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Models For Hsv Shedding Must Account For Two Levels Of Overdispersion, Amalia Magaret Jan 2016

Models For Hsv Shedding Must Account For Two Levels Of Overdispersion, Amalia Magaret

UW Biostatistics Working Paper Series

We have frequently implemented crossover studies to evaluate new therapeutic interventions for genital herpes simplex virus infection. The outcome measured to assess the efficacy of interventions on herpes disease severity is the viral shedding rate, defined as the frequency of detection of HSV on the genital skin and mucosa. We performed a simulation study to ascertain whether our standard model, which we have used previously, was appropriately considering all the necessary features of the shedding data to provide correct inference. We simulated shedding data under our standard, validated assumptions and assessed the ability of 5 different models to reproduce the …


Net Reclassification Index: A Misleading Measure Of Prediction Improvement, Margaret Sullivan Pepe, Holly Janes, Kathleen F. Kerr, Bruce M. Psaty Sep 2013

Net Reclassification Index: A Misleading Measure Of Prediction Improvement, Margaret Sullivan Pepe, Holly Janes, Kathleen F. Kerr, Bruce M. Psaty

UW Biostatistics Working Paper Series

The evaluation of biomarkers to improve risk prediction is a common theme in modern research. Since its introduction in 2008, the net reclassification index (NRI) (Pencina et al. 2008, Pencina et al. 2011) has gained widespread use as a measure of prediction performance with over 1,200 citations as of June 30, 2013. The NRI is considered by some to be more sensitive to clinically important changes in risk than the traditional change in the AUC (Delta AUC) statistic (Hlatky et al. 2009). Recent statistical research has raised questions, however, about the validity of conclusions based on the NRI. (Hilden and …


Using The Stages Of Change Model To Choose An Optimal Health Marketing Target, Paula Diehr, Peggy A. Hannon, Barbara Pizacani, Mark Forehand, Jeffrey Harris, Hendrika Meischke, Susan J. Curry, Diane P. Martin, Marcia R. Weaver Mar 2010

Using The Stages Of Change Model To Choose An Optimal Health Marketing Target, Paula Diehr, Peggy A. Hannon, Barbara Pizacani, Mark Forehand, Jeffrey Harris, Hendrika Meischke, Susan J. Curry, Diane P. Martin, Marcia R. Weaver

UW Biostatistics Working Paper Series

Background: In the transtheoretical model of behavior change, “stages of change” are defined as Precontemplation (not even thinking about changing), Contemplation, Preparation, Action, and Maintenance (maintaining the behavior change). Marketing principles suggest that efforts should be targeted at persons most likely to “buy the product.”

Objectives: To examine the effect of intervening at different stages in populations of smokers, with various numbers of people in each “stage of change.” One type of intervention would increase by 10% the probability of a person moving to the next higher stage of change, such as from Precontemplation to Contemplation. The second type would …


Lot Quality Assurance Sampling (Lqas) And The Mozambique Malaria Indicator Surveys, Caitlin Biedron, Marcello Pagano, Bethany L. Hedt, Albert Kilian, Amy Ratcliffe, Samuel Mabunda, Joseph J. Valadez Nov 2009

Lot Quality Assurance Sampling (Lqas) And The Mozambique Malaria Indicator Surveys, Caitlin Biedron, Marcello Pagano, Bethany L. Hedt, Albert Kilian, Amy Ratcliffe, Samuel Mabunda, Joseph J. Valadez

Harvard University Biostatistics Working Paper Series

No abstract provided.


Learning From Near Misses In Medication Errors: A Bayesian Approach, Jessica A. Myers, Francesca Dominici, Laura Morlock Dec 2008

Learning From Near Misses In Medication Errors: A Bayesian Approach, Jessica A. Myers, Francesca Dominici, Laura Morlock

Johns Hopkins University, Dept. of Biostatistics Working Papers

Medical errors originating in health care facilities are a significant source of preventable morbidity, mortality, and healthcare costs. Voluntary error report systems that collect information on the causes and contributing factors of medi- cal errors regardless of the resulting harm may be useful for developing effective harm prevention strategies. Some patient safety experts question the utility of data from errors that did not lead to harm to the patient, also called near misses. A near miss (a.k.a. close call) is an unplanned event that did not result in injury to the patient. Only a fortunate break in the chain of …


Weighted Likelihood Method For Grouped Survival Data In Case-Cohort Studies With Application To Hiv Vaccine Trials, Zhiguo Li, Peter B. Gilbert, Bin Nan Apr 2007

Weighted Likelihood Method For Grouped Survival Data In Case-Cohort Studies With Application To Hiv Vaccine Trials, Zhiguo Li, Peter B. Gilbert, Bin Nan

The University of Michigan Department of Biostatistics Working Paper Series

Grouped failure time data arise often in HIV studies. In a recent preventive HIV vaccine efficacy trial, immune responses generated by the vaccine were measured from a case-cohort sample of vaccine recipients, who were subsequently evaluated for the study endpoint of HIV infection at pre-specified follow-up visits. Gilbert et al. (2005) and Forthal et al. (2007) analyzed the association between the immune responses and HIV incidence with a Cox proportional hazards model, treating the HIV infection diagnosis time as a right censored random variable. The data, however, are of the form of grouped failure time data with case-cohort covariate sampling, …


Estimating The Empirical Lorenz Curve And Gini Coefficient In The Presence Of Error, Chaya S. Moskowitz, E. S. Venkatraman, Elyn Riedel, Colin B. Begg Jan 2007

Estimating The Empirical Lorenz Curve And Gini Coefficient In The Presence Of Error, Chaya S. Moskowitz, E. S. Venkatraman, Elyn Riedel, Colin B. Begg

Memorial Sloan-Kettering Cancer Center, Dept. of Epidemiology & Biostatistics Working Paper Series

The Lorenz curve is a graphical tool that is widely used to characterize the concentration of a measure in a population, such as wealth. It is frequently the case that the measure of interest used to rank experimental units when estimating the empirical Lorenz curve, and the corresponding Gini coefficient, is subject to random error. This error can result in an incorrect ranking of experimental units which inevitably leads to a curve that exaggerates the degree of concentration (variation) in the population. We explore this bias and discuss several widely available statistical methods that have the potential to reduce or …


Assessing The Adequacy Of Variance Function In Heteroscedastic Regression Models, Lan Wang, Xiao-Hua Andrew Zhou Sep 2006

Assessing The Adequacy Of Variance Function In Heteroscedastic Regression Models, Lan Wang, Xiao-Hua Andrew Zhou

UW Biostatistics Working Paper Series

Heteroscedastic data arise in many applications. In a heteroscedastic regression model, the variance is often taken as a parametric function of the covariate or the regression mean. This paper presents a kernel-smoothing based nonparametric test for checking the adequacy of such a postulated variance structure. The test does not need to specify a parametric distribution for the random errors. It has an asymptotical normal distribution under the null hypothesis and is powerful against a large class of alternatives. Numerical simulations and an illustrative example are provided.


Reliability, Effect Size, And Responsiveness And Intraclass Correlation Of Health Status Measures Used In Randomized And Cluster-Randomized Trials, Paula Diehr, Lu Chen, Donald L. Patrick, Ziding Feng, Yutaka Yasui Mar 2006

Reliability, Effect Size, And Responsiveness And Intraclass Correlation Of Health Status Measures Used In Randomized And Cluster-Randomized Trials, Paula Diehr, Lu Chen, Donald L. Patrick, Ziding Feng, Yutaka Yasui

UW Biostatistics Working Paper Series

Background: New health status instruments are described by psychometric properties, such as Reliability, Effect Size, and Responsiveness. For cluster-randomized trials, another important statistic is the Intraclass Correlation for the instrument within clusters. Studies using better instruments can be performed with smaller sample sizes, but better instruments may be more expensive in terms of dollars, lost opportunities, or poorer data quality due to the response burden of longer instruments. Investigators often need to estimate the psychometric properties of a new instrument, or of an established instrument in a new setting. Optimal sample sizes for estimating these properties have not been studied …


Sensitivity Of The Hazard Ratio To Non-Ignorable Treatment Assignment In An Observational Study, Nandita Mitra, Daniel F. Heitjan Mar 2006

Sensitivity Of The Hazard Ratio To Non-Ignorable Treatment Assignment In An Observational Study, Nandita Mitra, Daniel F. Heitjan

UPenn Biostatistics Working Papers

In non-randomized studies, estimation of treatment effects generally requires adjustment for imbalances in observed covariates. One such method, based on the propensity score, is useful in many applications but may be biased when the assumption of strongly ignorable treatment assignment is violated. Because it is not possible to evaluate this assumption from the data, it is advisable to assess the sensitivity of conclusions to violations of strong ignorability. Lin et al [1] have implemented this idea by investigating how an unmeasured covariate may affect the conclusions of an observational study. We extend their method to assess sensitivity of the treatment …


Different Public Health Interventions Have Varying Effects, Paula Diehr, Anne B. Newman, Liming Cai, Ann Derleth Feb 2006

Different Public Health Interventions Have Varying Effects, Paula Diehr, Anne B. Newman, Liming Cai, Ann Derleth

UW Biostatistics Working Paper Series

Objective: To compare performance of one-time health interventions to those that change the probability of transitioning from one health state to another. Study Design and Setting: We used multi-state life table methods to estimate the impact of eight types of interventions on several outcomes. Results: In a cohort beginning at age 65, curing all the sick persons at baseline would increase life expectancy by 0.23 years and increase years of healthy life by .54 years. An equal amount of improvement could be obtained with a 12% decrease in the probability of getting sick, a 16% increase in the probability of …


Ranking Usrds Provider-Specific Smrs From 1998-2001, Rongheng Lin, Thomas A. Louis, Susan M. Paddock, Greg Ridgeway Dec 2004

Ranking Usrds Provider-Specific Smrs From 1998-2001, Rongheng Lin, Thomas A. Louis, Susan M. Paddock, Greg Ridgeway

Johns Hopkins University, Dept. of Biostatistics Working Papers

Provider profiling (ranking, "league tables") is prevalent in health services research. Similarly, comparing educational institutions and identifying differentially expressed genes depend on ranking. Effective ranking procedures must be structured by a hierarchical (Bayesian) model and guided by a ranking-specific loss function, however even optimal methods can perform poorly and estimates must be accompanied by uncertainty assessments. We use the 1998-2001 Standardized Mortality Ratio (SMR) data from United States Renal Data System (USRDS) as a platform to identify issues and approaches. Our analyses extend Liu et al. (2004) by combining evidence over multiple years via an AR(1) model; by considering estimates …


Semi-Parametric Single-Index Two-Part Regression Models, Xiao-Hua Zhou, Hua Liang Dec 2004

Semi-Parametric Single-Index Two-Part Regression Models, Xiao-Hua Zhou, Hua Liang

UW Biostatistics Working Paper Series

In this paper, we proposed a semi-parametric single-index two-part regression model to weaken assumptions in parametric regression methods that were frequently used in the analysis of skewed data with additional zero values. The estimation procedure for the parameters of interest in the model was easily implemented. The proposed estimators were shown to be consistent and asymptotically normal. Through a simulation study, we showed that the proposed estimators have reasonable finite-sample performance. We illustrated the application of the proposed method in one real study on the analysis of health care costs.


Estimating The Retransformed Mean In A Heteroscedastic Two-Part Model, Alan H. Welsh, Xiao-Hua Zhou Sep 2004

Estimating The Retransformed Mean In A Heteroscedastic Two-Part Model, Alan H. Welsh, Xiao-Hua Zhou

UW Biostatistics Working Paper Series

Two distribution free estimators are proposed to estimate the mean of a dependent variable after fitting a semiparametric two-part heteroscedastic regression model to a transformation of the dependent variable. We show that the proposed estimators are consistent and have asymptotic normal distributions. We also compare their finite-sample performance in a simulation study. Finally, we illustrate the proposed methods in a real-world example of predicting in-patient health care costs.


Nonparametric Confidence Intervals For The One- And Two-Sample Problems, Xiao-Hua Zhou, Phillip Dinh Sep 2004

Nonparametric Confidence Intervals For The One- And Two-Sample Problems, Xiao-Hua Zhou, Phillip Dinh

UW Biostatistics Working Paper Series

Confidence intervals for the mean of one sample and the difference in means of two independent samples based on the ordinary-t statistic suffer deficiencies when samples come from skewed distributions. In this article, we evaluate several existing techniques and propose new methods to improve coverage accuracy. The methods examined include the ordinary-t, the bootstrap-t, the biased-corrected acceleration (BCa) bootstrap, and three new intervals based on transformation of the t-statistic. Our study shows that our new transformation intervals and the bootstrap-t intervals give best coverage accuracy for a variety of skewed distributions; and that our new transformation intervals have shorter interval …


Studying Effects Of Primary Care Physicians And Patients On The Trade-Off Between Charges For Primary Care And Specialty Care Using A Hierarchical Multivariate Two-Part Model, John W. Robinson, Scott L. Zeger, Christopher B. Forrest Aug 2004

Studying Effects Of Primary Care Physicians And Patients On The Trade-Off Between Charges For Primary Care And Specialty Care Using A Hierarchical Multivariate Two-Part Model, John W. Robinson, Scott L. Zeger, Christopher B. Forrest

Johns Hopkins University, Dept. of Biostatistics Working Papers

Objective. To examine effects of primary care physicians (PCPs) and patients on the association between charges for primary care and specialty care in a point-of-service (POS) health plan.

Data Source. Claims from 1996 for 3,308 adult male POS plan members, each of whom was assigned to one of the 50 family practitioner-PCPs with the largest POS plan member-loads.

Study Design. A hierarchical multivariate two-part model was fitted using a Gibbs sampler to estimate PCPs' effects on patients' annual charges for two types of services, primary care and specialty care, the associations among PCPs' effects, and within-patient associations between charges for …


A Hierarchical Multivariate Two-Part Model For Profiling Providers' Effects On Healthcare Charges, John W. Robinson, Scott L. Zeger, Christopher B. Forrest Aug 2004

A Hierarchical Multivariate Two-Part Model For Profiling Providers' Effects On Healthcare Charges, John W. Robinson, Scott L. Zeger, Christopher B. Forrest

Johns Hopkins University, Dept. of Biostatistics Working Papers

Procedures for analyzing and comparing healthcare providers' effects on health services delivery and outcomes have been referred to as provider profiling. In a typical profiling procedure, patient-level responses are measured for clusters of patients treated by providers that in turn, can be regarded as statistically exchangeable. Thus, a hierarchical model naturally represents the structure of the data. When provider effects on multiple responses are profiled, a multivariate model rather than a series of univariate models, can capture associations among responses at both the provider and patient levels. When responses are in the form of charges for healthcare services and sampled …


Ozone And Mortality: A Meta-Analysis Of Time-Series Studies And Comparison To A Multi-City Study (The National Morbidity, Mortality, And Air Pollution Study), Michelle L. Bell, Jonathan M. Samet, Francesca Dominici Jul 2004

Ozone And Mortality: A Meta-Analysis Of Time-Series Studies And Comparison To A Multi-City Study (The National Morbidity, Mortality, And Air Pollution Study), Michelle L. Bell, Jonathan M. Samet, Francesca Dominici

Johns Hopkins University, Dept. of Biostatistics Working Papers

While many time-series studies of ozone and daily mortality identified positive associations,others yielded null or inconclusive results. We performed a meta-analysis of 144 effect estimates from 39 time-series studies, and estimated pooled effects by lags, age groups,cause-specific mortality, and concentration metrics. We compared results to estimates from the National Morbidity, Mortality, and Air Pollution Study (NMMAPS), a time-series study of 95 large U.S. cities from 1987 to 2000. Both meta-analysis and NMMAPS results provided strong evidence of a short-term association between ozone and mortality, with larger effects for cardiovascular and respiratory mortality, the elderly, and current day ozone exposure as …


Self-Reported Memory Symptoms With Coronary Artery Disease: A Prospective Of Cabg Patients And Nonsurgical Controls, Ola A. Selnes, Maura A. Grega, Louis M. Borowicz, Jr., Sarah Barry, Scott L. Zeger, Guy M. Mckhann Mar 2004

Self-Reported Memory Symptoms With Coronary Artery Disease: A Prospective Of Cabg Patients And Nonsurgical Controls, Ola A. Selnes, Maura A. Grega, Louis M. Borowicz, Jr., Sarah Barry, Scott L. Zeger, Guy M. Mckhann

Johns Hopkins University, Dept. of Biostatistics Working Papers

Background. Subjective memory complaints are common after coronary artery bypass grafting (CABG), but previous studies have concluded that such symptoms are more closely associated with depressed mood than objective cognitive dysfunction. We compared the incidence of self-reported memory symptoms at 3 and 12 months after CABG with that of a control group of patients with comparable risk factors for coronary artery disease but without surgery.

Methods. Patients undergoing CABG (n = 140) and a demographically similar nonsurgical control group with coronary artery disease (n = 92) were followed prospectively at 3 and 12 months. At each follow-up time, participants were …


Incorporating Death Into Health-Related Variables In Longitudinal Studies, Paula Diehr, Laura Lee Johnson, Donald L. Patrick, Bruce Psaty Jan 2004

Incorporating Death Into Health-Related Variables In Longitudinal Studies, Paula Diehr, Laura Lee Johnson, Donald L. Patrick, Bruce Psaty

UW Biostatistics Working Paper Series

Background: The aging process can be described as the change in health-related variables over time. Unfortunately, simple graphs of available data may be misleading if some people die, since they may confuse patterns of mortality with patterns of change in health. Methods have been proposed to incorporate death into self-rated health (excellent to poor) and the SF-36 profile scores, but not for other variables.

Objectives: (1) To incorporate death into the following variables: ADLs, IADLs, mini-mental state examination, depressive symptoms, body mass index (BMI), blocks walked per week, bed days, hospitalization, systolic blood pressure, and the timed walk. (2) To …


Optimization Of Breast Cancer Screening Modalities, Yu Shen, Giovanni Parmigiani Dec 2003

Optimization Of Breast Cancer Screening Modalities, Yu Shen, Giovanni Parmigiani

Johns Hopkins University, Dept. of Biostatistics Working Papers

Mathematical models and decision analyses based on microsimulations have been shown to be useful in evaluating relative merits of various screening strategies in terms of cost and mortality reduction. Most investigations regarding the balance between mortality reduction and costs have focused on a single modality, mammography. A systematic evaluation of the relative expenses and projected benefit of combining clinical breast examination and mammography is not at present available. The purpose of this report is to provide methodologic details including assumptions and data used in the process of modeling for complex decision analyses, when searching for optimal breast cancer screening strategies …


Smooth Quantile Ratio Estimation With Regression: Estimating Medical Expenditures For Smoking Attributable Diseases, Francesca Dominici, Scott L. Zeger Nov 2003

Smooth Quantile Ratio Estimation With Regression: Estimating Medical Expenditures For Smoking Attributable Diseases, Francesca Dominici, Scott L. Zeger

Johns Hopkins University, Dept. of Biostatistics Working Papers

In this paper we introduce a semi-parametric regression model for estimating the difference in the expected value of two positive and highly skewed random variables as a function of covariates. Our method extends Smooth Quantile Ratio Estimation (SQUARE), a novel estimator of the mean difference of two positive random variables, to a regression model.

The methodological development of this paper is motivated by a common problem in econometrics where we are interested in estimating the difference in the average expenditures between two populations, say with and without a disease, taking covariates into account. Let Y1 and Y2 be two positive …


Smooth Quantile Ratio Estimation, Francesca Dominici, Leslie Cope, Daniel Q. Naiman, Scott L. Zeger Oct 2003

Smooth Quantile Ratio Estimation, Francesca Dominici, Leslie Cope, Daniel Q. Naiman, Scott L. Zeger

Johns Hopkins University, Dept. of Biostatistics Working Papers

In a study of health care expenditures attributable to smoking, we seek to compare the distribution of medical costs for persons with lung cancer or chronic obstructive pulmonary disease (cases) to those without (controls) using a national survey which includes hundreds of cases and thousands of controls. The distribution of costs is highly skewed toward larger values, making estimates of the mean from the smaller sample dependent on a small fraction of the biggest values. One approach to deal with the smaller sample is to rely on a simple parametric model such as the log-normal, but this makes the undesirable …


Bootstrap Confidence Intervals For Medical Costs With Censored Observations, Hongyu Jiang, Xiao-Hua Zhou May 2003

Bootstrap Confidence Intervals For Medical Costs With Censored Observations, Hongyu Jiang, Xiao-Hua Zhou

UW Biostatistics Working Paper Series

Medical costs data with administratively censored observations often arise in cost-effectiveness studies of treatments for life threatening diseases. Mean of medical costs incurred from the start of a treatment till death or certain timepoint after the implementation of treatment is frequently of interest. In many situations, due to the skewed nature of the cost distribution and non-uniform rate of cost accumulation over time, the currently available normal approximation confidence interval has poor coverage accuracy. In this paper, we proposed a bootstrap confidence interval for the mean of medical costs with censored observations. In simulation studies, we showed that the proposed …


Probabilities Of Transition Among Health States For Older Adults, Paula Diehr, Donald L. Patrick Jan 2001

Probabilities Of Transition Among Health States For Older Adults, Paula Diehr, Donald L. Patrick

UW Biostatistics Working Paper Series

Goal: To estimate the probabilities of transition among self-rated health states for older adults, and examine how they vary by age and sex. Methods: We used self-rated health (Excellent, Very Good, Good, Fair, Poor, Dead) collected in two longitudinal studies of older adults (Mean age 75) to estimate the probability of transition in two years. We used the estimates to project future health for selected cohorts.

Findings: These older adults were most likely to be in the same health state 2 years later, but a substantial proportion changed in both directions. Transition probabilities varied by initial health state, age and …