Biostatistics Commons^™

Learning From Data: Plant Breeding Applications Of Machine Learning, Alencar Xavier

Open Access Dissertations

Increasingly, new sources of data are being incorporated into plant breeding pipelines. Enormous amounts of data from field phenomics and genotyping technologies places data mining and analysis into a completely different level that is challenging from practical and theoretical standpoints. Intelligent decision-making relies on our capability of extracting from data useful information that may help us to achieve our goals more efficiently. Many plant breeders, agronomists and geneticists perform analyses without knowing relevant underlying assumptions, strengths or pitfalls of the employed methods. The study endeavors to assess statistical learning properties and plant breeding applications of supervised and unsupervised machine learning …

Diabetes Is Associated With Cerebrovascular But Not Alzheimer's Disease Neuropathology, Erin L. Abner, Peter T. Nelson, Richard J. Kryscio, Frederick A. Schmitt, David W. Fardo, Randall L. Woltjer, Nigel J. Cairns, Lei Yu, Hiroko H. Dodge, Chengjie Xiong, Kamal Masaki, Suzanne L. Tyas, David A. Bennett, Julie A. Schneider, Zoe Arvanitakis

Sanders-Brown Center on Aging Faculty Publications

INTRODUCTION: The relationship of diabetes to specific neuropathologic causes of dementia is incompletely understood.

METHODS: We used logistic regression to evaluate the association between diabetes and infarcts, Braak neurofibrillary tangle stage, and neuritic plaque score in 2365 autopsied persons. In a subset of >1300 persons with available cognitive data, we examined the association between diabetes and cognition using Poisson regression.

RESULTS: Diabetes increased odds of brain infarcts (odds ratio [OR] = 1.57, P < .0001), specifically lacunes (OR = 1.71, P < .0001), but not Alzheimer's disease neuropathology. Diabetes plus infarcts was associated with lower cognitive scores at end of life than infarcts or diabetes alone, and diabetes plus high level of Alzheimer's neuropathologic changes was associated with lower mini-mental state examination scores than the pathology alone.

DISCUSSION: This study supports the conclusions that diabetes increases the risk of cerebrovascular but not Alzheimer's disease pathology, and at least some of diabetes' relationship to …

Multilevel Models For Longitudinal Data, Aastha Khatiwada

Electronic Theses and Dissertations

Longitudinal data arise when individuals are measured several times during an ob- servation period and thus the data for each individual are not independent. There are several ways of analyzing longitudinal data when different treatments are com- pared. Multilevel models are used to analyze data that are clustered in some way. In this work, multilevel models are used to analyze longitudinal data from a case study. Results from other more commonly used methods are compared to multilevel models. Also, comparison in output between two software, SAS and R, is done. Finally a method consisting of fitting individual models for each …

Apoe Ε4 Allele Modifies The Association Of Lead Exposure With Age-Related Cognitive Decline In Older Individuals, Diddier Prada, Elena Colicino, Melinda C. Power, Marc G Weisskopf, Jia Zhong, Lifang Hou, Avron Spiro, Pantel Vokonas, Plus 4 Others...

Epidemiology Faculty Publications

BACKGROUND: Continuing chronic and sporadic high-level of lead exposure in some regions in the U.S. has directed public attention to the effects of lead on human health. Long-term lead exposure has been associated with faster cognitive decline in older individuals; however, genetic susceptibility to lead-related cognitive decline during aging has been poorly studied.

METHODS: We determined the interaction of APOE-epsilon variants and environmental lead exposure in relation to age-related cognitive decline. We measured tibia bone lead by K-shell-x-ray fluorescence, APOE-epsilon variants by multiplex PCR and global cognitive z-scores in 489 men from the VA-Normative Aging Study. To determine global cognitive …

Retention Of Mothers And Infants In The Prevention Of Mother-To-Child Transmission Of Hiv Programme Is Associated With Individual And Facility-Level Factors In Rwanda., Godfrey B Woelk, Dieudonne Ndatimana, Sally Behan, Martha Mukaminega, Epiphanie Nyirabahizi, Heather J. Hoffman, Placidie Mugwaneza, Muhayimpundu Ribakare, Anouk Amzel, B Ryan Phelps

Epidemiology Faculty Publications

OBJECTIVES: Investigate levels of retention at specified time periods along the prevention of mother-to-child transmission (PMTCT) cascade among mother-infant pairs as well as individual- and facility-level factors associated with retention.

METHODS: A retrospective cohort of HIV-positive pregnant women and their infants attending five health centres from November 2010 to February 2012 in the Option B programme in Rwanda was established. Data were collected from several health registers and patient follow-up files. Additionally, informant interviews were conducted to ascertain health facility characteristics. Generalized estimating equation methods and modelling were utilized to estimate the number of mothers attending each antenatal care visit …

Variable Selection For Estimating The Optimal Treatment Regimes In The Presence Of A Large Number Of Covariate, Baqun Zhang, Min Zhang

The University of Michigan Department of Biostatistics Working Paper Series

Most of existing methods for optimal treatment regimes, with few exceptions, focus on estimation and are not designed for variable selection with the objective of optimizing treatment decisions. In clinical trials and observational studies, often numerous baseline variables are collected and variable selection is essential for deriving reliable optimal treatment regimes. Although many variable selection methods exist, they mostly focus on selecting variables that are important for prediction (predictive variables) instead of variables that have a qualitative interaction with treatment (prescriptive variables) and hence are important for making treatment decisions. We propose a variable selection method within a general classification …

Practical Targeted Learning From Large Data Sets By Survey Sampling, Patrice Bertail, Antoine Chambaz, Emilien Joly

U.C. Berkeley Division of Biostatistics Working Paper Series

We address the practical construction of asymptotic confidence intervals for smooth (i.e., pathwise differentiable), real-valued statistical
parameters by targeted learning from independent and identically
distributed data in contexts where sample size is so large that it poses
computational challenges. We observe some summary measure of all data and select a sub-sample from the complete data set by Poisson rejective sampling with unequal inclusion probabilities based on the summary measures. Targeted learning is carried out from the easier to handle sub-sample. We derive a central limit theorem for the targeted minimum loss estimator (TMLE) which enables the construction of …

Improved Estimation Of Optimal Cut-Off Point Associated With Youden Index Using Ranked Set Sampling, Jingjing Yin, Hani M. Samawi, Daniel Linder

Biostatistics: Faculty Publications

A diagnostic cut-off point of a biomarker measurement is needed for classifying a random subject to be either diseased or healthy. However, the cut-off point is usually unknown and needs to be estimated by some optimization criteria. One important criterion is the Youden index, which has been widely adopted in practice. The Youden index, which is defined as the maximum of (sensitivity + specificity −1), directly measures the largest total diagnostic accuracy a biomarker can achieve. Therefore, it is desirable to estimate the optimal cut-off point associated with the Youden index. Sometimes, taking the actual measurements of a biomarker is …

Novel Methods For Analyzing Longitudinal Data With Measurement Error In The Time Variable, Caroline Munindi Mulatya

Theses and Dissertations

In some longitudinal studies, the observed time points are often confounded with measurement error due to the sampling conditions, resulting into data with measurement error in the time variable. This type of data occurs mainly in observational studies when the onset of a longitudinal process is unknown or in clinical trials when individual visits do not take place as specified by the study protocol, but are often rounded to coincide with the study protocol. Methodological and inferential implications of error in time varying covariates for both linear and nonlinear models have been studied widely. In this dissertation, we shift attention …

Scalable Collaborative Targeted Learning For High-Dimensional Data, Cheng Ju, Susan Gruber, Samuel D. Lendle, Antoine Chambaz, Jessica M. Franklin, Richard Wyss, Sebastian Schneeweiss, Mark J. Van Der Laan

U.C. Berkeley Division of Biostatistics Working Paper Series

Robust inference of a low-dimensional parameter in a large semi-parametric model relies on external estimators of infinite-dimensional features of the distribution of the data. Typically, only one of the latter is optimized for the sake of constructing a well behaved estimator of the low-dimensional parameter of interest. Optimizing more than one of them for the sake of achieving a better bias-variance trade-off in the estimation of the parameter of interest is the core idea driving the C-TMLE procedure.

The original C-TMLE procedure can be presented as a greedy forward stepwise algorithm. It does not scale well when the number $p$ …

Propensity Score Prediction For Electronic Healthcare Databases Using Super Learner And High-Dimensional Propensity Score Methods, Cheng Ju, Mary Combs, Samuel D. Lendle, Jessica M. Franklin, Richard Wyss, Sebastian Schneeweiss, Mark J. Van Der Laan

U.C. Berkeley Division of Biostatistics Working Paper Series

The optimal learner for prediction modeling varies depending on the underlying data-generating distribution. Super Learner (SL) is a generic ensemble learning algorithm that uses cross-validation to select among a "library" of candidate prediction models. The SL is not restricted to a single prediction model, but uses the strengths of a variety of learning algorithms to adapt to different databases. While the SL has been shown to perform well in a number of settings, it has not been thoroughly evaluated in large electronic healthcare databases that are common in pharmacoepidemiology and comparative effectiveness research. In this study, we applied and evaluated …

Tmle For Marginal Structural Models Based On An Instrument, Boriska Toth, Mark J. Van Der Laan

U.C. Berkeley Division of Biostatistics Working Paper Series

We consider estimation of a causal effect of a possibly continuous treatment when treatment assignment is potentially subject to unmeasured confounding, but an instrumental variable is available. Our focus is on estimating heterogeneous treatment effects, so that the treatment effect can be a function of an arbitrary subset of the observed covariates. One setting where this framework is especially useful is with clinical outcomes. Allowing the causal dose-response curve to depend on a subset of the covariates, we define our parameter of interest to be the projection of the true dose-response curve onto a user-supplied working marginal structural model. We …

Predictors Of Neonatal Abstinence Syndrome In Buprenorphine Exposed Newborn: Can Cord Blood Buprenorphine Metabolite Levels Help?, Darshan Shah, Stacy Brown, Nick Hagemeier, Shimin Zheng, Amy Kyle, Jason Pryor, Nilesh Dankhara, Piyuesh Singh

ETSU Faculty Works

Background

Buprenorphine is a semi-synthetic opioid used for the treatment of opioid dependence. Opioid use, including buprenorphine, has been increasing in recent years, in the general population and in pregnant women. Consequently, there has been a rise in frequency of neonatal abstinence syndrome (NAS), associated with buprenorphine use during pregnancy. The purpose of this study was to investigate correlations between buprenorphine and buprenorphine-metabolite concentrations in cord blood and onset of NAS in buprenorphine exposed newborns.

Methods

Nineteen (19) newborns who met inclusion criteria were followed after birth until discharge in a double-blind non-intervention study, after maternal consent. Cord blood and …

A Powerful Statistical Framework For Generalization Testing In Gwas, With Application To The Hchs/Sol, Tamar Sofer, Ruth Heller, Marina Bogomolov, Christy L. Avery, Mariaelisa Graff, Kari E. North, Alex Reiner, Timothy A. Thornton, Kenneth Rice, Yoav Benjamini, Cathy C. Laurie, Kathleen F. Kerr

UW Biostatistics Working Paper Series

In GWAS, “generalization” is the replication of genotype-phenotype association in a population with different ancestry than the population in which it was first identified. The standard for reporting findings from a GWAS requires a two-stage design, in which discovered associations are replicated in an independent follow-up study. Current practices for declaring generalizations rely on testing associations while controlling the Family Wise Error Rate (FWER) in the discovery study, then separately controlling error measures in the follow-up study. While this approach limits false generalizations, we show that it does not guarantee control over the FWER or False Discovery Rate (FDR) of …

Total Versus Partial Splenectomy In Pediatric Hereditary Spherocytosis: A Systematic Review And Meta-Analysis, Leonardo Guizzetti

Epidemiology and Biostatistics Publications

To compare the clinical effectiveness of total (TS) or partial (PS) splenectomy in pediatric hereditary spherocytosis, a systematic review and meta-analysis was performed (PROSPERO registration CRD42015030056). There were 14 observational studies comparing pre- and post- operative hematologic parameters. Secondary outcomes include in-hospital infections, surgical complications, symptomatic recurrence and biliary disease. TS is more effective than PS to increase hemoglobin (3.6 g/dL vs 2.2 g/dL) and reduce reticulocytes (12.5% vs 6.5%) after one year; outcomes following PS are stable for at least 6 years. There were no cases of overwhelming post-splenectomy sepsis. A population-based patient registry is needed for long-term follow-up.

Dealing With Zero-Numerators In Estimating Drug-Dependence Chances: A Bayesian Approach, Olga A. Vsevolozhskaya, Fernando A. Wagner, James C. Anthony

Biostatistics Presentations

Aims: At CPDD 2015, we applied parametric Hill functions to estimate the probability of drug dependence in relation to the duration of drug-taking experience. A problem we and others have encountered in the estimation of risk of becoming a drug dependence case is an observed point estimate of zero – the so-called “zero-numerator problem.” This problem can be easily observed in certain low risk subgroups even when the sample is large (e.g., the incidence of heroin dependence among 12 year old newly incident heroin users) or with small subgroup sample sizes. In these instances, tan observed zero point estimate …

Mapping Morels: Predicting The Locations Of Morchella Species Through Environmental Factors Using The Gis System, Emily M. Stanevicius

Celebration of Learning

Morel mushrooms, Morechella esculenta and M. deliciosa, are known delicacies across the globe, ranging from exquisite dishes in French cuisine to Eastern palates such as Japanese Matsutake. According to literature, true morels diverged as their own genus about 129 million years, again which has led to the development of more than 177 species and have been part of the human diet since their beginning. However, the elusiveness of morels has contributed to the mushrooms infamy for rarity, and has even been known to sell for more than $40 per pound. This project seeks to aid in the search for morels …

Putting Prep Into Practice: Lessons Learned From Early-Adopting U.S. Providers' Firsthand Experiences Providing Hiv Pre-Exposure Prophylaxis And Associated Care, S. K. Calabrese, Manya Magnus, K. H. Mayer, D. S. Krakower, A. I. Eldahan, L. A. Gaston Hawkins, +5 Additional Authors

Epidemiology Faculty Publications

Optimizing access to HIV pre-exposure prophylaxis (PrEP), an evidence-based HIV prevention resource, requires expanding healthcare providers' adoption of PrEP into clinical practice. This qualitative study explored PrEP providers' firsthand experiences relative to six commonly-cited barriers to prescription-financial coverage, implementation logistics, eligibility determination, adherence concerns, side effects, and anticipated behavior change (risk compensation)-as well as their recommendations for training PrEP-inexperienced providers. U.S.-based PrEP providers were recruited via direct outreach and referral from colleagues and other participants (2014-2015). One-on-one interviews were conducted in person or by phone, transcribed, and analyzed. The sample (n = 18) primarily practiced in the Northeastern (67%) or …

Partner Interfering Behaviors Affecting Cancer Quality Of Life, Ann L. Coker, Diane R. Follingstad, Lisandra S. Garcia, Heather M. Bush

Obstetrics and Gynecology Faculty Publications

Objective: Because partners are an important and unpaid resource in cancer care, understanding how destructive, controlling or interfering partner behaviors influence women's cancer care may be particularly relevant for health care providers seeking to provide cancer care and enhance recovery. Using a new measure of partner interfering behaviors in cancer care (PIB-C), we investigated whether women with a recent cancer diagnosis who additionally endorsed any PIB-C would report (a) more symptoms of depression and stress, and (b) lower Functional Assessment of Cancer Therapy (FACT-G) and lower Functional Assessment of Chronic Illness Therapy-Spiritual Well-being (FACIT-SP) scale scores indicating poorer quality of …

Housewives’ Compliance In Reading Food Labels In Gorontalo City, Imran Tumenggung, Lucky Herawati, Sofyawati Talibo

Kesmas

Di Indonesia, masalah label pada kemasan makanan kurang mendapat perhatian konsumen. Penelitian ini bertujuan untuk mempelajari determinan kepatuhan membaca label pada kemasan makanan oleh ibu rumah tangga di Kota Gorontalo. Penelitian dengan metode survei ini dilakukan dari bulan Juni sampai Agustus 2013. Data dikumpulkan secara potong lintang dengan menggunakan angket. Variabel terikat adalah kepatuhan membaca label pada kemasan makanan yang terdiri dari label informasi nilai gizi, komposisi makanan, masa kedaluwarsa, harga, dan status halal. Variabel bebas adalah usia, tingkat pendidikan, dan keterpaparan dengan media informasi. Besar sampel 262 orang ditentukan secara accidental technique. Analisis data menggunakan uji kai kuadrat. Hasil …