Journal ArticleDOI
Estimating causal effects of treatments in randomized and nonrandomized studies.
TLDR
A discussion of matching, randomization, random sampling, and other methods of controlling extraneous variation is presented in this paper, where the objective is to specify the benefits of randomization in estimating causal effects of treatments.Abstract:
A discussion of matching, randomization, random sampling, and other methods of controlling extraneous variation is presented. The objective is to specify the benefits of randomization in estimating causal effects of treatments. The basic conclusion is that randomization should be employed whenever possible but that the use of carefully controlled nonrandomized data to estimate causal effects is a reasonable and necessary procedure in many cases. Recent psychological and educational literature has included extensive criticism of the use of nonrandomized studies to estimate causal effects of treatments (e.g., Campbell & Erlebacher, 1970). The implication in much of this literature is that only properly randomized experiments can lead to useful estimates of causal effects. If taken as applying to all fields of study, this position is untenable. Since the extensive use of randomized experiments is limited to the last half century,8 and in fact is not used in much scientific investigation today,4 one is led to the conclusion that most scientific "truths" have been established without using randomized experiments. In addition, most of us successfully determine the causal effects of many of our everyday actions, even interpersonal behaviors, without the benefit of randomization. Even if the position that causal effects of treatments can only be well established from randomized experiments is taken as applying only to the social sciences in whichread more
Citations
More filters
Book
Econometric Analysis of Cross Section and Panel Data
TL;DR: This is the essential companion to Jeffrey Wooldridge's widely-used graduate text Econometric Analysis of Cross Section and Panel Data (MIT Press, 2001).
Journal ArticleDOI
The central role of the propensity score in observational studies for causal effects
TL;DR: The authors discusses the central role of propensity scores and balancing scores in the analysis of observational studies and shows that adjustment for the scalar propensity score is sufficient to remove bias due to all observed covariates.
Journal ArticleDOI
An Introduction to Propensity Score Methods for Reducing the Effects of Confounding in Observational Studies
TL;DR: The propensity score is a balancing score: conditional on the propensity score, the distribution of observed baseline covariates will be similar between treated and untreated subjects, and different causal average treatment effects and their relationship with propensity score analyses are described.
BookDOI
Designing Social Inquiry: Scientific Inference in Qualitative Research
TL;DR: For instance, King, Keohane, Verba, and Verba as mentioned in this paper have developed a unified approach to valid descriptive and causal inference in qualitative research, where numerical measurement is either impossible or undesirable.
Journal ArticleDOI
Some practical guidance for the implementation of propensity score matching
Marco Caliendo,Sabine Kopeinig +1 more
TL;DR: Propensity score matching (PSM) has become a popular approach to estimate causal treatment effects as discussed by the authors, but empirical examples can be found in very diverse fields of study, and each implementation step involves a lot of decisions and different approaches can be thought of.
References
More filters
Journal ArticleDOI
University Group Diabetes Program
TL;DR: The UGDP was undertaken to evaluate prospectively the influence of treatment upon the development of complications in adult-onset diabetics and the basic question, so vital to the day-to-day care of diabetic patients, has not been answered to date.
Journal ArticleDOI
The University Group Diabetes Program. A further statistical analysis of the mortality findings.
TL;DR: With no evidence of efficacy and a definite possibility of toxicity the investigators concluded that the safety of the patients still receiving tolbutamide therapy required its discontinuance and that the factual basis for this decision needed to be communicated to the biomedical scientific community.
Journal ArticleDOI
Statistics: A Guide to the Unknown.
Vanderlyn R. Pine,Judith M. Tanur,Frederick Mosteller,William Kruskal,Richard F. Link,Richard S. Pieters,Gerald R. Rising +6 more
Journal ArticleDOI
Design and Analysis of Industrial Experiments.
TL;DR: In this article, a lecture on the "Design and Analysis of Industrial Experiments" given by Dr O. L. Davies on the 8th of May 1954 to the Industrial Section of the Vereniging voor Statistiek is described.