Propensity score analysis is one statistical technique that can be applied to observational data to mimic randomization and thus can be used to estimate causal effects in studies in which the researchers have not applied randomization. In this article the authors (a) describe propensity score methodology and (b) demonstrate its application using elementary student data from the Early Childhood Longitudinal Study-Kindergarten Class of 1998-99 (ECLS-K). The authors also discuss methodological considerations that need to be addressed when using data from complex samples as in this analysis. Furthermore, the authors provide a tutorial that can be used by researchers to understand the methodology behind and to emulate the steps of conducting pro...
Estimation of the effect of a binary exposure on an outcome in the presence of confounding is often ...
In this article we develop the theoretical properties of the propensity function, which is a general...
The principal aim of analysis of any sample of data is to draw causal inferences about the effects o...
Propensity score analysis is one statistical technique that can be applied to observational data to ...
Propensity score analysis is one statistical technique that can be applied to observational data to ...
Often it is infeasible or unethical to use random assignment in educational settings to study import...
Propensity score methods are popular and effective statistical techniques for reducing selection bia...
Educational researchers frequently study the impact of treatments or interventions on educational ou...
It is common for researchers in the field of education to engage in research that involves two group...
Propensity score analysis seeks to resolve the bias in which the intervention conditions (treatment ...
Propensity score matching is commonly used to estimate causal effects of treatments. However, when u...
In this article, we review four software packages for implementing propensity score analysis in R : ...
Recent calls for accountability have focused on scientifically based research that isolates causal m...
The central role of the propensity score analysis (PSA) in observational studies is for causal infer...
While experimental designs are regarded as the gold standard for establishing causal relationships, ...
Estimation of the effect of a binary exposure on an outcome in the presence of confounding is often ...
In this article we develop the theoretical properties of the propensity function, which is a general...
The principal aim of analysis of any sample of data is to draw causal inferences about the effects o...
Propensity score analysis is one statistical technique that can be applied to observational data to ...
Propensity score analysis is one statistical technique that can be applied to observational data to ...
Often it is infeasible or unethical to use random assignment in educational settings to study import...
Propensity score methods are popular and effective statistical techniques for reducing selection bia...
Educational researchers frequently study the impact of treatments or interventions on educational ou...
It is common for researchers in the field of education to engage in research that involves two group...
Propensity score analysis seeks to resolve the bias in which the intervention conditions (treatment ...
Propensity score matching is commonly used to estimate causal effects of treatments. However, when u...
In this article, we review four software packages for implementing propensity score analysis in R : ...
Recent calls for accountability have focused on scientifically based research that isolates causal m...
The central role of the propensity score analysis (PSA) in observational studies is for causal infer...
While experimental designs are regarded as the gold standard for establishing causal relationships, ...
Estimation of the effect of a binary exposure on an outcome in the presence of confounding is often ...
In this article we develop the theoretical properties of the propensity function, which is a general...
The principal aim of analysis of any sample of data is to draw causal inferences about the effects o...