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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
Identifying an appropriate set of predictors for the outcome of interest is a major challenge in clinical prediction research. The aim of this study is to show the application of some variable selecti...
Despite enormous development on variable selection approaches in recent years, modeling and selection of high dimensional censored regression remains a challenging question. When the number of predict...
The rank product statistic has been widely used to detect differentially expressed genes in replicated microarrays and a one-class setting. The objective of this article is to apply a rank product sta...
Patients who use complementary and integrative health services like chiropractic manipulative treatment (CMT) often have different characteristics than do patients who do not, and these differences ca...
In this work, two new and powerful chemometrics methods are applied for the modeling and prediction of the (19)F chemical shift values of some fluorinated organic compounds. The radial basis function-...
The researching subject is aimed to obtain the clinical evidences (including real benefits， risks ,etc. ) of traditional Chinese medicine in the treatment of advanced gastric cancer by c...
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...
Coordinated multi-center project with several complementary goals in each one of the sub-projects included. Objectives: 1.To determine risk factors of death, or major complications in the ...
This study seeks to investigate the capillary index score (CIS) to further improve patient selection of endovascular treatment (EVT) in acute ischemic stroke (AIS). The hypothesis or idea...
Idiopathic pulmonary fibrosis (IPF) is a progressing scarring disease of the lungs with an average survival of only 30-36 months since the time of diagnosis. The clinical course of IPF is ...
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.
Within medicine, nutrition (the study of food and the effect of its components on the body) has many different roles. Appropriate nutrition can help prevent certain diseases, or treat others. In critically ill patients, artificial feeding by tubes need t...