Biostatistics Commons^™

Finding Recurrent Regions Of Copy Number Variation: A Review, Oscar M. Rueda, Ramon Diaz-Uriarte

Ramon Diaz-Uriarte

Copy number alterations (CNA) in genomic DNA are linked to a variety of human diseases. Although many methods have been developed to analyze data from a single subject, disease-critical genes are more likely to be found in regions that are common or recurrent among diseased subjects. Unfortunately, finding recurrent CNA regions remains a challenge. We review existing methods for the identification of recurrent CNA regions. Methods differ in their working definition of ``recurrent region'', the type of input data, the statistical and computational methods used to identify recurrence, and the biological considerations they incorporate (which play a role in the …

Survival Unchanged Five Months After Implementing The 2005 Aha Cpr And Ecc Guidelines For Out-Of-Hospital Cardiac Arrest., Blair L. Bigham, Kent M. Koprowicz, John Stouffer, Tom P. Aufderheide, Stuart Donn, Judy Powell, Dan Davis, Sarah Nafziger, Brian Suffoletto, Ahamed Idris, Mike Helbock, Laurie J. Morrison

Kent M Koprowicz

Introduction: To improve survival from out of hospital cardiac arrest (OHCA), the American Heart Association released guidelines in 2005. We examined the effect of these guidelines on survival in the Resuscitation Outcomes Consortium (ROC) Epistry – Cardiac Arrest. We hypothesized that survival would increase after guideline implementation. Methods: 174 EMS agencies from 8 of the 10 ROC sites were surveyed to determine 2005 AHA guideline implementation, or crossover, date. Two sites with 2005 compatible treatment algorithms prior to guideline release were not included. Patients with OHCA secondary to a non cardiac cause, EMS witnessed events, patients <18 years>old, and patients with …

Composite Endpoint Analysis For Assessing Surrogacy With Censored Data, Debashis Ghosh

Debashis Ghosh

Background: There is great interest in the development of surrogate endpoints using new technologies in medical research. The promise of such endpoints is that they would allow for faster completion of clinical trials and would be potentially cost-effective.

Purpose: In determining surrogacy, it is important to distinguish the roles of surrogate from the true endpoint. The latter should be thought of as the gold standard. We discuss a framework in which the utility of a surrogate endpoint is based on whether or not as part of a composite endpoint, it yields treatment effects that associate with that on the true …

On Correcting The Overestimation Of The Permutation Based False Discovery Rate Estimator., Shuo Jiao, Shunpu Zhang

Shuo Jiao

Motivation: Recent attempts to account for multiple testing in the analysis of microarray data have focused on controlling the false discovery rate (FDR), which is defined as the expected percentage of the number of false positive genes among the claimed significant genes. As a consequence, the accuracy of the FDR estimators will

be important for correctly controlling FDR. Xie et al. found that the standard permutation method of estimating FDR is biased and proposed to delete the predicted differentially expressed (DE) genes in the estimation of FDR for one-sample comparison. However, we notice that the formula of the FDR used …

Microproteomics: Analysis Of Protein Diversity In Small Samples, Howard B. Gutstein, Jeffrey S. Morris, Suresh P. Annangudi, Jonathan V. Sweedler

Jeffrey S. Morris

Proteomics, the large-scale study of protein expression in organisms, offers the potential to evaluate global changes in protein expression and their post-translational modifications that take place in response to normal or pathological stimuli. One challenge has been the requirement for substantial amounts of tissue in order to perform comprehensive proteomic characterization. In heterogeneous tissues, such as brain, this has limited the application of proteomic methodologies. Efforts to adapt standard methods of tissue sampling, protein extraction, arraying, and identification are reviewed, with an emphasis on those appropriate to smaller samples ranging in size from several microliters down to single cells. The …

Comment On Global Dynamics Of Biological Systems, Radhakrishnan Nagarajan

Radhakrishnan Nagarajan

No abstract provided.

Software For Fitting Hierarchical Spatial Functional Models, Veera Baladandayuthapani

Veera Baladandayuthapani

No abstract provided.

Generalized Mcnemar's Test For Homogeneity Of The Marginal Distributions, Zhao Yang

Zhao (Tony) Yang, Ph.D.

In the matched-pairs data, McNemar's test (McNemar, 1947) can be applied only to the case in which there are two possible categories for the outcome. In practice, however, it is possible that the outcomes are classified into multiple categories. Under this situation, the test statistic proposed by Stuart (1955) and Maxwell (1970) is useful; it is actually the generalization of the McNemar's test, commonly referred to as generalized McNemar's or Stuart-Maxwell test. There is no public available SAS program to calculate this statistic, the author has developed a SAS macro (the code is detailed in appendix) to perform this test …

Direct Effect Models, Mark J. Van Der Laan, Maya L. Petersen

Maya Petersen

The causal effect of a treatment on an outcome is generally mediated by several intermediate variables. Estimation of the component of the causal effect of a treatment that is not mediated by an intermediate variable (the direct effect of the treatment) is often relevant to mechanistic understanding and to the design of clinical and public health interventions. Robins, Greenland and Pearl develop counterfactual definitions for two types of direct effects, natural and controlled, and discuss assumptions, beyond those of sequential randomization, required for the identifiability of natural direct effects. Building on their earlier work and that of others, this article …

Using The Estimated Penetrances To Determine The Range Of The Underlying Genetic Model In Case-Control Design, Mark J. Meyer, Neal Jeffries, Gang Zheng

Mark J Meyer

It is well known that the penetrance cannot be estimated using the retrospective case- control samples without making additional assumptions. In the literature the estimation of the penetrance is based on the assumptions that either the disease is rare or the disease prevalence is known. We propose an alternative approach to estimate the penetrance by assuming an underlying genetic model even though it is unknown. With this assumption, we can obtain the point estimates of the penetrances as functions of the genetic model, from which the range of underlying genetic models can be determined. We examine the performance of our …

Characterizing Pharmacy And Medical Claims For A Private Insurance Polypharmacy Population, Brian W. Bresnahan, Kent M. Koprowicz, Sanchita Roy Choudhury, Louis P. Garrison, Ed Wong

Kent M Koprowicz

Objectives: To describe and characterize a group of private insurance members taking multiple medications over a one-year period. Methods: Persons were selected for this polypharmacy analysis if they had at least five unique maintenance prescriptions in their pharmacy claims records for the period of January-March 2005, based on a customized list of chronic medications. The full set of pharmacy and medical claims for these members were evaluated for a twelve month period, October 2004 to September 2005. Standard descriptive statistics were calculated to characterize the population. Logistic regression models were used to assess the association of pharmacy claims and “safety …

Multiple Testing Procedures Under Confounding, Debashis Ghosh

Debashis Ghosh

While multiple testing procedures have been the focus of much statistical research, an important facet of the problem is how to deal with possible confounding. Procedures have been developed by authors in genetics and statistics. In this chapter, we relate these proposals. We propose two new multiple testing approaches within this framework. The first combines sensitivity analysis methods with false discovery rate estimation procedures. The second involves construction of shrinkage estimators that utilize the mixture model for multiple testing. The procedures are illustrated with applications to a gene expression profiling experiment in prostate cancer.

Joint Variable Selection And Classification With Immunohistochemical Data, Debashis Ghosh, Ratna Chakrabarti

Debashis Ghosh

To determine if candidate cancer biomarkers have utility in a clinical setting, validation using immunohistochemical methods is typically done. Most analyses of such data have not incorporated the multivariate nature of the staining profiles. In this article, we consider modelling such data using recently developed ideas from the machine learning community. In particular, we consider the joint goals of feature selection and classification. We develop esti- mation procedures for the analysis of immunohistochemical profiles using the least absolute selection and shrinkage operator. These lead to novel and flexible models and algorithms for the analysis of compositional data. The techniques are …

An Improved Model Averaging Scheme For Logistic Regression, Debashis Ghosh, Zheng Yuan

Debashis Ghosh

Recently, penalized regression methods have attracted much attention in the statistical literature. In this article, we argue that such methods can be improved for the purposes of prediction by utilizing model averaging ideas. We propose a new algorithm that combines penalized regression with model averaging for improved prediction. We also discuss the issue of model selection versus model averaging and propose a diagnostic based on the notion of generalized degrees of freedom. The proposed methods are studied using both simulated and real data.