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Full-Text Articles in Statistics and Probability

The Analysis Of Pixel Intensity (Myocardial Signal Density) Data: The Quantification Of Myocardial Perfusion By Imaging Methods., William F. Mccarthy, Douglas R. Thompson May 2007

The Analysis Of Pixel Intensity (Myocardial Signal Density) Data: The Quantification Of Myocardial Perfusion By Imaging Methods., William F. Mccarthy, Douglas R. Thompson

COBRA Preprint Series

This paper described a number of important issues in the analysis of pixel intensity data, as well as approaches for dealing with these. We particularly emphasized the issue of clustering, which may be ubiquitous in studies of pixel intensity data. Clustering can take many forms, e.g., measurements of different sections of a heart or repeated measurements of the same research participant. Clustering typically has the effect of increasing variance estimates. When one fails to account for clustering, variance estimates may be unrealistically small, resulting in spurious significance. We illustrated several possible approaches to account for clustering, including adjusting standard errors …

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Estimating The Effect Of Vigorous Physical Activity On Mortality In The Elderly Based On Realistic Individualized Treatment And Intention-To-Treat Rules, Oliver Bembom, Mark J. Van Der Laan May 2007

Estimating The Effect Of Vigorous Physical Activity On Mortality In The Elderly Based On Realistic Individualized Treatment And Intention-To-Treat Rules, Oliver Bembom, Mark J. Van Der Laan

U.C. Berkeley Division of Biostatistics Working Paper Series

The effect of vigorous physical activity on mortality in the elderly is difficult to estimate using conventional approaches to causal inference that define this effect by comparing the mortality risks corresponding to hypothetical scenarios in which all subjects in the target population engage in a given level of vigorous physical activity. A causal effect defined on the basis of such a static treatment intervention can only be identified from observed data if all subjects in the target population have a positive probability of selecting each of the candidate treatment options, an assumption that is highly unrealistic in this case since …

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Analyzing Sequentially Randomized Trials Based On Causal Effect Models For Realistic Individualized Treatment Rules, Oliver Bembom, Mark J. Van Der Laan May 2007

Analyzing Sequentially Randomized Trials Based On Causal Effect Models For Realistic Individualized Treatment Rules, Oliver Bembom, Mark J. Van Der Laan

U.C. Berkeley Division of Biostatistics Working Paper Series

In this paper, we argue that causal effect models for realistic individualized treatment rules represent an attractive tool for analyzing sequentially randomized trials. Unlike a number of methods proposed previously, this approach does not rely on the assumption that intermediate outcomes are discrete or that models for the distributions of these intermediate outcomes given the observed past are correctly specified. In addition, it generalizes the methodology for performing pairwise comparisons between individualized treatment rules by allowing the user to posit a marginal structural model for all candidate treatment rules simultaneously. If only a small number of candidate treatment rules are …

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Racial Disparities In Mortality Risks In A Sample Of The U.S. Medicare Population, Yijie Zhou, Francesca Dominici, Thomas A. Louis May 2007

Racial Disparities In Mortality Risks In A Sample Of The U.S. Medicare Population, Yijie Zhou, Francesca Dominici, Thomas A. Louis

Johns Hopkins University, Dept. of Biostatistics Working Papers

Racial disparities in mortality risks adjusted by socioeconomic status (SES) are not well understood. To add to the understanding of racial disparities, we construct and analyze a data set that links, at individual and zip code levels, three government databases: Medicare, Medicare Current Beneficiary Survey and U.S. Census. Our study population includes more than 4 million Medicare enrollees residing in 2095 zip codes in the Northeast region of U.S. We develop hierarchical models to estimate Black-White disparity in risk of death, adjusted by both individual-level and zip codelevel income. We define population-level attributable risk (AR), relative attributable risk (RAR) and …

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Adjusting For Covariates In Studies Of Diagnostic, Screening, Or Prognostic Markers: An Old Concept In A New Setting, Holly Janes, Margaret Pepe May 2007

Adjusting For Covariates In Studies Of Diagnostic, Screening, Or Prognostic Markers: An Old Concept In A New Setting, Holly Janes, Margaret Pepe

UW Biostatistics Working Paper Series

The concept of covariate adjustment is well established in therapeutic and etiologic studies. However, it has received little attention in the growing area of medical research devoted to the development of markers for disease diagnosis, screening, or prognosis, where classification accuracy, rather than association, is of primary interest. In this paper, we demonstrate the need for covariate adjustment in studies of classification accuracy, discuss methods for adjusting for covariates, and distinguish covariate adjustment from several other related but fundamentally different uses for covariates. We draw analogies and contrasts throughout with studies of association.

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A Case Study In Pharmacologic Imaging Using Principal Curves In Single Photon Emission Computed Tomography, Brian S. Caffo, Ciprian M. Crainiceanu, Lijuan Deng, Craig W. Hendrix May 2007

A Case Study In Pharmacologic Imaging Using Principal Curves In Single Photon Emission Computed Tomography, Brian S. Caffo, Ciprian M. Crainiceanu, Lijuan Deng, Craig W. Hendrix

Johns Hopkins University, Dept. of Biostatistics Working Papers

In this manuscript we are concerned with functional imaging of the colon to assess the kinetics of a microbicide lubricant. The overarching goal is to understand the distribution of the lubricant in the colon. Such information is crucial for understanding the potential impact of the microbicide on HIV viral transmission. The experiment was conducted by imaging a radiolabeled lubricant distributed in the subject’s colon. The tracer imaging was conducted via single photon emission computed tomography (SPECT), a non-invasive, in-vivo functional imaging technique. We develop a novel principal curve algorithm to construct a three dimensional curve through the colon images. The …

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Ecologic Studies Revisited, Jon Wakefield May 2007

Ecologic Studies Revisited, Jon Wakefield

UW Biostatistics Working Paper Series

Ecologic studies use data aggregated over groups, rather than data on individuals. Such studies are popular since they may make use of existing data bases, and can offer large exposure variation if based on broad geographical areas. Unfortunately the aggregation of data that defines ecologic studies results in a loss of information that can lead to ecologic bias. Specifically, ecologic bias arises from the inability of ecologic data to characterize within-area variability in exposures and confounders. We describe in detail particular forms of ecologic bias so that their potential impact on any particular study may be assessed. The only way …

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Gamma Generalized Linear Models For Pharmacokinetic Data, Ruth Salway, Jon Wakefield May 2007

Gamma Generalized Linear Models For Pharmacokinetic Data, Ruth Salway, Jon Wakefield

UW Biostatistics Working Paper Series

This paper considers the modeling of single dose pharmacoki- netic data. Traditionally, so-called compartmental models have been used to analyze such data. Unfortunately the mean function of such models are sums of exponentials for which inference and computation may not be straightfor- ward. We present an alternative to these models based on generalized linear models, for which desirable statistical properties exist, with a logarithmic link and gamma distribution. The latter has a constant coefficient of variation which is often appropriate for pharmacokinetic data. Inference is convenient from either a likelihood or a Bayesian perspective. We consider models for both single …

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Biomarker Evaluation Using The Controls As A Reference Population, Ying Huang, Margaret Pepe Apr 2007

Biomarker Evaluation Using The Controls As A Reference Population, Ying Huang, Margaret Pepe

UW Biostatistics Working Paper Series

The classification accuracy of a continuous marker is typically evaluated with the Receiver Operating Characteristic Curve. In this paper, we study an alternative conceptual framework, the "percentile value". In particular the controls only provide a reference distribution to standardize the marker. The analysis proceeds by analyzing the standardized marker only in cases. The approach is shown to be equivalent to ROC analysis. Advantages are that it provides a framework more familiar to biostatisticians and it opens up avenues for new statistical techniques in biomarker evaluation. We develop several new procedures based on this framework for comparing biomarkers and for comparing …

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Potret Buram Pelayanan Kesehatan Lanjut Usia Di Indonesia, Indang Trihandini Apr 2007

Potret Buram Pelayanan Kesehatan Lanjut Usia Di Indonesia, Indang Trihandini

Kesmas

Jumlah dan proporsi kelompok lanjut usia (lansia) di seluruh dunia, terus meningkat, dan cenderung menjadi masalah kesehatan dan sosial sehingga mendapat perhatian dan dukungan yang serius. Resolusi PBB no 46/ 1991, 16 Desember 1991 menghimbau agar seluruh negara di dunia memberikan hak yang layak kepada kelompok lansia. Di Indonesia, populasi lansia pada tahun 2000 (17,2 juta) meningkat 3 kali lebih besar dari pada tahun 1970 (5,3 juta). Pada tahun 2020, jumlah dan proporsi kelompok lansia di Indonesia diprediksi akan mencapai 28 juta jiwa dan 9,5%. Aspek legal telah menempatkan lansia Indonesia pada tempat yang respek dan terhormat, tetapi, kenyataan memperlihatkan …

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Tantangan Pencapaian Millenium Development Goals (Mdgs) Bidang Kesehatan Di Indonesia, Budi Utomo Apr 2007

Tantangan Pencapaian Millenium Development Goals (Mdgs) Bidang Kesehatan Di Indonesia, Budi Utomo

Kesmas

Laporan pemerintah tentang pencapaian MDGs di Indonesia sampai tahun 2002 merefleksikan komitmen dalam mensejahterakan rakyat. Kesehatan yang dijabarkan dalam berbagai indikator tujuan 4, 5, dan 6 dilaporkan membaik. Tulisan ini menelaah status pencapaian, mencari penjelasan latar belakang pencapaian, dan menilai prospek pencapaian MDGs utamanya bidang kesehatan. Hasil telaah menunjukkan sebagian besar indikator kesehatan membaik, tetapi lamban. Walau menurun, angka kematian ibu dan anak masih tinggi. Penyakit infeksi dan masalah gizi masih prevalen. Akses masyarakat terhadap pelayanan kesehatan masih rendah. Biaya masih menjadi penghambat utama pelayanan kesehatan bagi mereka yang membutuhkan. Program pemberantasan penyakit menular, termasuk HIV/AIDS, malaria, dan TB masih …

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A Bayesian Hierarchical Framework For Spatial Modeling Of Fmri Data, F. Dubois Bowman, Brian S. Caffo, Susan Spear Bassett, Clinton Kilts Apr 2007

A Bayesian Hierarchical Framework For Spatial Modeling Of Fmri Data, F. Dubois Bowman, Brian S. Caffo, Susan Spear Bassett, Clinton Kilts

Johns Hopkins University, Dept. of Biostatistics Working Papers

Functional neuroimaging techniques enable investigations into the neural basis of human cognition, emotions, and behaviors. In practice, applications of functional magnetic resonance imaging (fMRI) have provided novel insights into the neuropathophysiology of major psychiatric,neurological, and substance abuse disorders, as well as into the neural responses to their treatments. Modern activation studies often compare localized task-induced changes in brain activity between experimental groups. One may also extend voxel-level analyses by simultaneously considering the ensemble of voxels constituting an anatomically defined region of interest (ROI) or by considering means or quantiles of the ROI. In this work we present a Bayesian extension …

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Fast Adaptive Penalized Splines, Tatyana Krivobokova, Ciprian M. Crainiceanu, Goran Kauermann Mar 2007

Fast Adaptive Penalized Splines, Tatyana Krivobokova, Ciprian M. Crainiceanu, Goran Kauermann

Johns Hopkins University, Dept. of Biostatistics Working Papers

This paper proposes a numerically simple routine for locally adaptive smoothing. The locally heterogeneous regression function is modelled as a penalized spline with a smoothly varying smoothing parameter modelled as another penalized spline. This is being formulated as hierarchical mixed model, with spline coe±cients following a normal distribution, which by itself has a smooth structure over the variances. The modelling exercise is in line with Baladandayuthapani, Mallick & Carroll (2005) or Crainiceanu, Ruppert & Carroll (2006). But in contrast to these papers Laplace's method is used for estimation based on the marginal likelihood. This is numerically simple and fast and …

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A Flexible Semi-Parametric Approach To Estimating A Dose-Response Relationship: The Treatment Of Childhood Amblyopia. , David A. Stephens, Erica E M Moodie Mar 2007

A Flexible Semi-Parametric Approach To Estimating A Dose-Response Relationship: The Treatment Of Childhood Amblyopia. , David A. Stephens, Erica E M Moodie

COBRA Preprint Series

In a study of a dose-response relationship, flexibility in modelling is essential to capturing the treatment effect when the mean effect of other covariates is not fully understood, so that observed treatment effect is not due to the imposition of a rigid model for the relationship between response, treatment, and other variables. A semiparametric additive linear mixed (SPALM) model (Ruppert et al. 2003) provides a tractable and flexible approach to modelling the influence of potentially confounding variables. In this paper, we present pure likelihood and Bayesian versions of the SPALM model. Both methods of inference are readily implementable, but the …

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Modified Test Statistics By Inter-Voxel Variance Shrinkage With An Application To Fmri, Shu-Chih Su, Brian Caffo, Elizabeth Garrett-Mayer, Susan Bassett Mar 2007

Modified Test Statistics By Inter-Voxel Variance Shrinkage With An Application To Fmri, Shu-Chih Su, Brian Caffo, Elizabeth Garrett-Mayer, Susan Bassett

Johns Hopkins University, Dept. of Biostatistics Working Papers

Functional Magnetic Resonance Imaging (fMRI) is a non-invasive technique which is commonly used to quantify changes in blood oxygenation and flow coupled to neuronal activation. One of the primary goals of fMRI studies is to identify localized brain regions where neuronal activation levels vary between groups. Single voxel t-tests have been commonly used to determine whether activation related to the protocol differs across groups. Due to the generally limited number of subjects within each study, accurate estimation of variance at each voxel is difficult. Thus, combining information across voxels in the statistical analysis of fMRI data is desirable in order …

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The Association Between Lifestyle Factors And Inflammatory Markers, Kerry Ann Stonebrook Mar 2007

The Association Between Lifestyle Factors And Inflammatory Markers, Kerry Ann Stonebrook

Loma Linda University Electronic Theses, Dissertations & Projects

Background: Cardiovascular disease (CVD) is the leading cause of death for both men and women in the United States. While smoking, high blood pressure, and elevated cholesterol levels are established risk factors for CVD, inflammation is being evaluated as a potential independent risk factor. A key cytokine regulator of the inflammatory response, interleukin-1 (IL-1), has emerged as playing a particularly important role at the genetic level in determining the degree to which the inflammation pathway is turned on. How an individual’s genetic make-up affects inflammation, CVD risk, and response to lifestyle intervention is an area of research that is in …

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Analysis Of Multi-Level Correlated Data In The Framework Of Generalized Estimating Equations Via Xtmultcorr Procedures In Stata And Qls Functions In Matlab, Justine Shults, Sarah J. Ratcliffe Jan 2007

Analysis Of Multi-Level Correlated Data In The Framework Of Generalized Estimating Equations Via Xtmultcorr Procedures In Stata And Qls Functions In Matlab, Justine Shults, Sarah J. Ratcliffe

UPenn Biostatistics Working Papers

No abstract provided.

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Is A Basketball Free-Throw Sequence Nonrandom? A Group Exercise For Undergraduate Statistics Students, Stephen C. Adolph Jan 2007

Is A Basketball Free-Throw Sequence Nonrandom? A Group Exercise For Undergraduate Statistics Students, Stephen C. Adolph

All HMC Faculty Publications and Research

I describe a group exercise that I give to my undergraduate biostatistics class. The exercise involves analyzing a series of 200 consecutive basketball free-throw attempts to determine whether there is any evidence for sequential dependence in the probability of making a free-throw. The students are given the exercise before they have learned the appropriate statistical tests, so that they can come up with ideas on their own. Students spend a full class period working on the problem, with my guidance and hints. In the next class period, we discuss how each student group approached the problem. I then present several …

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An Adaptive Dose Finding Design (Dosefind) Using A Nonlinear Dose Response Model, James Michael Davenport Jan 2007

An Adaptive Dose Finding Design (Dosefind) Using A Nonlinear Dose Response Model, James Michael Davenport

Theses and Dissertations

First-in-man (FIM) Phase I clinical trials are part of the critical path in the development of a new compound entity (NCE). Since FIM clinical trials are the first time that an NCE is dosed in human subjects, the designs used in these trials are unique and geared toward patient safety. We develop a method for obtaining the desired response using an adaptive non-linear approach. This method is applicable for studies in which MTD, NOEL,NOAEL, PK, PD effects or other such endpoints are evaluated to determine the desired dose. The method has application whenever a measurable PD marker is an indicator …

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Phase Ii Trials Powered To Detect Activity In Tumor Subsets With Retrospective (Or Prospective) Use Of Predictive Markers, Grishma S. Sheth Jan 2007

Phase Ii Trials Powered To Detect Activity In Tumor Subsets With Retrospective (Or Prospective) Use Of Predictive Markers, Grishma S. Sheth

Theses and Dissertations

Classical phase II trial designs assume a patient population with a homogeneous tumor type and yield an estimate of a stochastic probability of tumor response. Clinically, however, oncology is moving towards identifying patients who are likely to respond to therapy using tumor subtyping based upon predictive markers. Such designs are called targeted designs (Simon, 2004). For a given phase I1 trial predictive markers may be defined prospectively (on the basis of previous results) or identified retrospectively on the basis of analysis of responding and non-responding tumors. For the prospective case we propose two Phase I1 targeted designs in which a) …

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Lehmann Family Of Roc Curves, Mithat Gonen, Glenn Heller Dec 2006

Lehmann Family Of Roc Curves, Mithat Gonen, Glenn Heller

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

Receiver operating characteristic (ROC) curves are useful in evaluating the ability of a continuous marker in discriminating between the two states of a binary outcome such as diseased/not diseased. The most popular parametric model for an ROC curve is the binormal model which assumes that the marker is normally distributed conditional on the outcome. Here we present an alternative to the binormal model based on the Lehmann family, also known as the proportional hazards specification. The resulting ROC curve and its functionals (such as the area under the curve) have simple analytic forms. We derive closed-form expressions for the asymptotic …

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A Likelihood Based Method For Real Time Estimation Of The Serial Interval And Reproductive Number Of An Epidemic, Laura Forsberg White, Marcello Pagano Dec 2006

A Likelihood Based Method For Real Time Estimation Of The Serial Interval And Reproductive Number Of An Epidemic, Laura Forsberg White, Marcello Pagano

Harvard University Biostatistics Working Paper Series

No abstract provided.

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A Semiparametric Approach For The Nonparametric Transformation Survival Model With Multiple Covariates, Xiao Song, Shuangge Ma, Jian Huang, Xiao-Hua Zhou Dec 2006

A Semiparametric Approach For The Nonparametric Transformation Survival Model With Multiple Covariates, Xiao Song, Shuangge Ma, Jian Huang, Xiao-Hua Zhou

UW Biostatistics Working Paper Series

The nonparametric transformation model for survival time that makes no parametric assumptions on both the transformation function and the error is appealing in its flexibility. The nonparametric transformation model makes no assumption on the forms of the transformation function and the error distribution. This model is appealing in its flexibility for modeling censored survival data. Current approaches for estimation of the regression parameters involve maximizing discontinuous objective functions, which are numerically infeasible to implement in the case of multiple covariates. Based on the partial rank estimator (Khan & Tamer, 2004), we propose a smoothed partial rank estimator which maximizes a …

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Semiparametric Regression Of Multi-Dimensional Genetic Pathway Data: Least Squares Kernel Machines And Linear Mixed Models, Dawei Liu, Xihong Lin, Debashis Ghosh Nov 2006

Semiparametric Regression Of Multi-Dimensional Genetic Pathway Data: Least Squares Kernel Machines And Linear Mixed Models, Dawei Liu, Xihong Lin, Debashis Ghosh

The University of Michigan Department of Biostatistics Working Paper Series

SUMMARY. We consider a semiparametric regression model that relates a normal outcome to covariates and a genetic pathway, where the covariate effects are modeled parametrically and the pathway effect of multiple gene expressions is modeled parametrically or nonparametrically using least squares kernel machines (LSKMs). This unified framework allows a flexible function for the joint effect of multiple genes within a pathway by specifying a kernel function and allows for the possibility that each gene expression effect might be nonlinear and the genes within the same pathway are likely to interact with each other in a complicated way. This semiparametric model …

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Semiparametric Regression Of Multi-Dimensional Genetic Pathway Data: Least Squares Kernel Machines And Linear Mixed Models, Dawei Liu, Xihong Lin, Debashis Ghosh Nov 2006

Semiparametric Regression Of Multi-Dimensional Genetic Pathway Data: Least Squares Kernel Machines And Linear Mixed Models, Dawei Liu, Xihong Lin, Debashis Ghosh

Harvard University Biostatistics Working Paper Series

No abstract provided.

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Analysis Of Case-Control Age-At-Onset Data Using A Modified Case-Cohort Method, Bin Nan, Xihong Lin Nov 2006

Analysis Of Case-Control Age-At-Onset Data Using A Modified Case-Cohort Method, Bin Nan, Xihong Lin

The University of Michigan Department of Biostatistics Working Paper Series

Case-control designs are widely used in rare disease studies. In a typical case-control study, data are collected from a sample of all available subjects who have experienced a disease (cases) and a sub-sample of subjects who have not experienced the disease (controls) in a study cohort. Cases are often oversampled in case-control studies. Logistic regression is a common tool to estimate the relative risks of the disease and a set of covariates. Very often in such a study, information of ages-at-onset of the disease for all cases and ages at survey of controls are known. Standard logistic regression analysis using …

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Doubly Penalized Buckley-James Method For Survival Data With High-Dimensional Covariates, Sijian Wang, Bin Nan, Ji Zhu, David G. Beer Nov 2006

Doubly Penalized Buckley-James Method For Survival Data With High-Dimensional Covariates, Sijian Wang, Bin Nan, Ji Zhu, David G. Beer

The University of Michigan Department of Biostatistics Working Paper Series

Recent interest in cancer research focuses on predicting patients' survival by investigating gene expression profiles based on microarray analysis. We propose a doubly penalized Buckley-James method for the semiparametric accelerated failure time model to relate high-dimensional genomic data to censored survival outcomes, which uses a mixture of L1-norm and L2-norm penalties. Similar to the elastic-net method for linear regression model with uncensored data, the proposed method performs automatic gene selection and parameter estimation, where highly correlated genes are able to be selected (or removed) together. The two-dimensional tuning parameter is determined by cross-validation and uniform design. …

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Exploiting Gene-Environment Independence For Analysis Of Case-Control Studies: An Empirical Bayes Approach To Trade Off Between Bias And Efficiency, Bhramar Mukherjee, Nilanjan Chatterjee Nov 2006

Exploiting Gene-Environment Independence For Analysis Of Case-Control Studies: An Empirical Bayes Approach To Trade Off Between Bias And Efficiency, Bhramar Mukherjee, Nilanjan Chatterjee

The University of Michigan Department of Biostatistics Working Paper Series

Standard prospective logistic regression analysis of case-control data often leads to very imprecise estimates of gene-environment interactions due to small numbers of cases or controls in cells of crossing genotype and exposure. In contrast, under the assumption of gene-environment independence, modern “retrospective” methods, including the “case-only” approach, can estimate the interaction parameters much more precisely, but they can be seriously biased when the underlying assumption of gene-environment independence is violated. In this article, we propose a novel approach to analyze case-control data that can relax the gene-environment independence assumption using an empirical Bayes framework. In the special case, involving a …

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A Note On Bias Due To Fitting Prospective Multivariate Generalized Linear Models To Categorical Outcomes Ignoring Retrospective Sampling Schemes, Bhramar Mukherjee, Ivy Liu Nov 2006

A Note On Bias Due To Fitting Prospective Multivariate Generalized Linear Models To Categorical Outcomes Ignoring Retrospective Sampling Schemes, Bhramar Mukherjee, Ivy Liu

The University of Michigan Department of Biostatistics Working Paper Series

Outcome dependent sampling designs are commonly used in economics, market research and epidemiological studies. Case-control sampling design is a classic example of outcome dependent sampling, where exposure information is collected on subjects conditional on their disease status. In many situations, the outcome under consideration may have multiple categories instead of a simple dichotomization. For example, in a case-control study, there may be disease sub-classification among the “cases” based on progression of the disease, or in terms of other histological and morphological characteristics of the disease. In this note, we investigate the issue of fitting prospective multivariate generalized linear models to …

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Indeks Sosio-Ekonomi Menggunakan Principal Component Analysis, Iwan Ariawan Oct 2006

Indeks Sosio-Ekonomi Menggunakan Principal Component Analysis, Iwan Ariawan

Kesmas

Pada penelitian survei, kita dapat mengukur tingkat status sosio-ekonomi rumah tangga melalui pemasukan, pengeluaran dan kepemilikan barang-barang berharga. Penggunaan variabel pemasukan dan pengeluaran di negara berkembang memiliki banyak kelemahan, sehingga banyak peneliti lebih suka menggunakan variabel kepemilikan barang berharga untuk mengukur status sosio-ekonomi. Namun, penggunaan variabel kepemilikan barang berharga menimbulkan masalah lain, yaitu banyaknya variabel untuk mengukur status sosio-ekonomi. Tujuan penulisan ini adalah menyederhanakan banyak variabel kepemilikan barang berharga menjadi 1 indeks sosio-ekonomi. Data yang digunakan adalah data Survei Demografi Kesehatan Indonesia 2002-2003 yang memiliki 7 variabel binomial tentang kepemilikan barang berharga dan 3 variabel ordinal tentang keadaan rumah untuk …

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