day Outcome After Acute Large Cerebral Artery Occlusion, Nils Henninger, Eugene Lin, Stephen Baker, Ajay Wakhloo, Deepak Takhtani, Majaz Moonis

Nils Henninger

BACKGROUND: To date limited information regarding outcome-modifying factors in patients with acute intracranial large artery occlusion (ILAO) in the anterior circulation is available. Leukoaraiosis (LA) is a common finding among patients with ischemic stroke and has been associated with poor post-stroke outcomes but its association with ILAO remains poorly characterized. This study sought to clarify the contribution of baseline LA and other common risk factors to 90-day outcome (modified Rankin Scale, mRS) after stroke due to acute anterior circulation ILAO. METHODS: We retrospectively analyzed 1,153 consecutive patients with imaging-confirmed ischemic stroke during a 4-year period (2007-2010) at a single academic …

Teaching Of Biostatistics And Epidemiology In Medical Schools: How Do We Fare Compared With Developed Countries, Vijay Tiwari, Kuldeep Kumar, Sherin Raj

Kuldeep Kumar

Background Biostatistics is taught in almost all medical schools at the undergraduate and the postgraduate levels as a core course and is a prerequisite to epidemiology, public health and evidence-based medicine. However, it has to be taught in a different way in medical schools as compared with how it is taught to the students studying MSc (Biostatistics) or in the Statistics Department in universities. Objectives (1) To review the experience of teaching biostatistics in medical schools in India and compares the same with abroad (2) How best the curriculum can be designed as per the need of the medical students …

Targeted Estimation And Inference For The Sample Average Treatment Effect, Laura B. Balzer, Maya L. Petersen, Mark J. Van Der Laan

Laura B. Balzer

While the population average treatment effect has been the subject of extensive methods and applied research, less consideration has been given to the sample average treatment effect: the mean difference in the counterfactual outcomes for the study units. The sample parameter is easily interpretable and is arguably the most relevant when the study units are not representative of a greater population or when the exposure's impact is heterogeneous. Formally, the sample effect is not identifiable from the observed data distribution. Nonetheless, targeted maximum likelihood estimation (TMLE) can provide an asymptotically unbiased and efficient estimate of both the population and sample …

Surrogate Markers For Time-Varying Treatments And Outcomes, Jesse Hsu, Edward Kennedy, Jason Roy, Alisa Stephens-Shields, Dylan Small, Marshall Joffe

Edward H. Kennedy

A surrogate marker is a variable commonly used in clinical trials to guide treatment decisions when the outcome of ultimate interest is not available. A good surrogate marker is one where the treatment effect on the surrogate is a strong predictor of the effect of treatment on the outcome. We review the situation when there is one treatment delivered at baseline, one surrogate measured at one later time point, and one ultimate outcome of interest and discuss new issues arising when variables are time-varying. Most of the literature on surrogate markers has only considered simple settings with one treatment, one …

Challenges And Best Practices In Real-Time Prediction Of Infectious Disease: A Case Study Of Dengue In Thailand, Nicholas Reich, Stephen Lauer, Krzysztof Sakrejda, Sopon Iamsirithaworn, Soawapak Hinjoy, Paphanij Suangtho, Suthanun Suthachana, Hannah Clapham, Henrik Salje, Derek Cummings, Justin Lessler

Nicholas G Reich

Epidemics of communicable diseases place a huge burden on public health infrastructures across the world. Producing accurate and actionable forecasts of infectious disease incidence at short and long time scales will improve public health response to outbreaks. However, scientists and public health officials face many obstacles in trying to create accurate and actionable real-time forecasts of infectious disease incidence. Dengue is a mosquito-borne virus that annually infects over 400 million people worldwide. We developed a real-time forecasting model for dengue hemorrhagic fever in the 77 provinces of Thailand. We created an operational and computational infrastructure that generated multi-step predictions of …

Bayesian Function-On-Function Regression For Multi-Level Functional Data, Mark J. Meyer, Brent A. Coull, Francesco Versace, Paul Cinciripini, Jeffrey S. Morris

Jeffrey S. Morris

Medical and public health research increasingly involves the collection of more and more complex and high dimensional data. In particular, functional data|where the unit of observation is a curve or set of curves that are finely sampled over a grid -- is frequently obtained. Moreover, researchers often sample multiple curves per person resulting in repeated functional measures. A common question is how to analyze the relationship between two functional variables. We propose a general function-on-function regression model for repeatedly sampled functional data, presenting a simple model as well as a more extensive mixed model framework, along with multiple functional posterior …

Functional Regression, Jeffrey S. Morris

Jeffrey S. Morris

Functional data analysis (FDA) involves the analysis of data whose ideal units of observation are functions defined on some continuous domain, and the observed data consist of a sample of functions taken from some population, sampled on a discrete grid. Ramsay and Silverman's 1997 textbook sparked the development of this field, which has accelerated in the past 10 years to become one of the fastest growing areas of statistics, fueled by the growing number of applications yielding this type of data. One unique characteristic of FDA is the need to combine information both across and within functions, which Ramsay and …

Ordinal Probit Wavelet-Based Functional Models For Eqtl Analysis, Mark J. Meyer, Jeffrey S. Morris, Craig P. Hersh, Jarret D. Morrow, Christoph Lange, Brent A. Coull

Jeffrey S. Morris

Current methods for conducting expression Quantitative Trait Loci (eQTL) analysis are limited in scope to a pairwise association testing between a single nucleotide polymorphism (SNPs) and expression probe set in a region around a gene of interest, thus ignoring the inherent between-SNP correlation. To determine association, p-values are then typically adjusted using Plug-in False Discovery Rate. As many SNPs are interrogated in the region and multiple probe-sets taken, the current approach requires the fitting of a large number of models. We propose to remedy this by introducing a flexible function-on-scalar regression that models the genome as a functional outcome. The …

Estimating Controlled Direct Effects Of Restrictive Feeding Practices In The `Early Dieting In Girls' Study, Yeying Zhu, Debashis Ghosh, Donna L. Coffman, Jennifer S. Williams

Debashis Ghosh

In this article, we examine the causal effect of parental restrictive feeding practices on children’s weight status. An important mediator we are interested in is children’s self-regulation status. Traditional mediation analysis (Baron and Kenny, 1986) applies a structural equation modelling (SEM) approach and decomposes the intent-to-treat (ITT) effect into direct and indirect effects. More recent approaches interpret the mediation effects based on the potential outcomes framework. In practice, there often exist confounders that jointly influence the mediator and the outcome. Inverse probability weighting based on propensity scores are used to adjust for confounding and reduce the dimensionality of confounders simultaneously. …

A General Approach To Goodness Of Fit For U Processes, Debashis Ghosh, Youngjoo Cho

Debashis Ghosh

Goodness of fit procedures are essential tools for assessing model adequacy in statistics. In this work, we present a general theory and approach to goodness of fit techniques based on U-processes for the accelerated failure time (AFT) model. Many of the examples will focus on U-statistics of order 2. While many authors have proposed goodness of fit tests for U-statistics of order one, less has been developed for higher order U-statistics. In this paper, we propose goodness of fit tests for U-statistics of order 2 by using theoretical results from Nolan and Pollard (1987) and Nolan and Pollard (1988). We …

A Boosting Algorithm For Estimating Generalized Propensity Scores With Continuous Treatments, Yeying Zhu, Donna L. Coffman, Debashis Ghosh

Debashis Ghosh

In this article, we study the causal inference problem with a continuous treatment variable using propensity score-based methods. For a continuous treatment, the generalized propensity score is defined as the conditional density of the treatment-level given covariates (confounders). The dose–response function is then estimated by inverse probability weighting, where the weights are calculated from the estimated propensity scores. When the dimension of the covariates is large, the traditional nonparametric density estimation suffers from the curse of dimensionality. Some researchers have suggested a two-step estimation procedure by first modeling the mean function. In this study, we suggest a boosting algorithm to …