The role of the c-statistic in variable selection for propensity score models.
Summary of "The role of the c-statistic in variable selection for propensity score models."
The applied literature on propensity scores has often cited the c-statistic as a measure of the ability of the propensity score to control confounding. However, a high c-statistic in the propensity model is neither necessary nor sufficient for control of confounding. Moreover, use of the c-statistic as a guide in constructing propensity scores may result in less overlap in propensity scores between treated and untreated subjects; this may require the analyst to restrict populations for inference. Such restrictions may reduce precision of estimates and change the population to which the estimate applies. Variable selection based on prior subject matter knowledge, empirical observation, and sensitivity analysis is preferable and avoids many of these problems. Copyright © 2010 John Wiley & Sons, Ltd.
This article was published in the following journal.
Name: Pharmacoepidemiology and drug safety
Little is known about influences of sample selection on estimation in propensity score matching. The purpose of the study was to assess potential selection bias using one-to-one greedy matching versus...
Variable (wavelength or feature) selection techniques have become a critical step for the analysis of datasets with high number of variables and relatively few samples. In this study, a novel variable...
Although intracranial pressure (ICP) monitoring in severe traumatic brain injury (TBI) is recommended by the Brain Trauma Foundation, the benefits remain controversial. We sought to determine the impa...
When conducting research on pain and symptom management interventions for seriously ill individuals, randomized controlled trials are not always feasible or ethical to conduct. Secondary analyses of o...
The aim of this study is to identify biomarkers of disease recurrence and prognosis to optimize patient selection for treatment with cytoreductive surgery (CRS) with hyperthermic intraperi...
BBR 2778 is a novel aza-anthracenedione that has activity in experimental tumors and shows reduced potential for cardiotoxicity in animal models. This cytotoxic agent has structural simila...
Patients with acute abdominal pain and suspicion of appendicitis are common. The management of these patients is controversial with large variations between hospitals. The clinical diagnos...
The study aims at providing information on how the Short Message Service (SMS) tool influences self-management in asthma patients and to assess the resulting health related effect. A wide ...
Objective: To compare pregnancy rates and implantation rates when embryos are selected based on a single Day 3 (D.3) score vs. a GES score plus sHLA-G expression.
Medical and Biotech [MESH] Definitions
Conditional probability of exposure to a treatment given observed covariates.
Procedures for finding the mathematical function which best describes the relationship between a dependent variable and one or more independent variables. In linear regression (see LINEAR MODELS) the relationship is constrained to be a straight line and LEAST-SQUARES ANALYSIS is used to determine the best fit. In logistic regression (see LOGISTIC MODELS) the dependent variable is qualitative rather than continuously variable and LIKELIHOOD FUNCTIONS are used to find the best relationship. In multiple regression, the dependent variable is considered to depend on more than a single independent variable.
Statistical models which describe the relationship between a qualitative dependent variable (that is, one which can take only certain discrete values, such as the presence or absence of a disease) and an independent variable. A common application is in epidemiology for estimating an individual's risk (probability of a disease) as a function of a given risk factor.
A distribution in which a variable is distributed like the sum of the squares of any given independent random variable, each of which has a normal distribution with mean of zero and variance of one. The chi-square test is a statistical test based on comparison of a test statistic to a chi-square distribution. The oldest of these tests are used to detect whether two or more population distributions differ from one another.
A method, developed by Dr. Virginia Apgar, to evaluate a newborn's adjustment to extrauterine life. Five items - heart rate, respiratory effort, muscle tone, reflex irritability, and color - are evaluated 60 seconds after birth and again five minutes later on a scale from 0-2, 0 being the lowest, 2 being normal. The five numbers are added for the Apgar score. A score of 0-3 represents severe distress, 4-7 indicates moderate distress, and a score of 7-10 predicts an absence of difficulty in adjusting to extrauterine life.