Propensity score methodology is being increasingly used to try and make inferences about treatments when randomised trials are either impossible or not conducted and the only data are from observational studies. This paper reviews the basis of propensity scores and the current state of knowledge about them. It uses and critiques a current paper in the Emergency Medicine Journal to illustrate the methodology
Randomized clinical trials (RCT) are accepted as the gold-standard approaches to measure effects of ...
For observational studies, the propensity score is the probability of treatment for a given set of b...
BACKGROUND. Health services researchers are often interested in the effect of a treatment or a servi...
Real-world data are increasingly available to investigate real-world' safety and efficacy. However, ...
Purpose. To document which established criteria for logistic regression modeling researchers conside...
National audienceObservational studies in the absence of selection bias reflect real life practices ...
The principal aim of analysis of any sample of data is to draw causal inferences about the effects o...
A propensity score is the conditional probability that a participant will be assigned to a treatment...
National audienceINTRODUCTION: In observational studies, a significant difference in the outcomes be...
Estimation of the effect of a binary exposure on an outcome in the presence of confounding is often ...
Background/Aims: Treatment effects from observational studies may be biased since the patients were ...
Experimental studies or randomized clinical trail in health care setting are usually the preferred t...
This review considers casual inference in observational studies which can prove medical treatment. T...
Propensity score (PS) techniques are useful if the number of potential confounding pretreatment vari...
Clinicians often face difficult decisions despite the lack of evidence from randomized trials. Thus,...
Randomized clinical trials (RCT) are accepted as the gold-standard approaches to measure effects of ...
For observational studies, the propensity score is the probability of treatment for a given set of b...
BACKGROUND. Health services researchers are often interested in the effect of a treatment or a servi...
Real-world data are increasingly available to investigate real-world' safety and efficacy. However, ...
Purpose. To document which established criteria for logistic regression modeling researchers conside...
National audienceObservational studies in the absence of selection bias reflect real life practices ...
The principal aim of analysis of any sample of data is to draw causal inferences about the effects o...
A propensity score is the conditional probability that a participant will be assigned to a treatment...
National audienceINTRODUCTION: In observational studies, a significant difference in the outcomes be...
Estimation of the effect of a binary exposure on an outcome in the presence of confounding is often ...
Background/Aims: Treatment effects from observational studies may be biased since the patients were ...
Experimental studies or randomized clinical trail in health care setting are usually the preferred t...
This review considers casual inference in observational studies which can prove medical treatment. T...
Propensity score (PS) techniques are useful if the number of potential confounding pretreatment vari...
Clinicians often face difficult decisions despite the lack of evidence from randomized trials. Thus,...
Randomized clinical trials (RCT) are accepted as the gold-standard approaches to measure effects of ...
For observational studies, the propensity score is the probability of treatment for a given set of b...
BACKGROUND. Health services researchers are often interested in the effect of a treatment or a servi...