Biostatistics Commons^™

Efektivitas Dan Efisiensi Sistem Informasi Keluarga Berencana Di Puskesmas, Aragar Putri, Besral Besral

Kesmas

Efisiensi dan efektivitas sistem informasi keluarga berencana (KB)-kesehatan yang telah disosialisasikan sejak tahun 2007 dibandingkan dengan sistem yang lama belum diketahui. Suatu penelitian survei dilakukan di empat provinsi, yaitu DKI Jakarta, Lampung, Kalimatan Tengah, dan Bali. Di tiap provinsi dipilih dua kabupaten/kota dan pada tiap kabupaten/kota dipilih dua puskesmas (kecamatan) yang sudah menerapkan sistem informasi KB-kesehatan tersebut. Pengumpulan data dilakukan pada bulan Juni-September 2008. Penelitian ini menemukan bahwa efektivitas dan efisiensi sistem informasi KB yang baru cukup baik, 77,8% responden menyatakan lebih efektif atau sangat lebih efektif dan 66,7% responden menyatakan lebih efisien atau sangat lebih efisien dibandingkan dengan sistem …

Bate Curve In Assessment Of Clinical Utility Of Predictive Biomarkers, Xiao-Hua Zhou, Yunbei Ma

UW Biostatistics Working Paper Series

In this paper, for time-to-event data, we propose a new statistical framework for casual inference in evaluating clinical utility of predictive biomarkers and in selecting an optimal treatment for a particular patient. This new casual framework is based on a new concept, called Biomarker Adjusted Treatment Effect (BATE) curve, which can be used to represent the clinical utility of a predictive biomarker and select an optimal treatment for one particular patient. We then propose semi-parametric methods for estimating the BATE curves of biomarkers and establish asymptotic results of the proposed estimators for the BATE curves. We also conduct extensive simulation …

Tmle: An R Package For Targeted Maximum Likelihood Estimation, Susan Gruber, Mark J. Van Der Laan

U.C. Berkeley Division of Biostatistics Working Paper Series

Targeted maximum likelihood estimation (TMLE) presents an approach for construction of an efficient double-robust semi-parametric substitution estimator of a target feature of the data generating distribution, such as a statistical association measure or a causal effect parameter. tmle is a recently developed R package that implements TMLE for estimation of the effect of a binary treatment at a single point in time on an outcome of interest, controlling for user supplied covariates: the additive treatment effect, the relative risk, the odds ratio. The package allows outcome data with missingness, and experimental units that contribute repeated records of the point-treatment data …

Causal Inference Under Multiple Versions Of Treatment, Tyler J. Vanderweele, Miguel A. Hernan

COBRA Preprint Series

In this article we discuss the no-multiple-versions-of-treatment assumption and extend the potential outcomes framework to accommodate causal inference under violations of this assumption. A variety of examples are discussed in which the assumption may be violated. Identification results are provided for the overall treatment effect and the effect of treatment on the treated when multiple versions of treatment are present and also for the causal effect comparing a version of one treatment to some other version of the same or a different treatment. Further identification and interpretative results are given for cases in which a treatment variable is dichotomized to …

Non-Homogeneous Markov Process Models With Incomplete Observations: Application To A Dementia Disease Study, Xiao-Hua Zhou, Baojiang Chen

UW Biostatistics Working Paper Series

Identifying risk factors for transition rates among normal cognition, mildly cognitive impairment, dementia and death in an Alzheimer's disease study is very important. It is known that transition rates among these states are strongly time dependent. While Markov process models are often used to describe these disease progressions, the literature mainly focuses on time homogeneous processes, and limited tools are available for dealing with non-homogeneity. Further, patients may choose when they want to visit the clinics, which creates informative observations. In this paper, we develop methods to deal with non-homogeneous Markov processes through time scale transformation when observation times are …

Doubly Robust Estimates For Binary Longitudinal Data Analysis With Missing Response And Missing Covariates, Baojiang Chen, Xiao-Hua Zhou

UW Biostatistics Working Paper Series

Longitudinal studies often feature incomplete response and covariate data. Likelihood-based methods such as the EM algorithm give consistent estimators for model parameters when data are missing at random provided that the response model and the missing covariate model are correctly specified; but we do not need to specify the missing data mechanism. An alternative method is the weighted estimating equation which gives consistent estimators if the missing data and response models are correctly specified; but we do not need to specify the distribution of the covariates that have missing values. In this paper we develop a doubly robust estimation method …

Semiparametric Estimation Of The Covariate-Specific Roc Curve In Presence Of Ignorable Verification Bias, Danping Liu, Xiao-Hua Zhou

UW Biostatistics Working Paper Series

Covariate-specific ROC curves are often used to evaluate the classification accuracy of a medical diagnostic test or a biomarker, when the accuracy of the test is associated with certain covariates. In many large-scale screening tests, the gold standard is subject to missingness due to high cost or harmfulness to the patient. In this paper, we propose a semiparametric estimation method for the covariate-specific ROC curves with a partial missing gold standard. A location-scale model is constructed for the test result to model the covariates' effect, but the residual distributions are left unspecified. Thus the baseline and link functions of the …

Evaluating Markers For Treatment Selection Based On Survival Time, Xiao Song, Xiao-Hua Zhou

UW Biostatistics Working Paper Series

For many medical conditions there are several treatment options available to patients. We consider evaluating markers based on a simple treatment selection policy that incorporates information on the patient's marker value exceeding a threshold. Although traditional regression methods may assess the effect of the marker and treatment on outcomes, it is appealing to quantify more directly the potential impact on the population of using the marker to select treatment. A useful tool is the selection impact (SI) curve proposed by Song and Pepe (2004, \textit{Biometrics} \textbf{60}, 874--883) for binary outcomes. However, this approach does not deal with continuous outcomes, nor …

Angiogenic Biomarkers For Risk Stratification In Women With Suspected Preeclampsia, Andreea Balan, Heather Young, Linda Ojo, Jennifer Keller, Sharon Maynard

Epidemiology Faculty Posters and Presentations

This poster presents the results of a single-center prospective cohort study of 315 pregnant women who presented to George Washington University Hospital Labor and Delivery service with a clinical suspicion of preeclampsia between February 2007 and November 2011. Informed consent was obtained. Baseline demographic information and medical history was collected on each patient including maternal age, ethnicity, body mass index, tobacco and other substance use, gestational age, medical problems and obstetric history. Serum samples were obtained from each enrolled subject within 24 hours of admission, and sFlt1, PlGF and sEng ELISA assays were performed in duplicate by a blinded laboratory …

Analysis Of Differential Gene Expression And Alternative Splicing In The Liver And Gastrointestinal Tract In The Lactating Rat, Antony Thomas Athippozhy

University of Kentucky Doctoral Dissertations

Rat exon microarrays were utilized to detect changes in mRNA expression and alternative splicing in the liver, duodenum, jejunum, and ileum of the lactating rat when compared to age-matched virgin controls. Analysis of data at the level of gene expression revealed differential expression of genes involved in cholesterol biosynthesis in each tissue examined, suggesting increased Sterol Response Element Binding Protein activity. We also detected decreased mRNA from components of the T-cell signaling pathway in the jejunum and ileum. We characterized expression of solute carrier and adenosine triphosphate binding cassette proteins. In addition to characterizing genes by pathway, we have also …

A Novel Device For Cell-Cell Electrofusion, Justin T. Stewart

USF Tampa Graduate Theses and Dissertations

Cell transplantation therapy is a potentially powerful tool and can be used to replace defective cells with healthy cells. This offers the possibility of alleviating the destructive symptoms for many diseases such as Parkinson's disease, Alzheimer's disease, stroke, spinal cord trauma, Type I diabetes and many more. While there are many diseases that could be positively impacted from cell transplantation therapy, the focus of this research is insulin dependent, Type I Diabetes.

The Islets of Langerhans are composed of various types of cells located in the pancreas and are responsible for a variety of biochemical functions. Specifically, the beta Islet …

Statistical Models For Environmental And Health Sciences, Yong Xu

USF Tampa Graduate Theses and Dissertations

Statistical analysis and modeling are useful for understanding the behavior of different phenomena. In this study we will focus on two areas of applications: Global warming and cancer research. Global Warming is one of the major environmental challenge people face nowadays and cancer is one of the major health problem that people need to solve.

For Global Warming, we are interest to do research on two major contributable variables: Carbon dioxide (CO2) and atmosphere temperature. We will model carbon dioxide in the atmosphere data with a system of differential equations. We will develop a differential equation for each of six …

Gender Differences In Lung Cancer Treatment And Survival, Margaret Anne Kowski

USF Tampa Graduate Theses and Dissertations

The objectives of this research were to test treatment and survival differences between women and men with lung cancer as there is minimal investigation in the literature. Three research questions were developed with statistical testing for gender differences based on similar cancer type, stage, treatment assignment and survival. Data for 44,863 primary lung cancer cases were collected from eight U.S. state-based cancer registries to investigate the research questions. The lung cancer incidence data included the morphological cell-types of adenocarcinoma (AC); squamous cell carcinoma (SCC); large cell carcinoma (LCC) and small cell carcinoma (SCC). Stage, grade, treatment type, as well as, …

Minimum Description Length Measures Of Evidence For Enrichment, Zhenyu Yang, David R. Bickel

COBRA Preprint Series

In order to functionally interpret differentially expressed genes or other discovered features, researchers seek to detect enrichment in the form of overrepresentation of discovered features associated with a biological process. Most enrichment methods treat the p-value as the measure of evidence using a statistical test such as the binomial test, Fisher's exact test or the hypergeometric test. However, the p-value is not interpretable as a measure of evidence apart from adjustments in light of the sample size. As a measure of evidence supporting one hypothesis over the other, the Bayes factor (BF) overcomes this drawback of the p-value but lacks …

Predicting Treatment Efficacy Via Quantitative Mri: A Bayesian Joint Model, Jincao Wu, Tim Johnson

The University of Michigan Department of Biostatistics Working Paper Series

The prognosis for patients with high-grade gliomas is poor, with a median survival of one year. Treatment efficacy assessment is typically unavailable until 5{6 months post diagnosis. Investigators hypothesize that quantitative MRI (qMRI) can assess treatment efficacy three weeks after therapy starts, thereby allowing salvage treatments to begin earlier. The purpose of this work is to build a predictive model of treatment efficacy using qMRI data and to assess its performance. The outcome is one-year survival status. We propose a joint, two-stage Bayesian model. In stage I, we smooth the image data with a multivariate spatio-temporal pairwise dierence prior. We …

Coronary Heart Disease Mortality And Long-Term Exposure To Ambient Particulate Air Pollutants In Elderly Nonsmoking California Residents, Lie Hong Chen

Loma Linda University Electronic Theses, Dissertations & Projects

The purpose of this study is to assess the effect of long-term concentrations of ambient PM on risks of all causes, cardiopulmonary, coronary heart disease (CHD), total cancer, and any mention of nonmalignant respiratory disease (NMRD) mortality.

The health effects of long-term ambient air pollution have been studied with up to 30 years of follow-up in the AHSMOG cohort, a cohort of 6,338 nonsmoking white California adults. Monthly concentrations of ambient air pollutants [particulate matter(PMio), Ozone (O3), sulfur dioxide (SO2), nitrogen dioxide (NO2) or particulate matter

In the AHSMOG cohort, each increment of 10 |ig/m3 in PMio in two-pollutant models …

The Determinants Of Colorectal Cancer Survival Disparities In Nevada, Lucas N. Wassira

UNLV Theses, Dissertations, Professional Papers, and Capstones

Different population groups across Nevada and throughout the United States suffer disproportionately from colorectal cancer and its after-effects. Overcoming cancer health disparities is important for lessening the burden of cancer. There has been an overall decline in the incidence of and mortality from colorectal cancer (CRC). This is likely due, in part, to the increasing use of screening procedures such as Fecal Occult Blood Test (FOBT) and/or endoscopy, which can reduce the risk of CRC mortality by fifty percent. Nevertheless, screening procedures are routinely used by only fifty percent of Americans aged fifty years and older. Despite overall mortality decreasing …

Spatial Epidemiology Of Birth Defects In The United States And The State Of Utah Using Geographic Information Systems And Spatial Statistics, Samson Y. Gebreab

All Graduate Theses and Dissertations, Spring 1920 to Summer 2023

Oral clefts are the most common form of birth defects in the United States (US) and the State of Utah has among the highest prevalence of oral clefts in the nation. The overall objective of this dissertation was to examine the spatial distribution of oral clefts and their linkage with a broad range of demographic, behavioral, social, economic, and environmental risk factors through the application of Geographic Information Systems (GIS) and spatial statistics. Using innovative linked micromaps plots, we investigated the geographic patterns of oral clefts occurrence from 1998 to 2002 and their relationships with maternal smoking rates and proportion …

Asymptotic Theory For Cross-Validated Targeted Maximum Likelihood Estimation, Wenjing Zheng, Mark J. Van Der Laan

U.C. Berkeley Division of Biostatistics Working Paper Series

We consider a targeted maximum likelihood estimator of a path-wise differentiable parameter of the data generating distribution in a semi-parametric model based on observing n independent and identically distributed observations. The targeted maximum likelihood estimator (TMLE) uses V-fold sample splitting for the initial estimator in order to make the TMLE maximally robust in its bias reduction step. We prove a general theorem that states asymptotic efficiency (and thereby regularity) of the targeted maximum likelihood estimator when the initial estimator is consistent and a second order term converges to zero in probability at a rate faster than the square root of …

Observational Study And Individualized Antiretroviral Therapy Initiation Rules For Reducing Cancer Incidence In Hiv-Infected Patients, Romain Neugebauer, Michael J. Silverberg, Mark J. Van Der Laan

U.C. Berkeley Division of Biostatistics Working Paper Series

Targeted Maximum Likelihood Learning (TMLL) has been proposed as a general estimation methodology that can, in particular, be applied to draw causal inferences based on marginal structural modeling with observational data using either a point treatment approach (all confounders are assumed not to be affected by the exposure(s) of interest) or a longitudinal data approach (some confounders may be affected by one of the exposures of interest). While formal development of TMLL has included road maps for applications in longitudinal data approaches, real-life implementations have been restricted to studies based on a point treatment approach. In this article, we illustrate …