The matching of experimental and control subjects on critical variables, particularly when used in conjunction with random assignment, is widely recognized as a valuable element in research design. Both in discussions of its usefulness and in applications, matching tends to be treated as an attribute. In fact, however, it is a variable, with a range determined by the number and precision of measurement of the items taken into account in the matching process, and by the size and homogeneity of the pool from which subjects are drawn. Failure to distinguish between well-matched and poorly-matched pairs can lead to significant errors of interpretation. But treating the quality of the match itself as a variable, and introducing it into the inter...
Matching is a technique used to avoid confounding in a study design. In a cohort study this is done ...
Matching is a technique used to avoid confounding in a study design. In a cohort study this is done ...
Matching is a common approach to reduce bias in observed covariates to draw reliable causal inferenc...
In the social sciences, randomized experimentation is the optimal research design for establishing c...
In the social sciences, randomized experimentation is the optimal research design for establishing c...
Experimental designs provide an excellent foundation for analyzing the effects of causes. Not all qu...
In observational studies, matching can be used to remove bias between treated and control subjects. ...
In observational studies, matching can be used to remove bias between treated and control subjects. ...
A quantitative study of treatment effects may form many matched pairs of a treated subject and an un...
In observational studies, treated subjects and controls are often matched to remove bias in pre-trea...
The matching of groups is a traditional way to control for confounding variables in developmental di...
In observational studies, treated subjects and controls are often matched to remove bias in pre-trea...
A simulation study is conducted to compare and evaluate recent developments for multivariate matchin...
A simulation study is conducted to compare and evaluate recent developments for multivariate matchin...
The characterization of matching factors in a case-control study in epidemiology is given in the pre...
Matching is a technique used to avoid confounding in a study design. In a cohort study this is done ...
Matching is a technique used to avoid confounding in a study design. In a cohort study this is done ...
Matching is a common approach to reduce bias in observed covariates to draw reliable causal inferenc...
In the social sciences, randomized experimentation is the optimal research design for establishing c...
In the social sciences, randomized experimentation is the optimal research design for establishing c...
Experimental designs provide an excellent foundation for analyzing the effects of causes. Not all qu...
In observational studies, matching can be used to remove bias between treated and control subjects. ...
In observational studies, matching can be used to remove bias between treated and control subjects. ...
A quantitative study of treatment effects may form many matched pairs of a treated subject and an un...
In observational studies, treated subjects and controls are often matched to remove bias in pre-trea...
The matching of groups is a traditional way to control for confounding variables in developmental di...
In observational studies, treated subjects and controls are often matched to remove bias in pre-trea...
A simulation study is conducted to compare and evaluate recent developments for multivariate matchin...
A simulation study is conducted to compare and evaluate recent developments for multivariate matchin...
The characterization of matching factors in a case-control study in epidemiology is given in the pre...
Matching is a technique used to avoid confounding in a study design. In a cohort study this is done ...
Matching is a technique used to avoid confounding in a study design. In a cohort study this is done ...
Matching is a common approach to reduce bias in observed covariates to draw reliable causal inferenc...