A Brief History of the Potential Outcomes Approach to Causal Inference

2015 ◽  
pp. 23-30
Keyword(s):  
Causal Inference ◽  
Potential Outcomes ◽  
History Of

Assessment for Monitoring of Education Systems: International Comparisons

2019 ◽  
Vol 683 (1) ◽  
pp. 75-92 ◽  
Author(s):  
Henry I. Braun ◽  
Judith D. Singer
Keyword(s):  
Education Policy ◽  
Causal Inference ◽  
Instrument Development ◽  
Global Education ◽  
Large Scale ◽  
International Comparisons ◽  
Education Policies ◽  
Country Rankings ◽  
History Of ◽  
Comparative Description

Over the last two decades, with the increase in both numbers of participating jurisdictions and media attention, international large-scale assessments (ILSAs) have come to play a more salient role in global education policies than they once did. This has led to calls for greater transparency with regard to instrument development and closer scrutiny of the use of instruments in education policy. We begin with a brief review of the history of ILSAs and describe the requirements and constraints that shape ILSA design, implementation, and analysis. We then evaluate the rationales of employing ILSA results for different purposes, ranging from those we argue are most appropriate (comparative description) to least appropriate (causal inference). We cite examples of ILSA usage from different countries, with particular attention to the widespread misinterpretations and misuses of country rankings based on average scores on an assessment (e.g., literacy or numeracy). Looking forward, we offer suggestions on how to enhance the constructive roles that ILSAs play in informing education policy.

scholarly journals Invited Commentary: Counterfactuals in Social Epidemiology—Thinking Outside of “the Box”

2019 ◽  
Vol 189 (3) ◽  
pp. 175-178 ◽  
Author(s):  
Tyler J VanderWeele
Keyword(s):  
Social Movements ◽  
Causal Inference ◽  
Social Determinants Of Health ◽  
Social Determinants ◽  
Social Epidemiology ◽  
Determinants Of Health ◽  
Potential Outcomes ◽  
The Social ◽  
Potential Outcomes Framework

Abstract There are tensions inherent between many of the social exposures examined within social epidemiology and the assumptions embedded in quantitative potential-outcomes-based causal inference framework. The potential-outcomes framework characteristically requires a well-defined hypothetical intervention. As noted by Galea and Hernán (Am J Epidemiol. 2020;189(3):167–170), for many social exposures, such well-defined hypothetical exposures do not exist or there is no consensus on what they might be. Nevertheless, the quantitative potential-outcomes framework can still be useful for the study of some of these social exposures by creative adaptations that 1) redefine the exposure, 2) separate the exposure from the hypothetical intervention, or 3) allow for a distribution of hypothetical interventions. These various approaches and adaptations are reviewed and discussed. However, even these approaches have their limits. For certain important historical and social determinants of health such as social movements or wars, the quantitative potential-outcomes framework with well-defined hypothetical interventions is the wrong tool. Other modes of inquiry are needed.

Collaborative Documentation in Mental Health: Applications to Rehabilitation Counseling

2016 ◽  
Vol 30 (3) ◽  
pp. 305-320 ◽  
Author(s):  
Lindsay Sheehan ◽  
Todd Lewicki
Keyword(s):  
Mental Health ◽  
Health Care ◽  
Critical Analysis ◽  
Rehabilitation Counseling ◽  
Potential Outcomes ◽  
Community Mental Health Care ◽  
Rigorous Research ◽  
History Of ◽  
Documentation Systems ◽  
Health Applications

Purpose: In this article, the emerging practice of collaborative documentation (CD) in community mental health care and its applications to rehabilitation counseling were explored. CD has the potential to promote greater client empowerment, clinical transparency, and documentation efficiency and quality; however, the CD process is not well validated through rigorous research.Method: We provide a critical analysis of issues with current documentation systems, principles of creating collaborative paperwork, and the potential outcomes for rehabilitation clients, agencies, and counselors who use CD.Results: The benefits of CD for rehabilitation educators, researchers, and practitioners will be provided for implementation in rehabilitation settings.Conclusion: Rehabilitation practitioners may be increasingly exposed to CD and transparency of treatment records. CD is a developing practice that fits well with the rehabilitation counseling philosophy and the profession’s history of client inclusion in treatment planning.

scholarly journals Causal inference under multiple versions of treatment

2013 ◽  
Vol 1 (1) ◽  
pp. 1-20 ◽  
Author(s):  
Tyler J. VanderWeele ◽  
Miguel A. Hernan
Keyword(s):  
Causal Inference ◽  
Treatment Effect ◽  
Indirect Effects ◽  
Causal Effect ◽  
Potential Outcomes ◽  
Direct And Indirect Effects ◽  
Treatment Variable ◽  
Effect Of Treatment ◽  
New Treatment ◽  
Potential Outcomes Framework

Abstract: In this article, we discuss causal inference when there are multiple versions of treatment. The potential outcomes framework, as articulated by Rubin, makes an assumption of no multiple versions of treatment, and here we discuss an extension of this potential outcomes framework to accommodate causal inference under violations of this assumption. A variety of examples are discussed in which the assumption may be violated. Identification results are provided for the overall treatment effect and the effect of treatment on the treated when multiple versions of treatment are present and also for the causal effect comparing a version of one treatment to some other version of the same or a different treatment. Further identification and interpretative results are given for cases in which the version precedes the treatment as when an underlying treatment variable is coarsened or dichotomized to create a new treatment variable for which there are effectively “multiple versions”. Results are also given for effects defined by setting the version of treatment to a prespecified distribution. Some of the identification results bear resemblance to identification results in the literature on direct and indirect effects. We describe some settings in which ignoring multiple versions of treatment, even when present, will not lead to incorrect inferences.

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