scholarly journals Graphical Models for Quasi-experimental Designs

2015 ◽  
Vol 46 (2) ◽  
pp. 155-188 ◽  
Author(s):  
Peter M. Steiner ◽  
Yongnam Kim ◽  
Courtney E. Hall ◽  
Dan Su
Keyword(s):  
Graphical Models ◽  
Instrumental Variable ◽  
Regression Discontinuity ◽  
Experimental Designs ◽  
Causal Effects ◽  
Confounding Bias ◽  
Randomized Controlled ◽  
Quasi Experimental ◽  
Causal Graphs ◽  
Latent Subgroups

Randomized controlled trials (RCTs) and quasi-experimental designs like regression discontinuity (RD) designs, instrumental variable (IV) designs, and matching and propensity score (PS) designs are frequently used for inferring causal effects. It is well known that the features of these designs facilitate the identification of a causal estimand and, thus, warrant a causal interpretation of the estimated effect. In this article, we discuss and compare the identifying assumptions of quasi-experiments using causal graphs. The increasing complexity of the causal graphs as one switches from an RCT to RD, IV, or PS designs reveals that the assumptions become stronger as the researcher’s control over treatment selection diminishes. We introduce limiting graphs for the RD design and conditional graphs for the latent subgroups of compliers, always takers, and never takers of the IV design, and argue that the PS is a collider that offsets confounding bias via collider bias.

scholarly journals Effect of holding office on the behavior of politicians

2016 ◽  
Vol 113 (48) ◽  
pp. 13690-13695 ◽  
Author(s):  
Daniel Enemark ◽  
Clark C. Gibson ◽  
Mathew D. McCubbins ◽  
Brigitte Seim
Keyword(s):  
Regression Discontinuity ◽  
Experimental Designs ◽  
Causal Effects ◽  
Government Officials ◽  
Public Resources ◽  
Previous Election ◽  
Vote Trading ◽  
Recruitment And Selection ◽  
Behavioral Games ◽  
Norm Of Reciprocity

Reciprocity is central to our understanding of politics. Most political exchanges—whether they involve legislative vote trading, interbranch bargaining, constituent service, or even the corrupt exchange of public resources for private wealth—require reciprocity. But how does reciprocity arise? Do government officials learn reciprocity while holding office, or do recruitment and selection practices favor those who already adhere to a norm of reciprocity? We recruit Zambian politicians who narrowly won or lost a previous election to play behavioral games that provide a measure of reciprocity. This combination of regression discontinuity and experimental designs allows us to estimate the effect of holding office on behavior. We find that holding office increases adherence to the norm of reciprocity. This study identifies causal effects of holding office on politicians’ behavior.

scholarly journals Mobile Health for First Nations Populations: Systematic Review

10.2196/14877 ◽  
2019 ◽  
Vol 7 (10) ◽  
pp. e14877 ◽  
Author(s):  
Georgina R Hobson ◽  
Liam J Caffery ◽  
Maike Neuhaus ◽  
Danette H Langbecker
Keyword(s):  
Mental Health ◽  
Systematic Review ◽  
First Nations ◽  
Clinical Effectiveness ◽  
The United States ◽  
Experimental Designs ◽  
Controlled Trials ◽  
Randomized Controlled ◽  
Quasi Experimental ◽  
User Perspectives

Background The ubiquitous presence and functionality of mobile devices offers the potential for mobile health (mHealth) to create equitable health opportunities. While mHealth is used among First Nations populations to respond to health challenges, the characteristics, uptake, and effectiveness of these interventions are unclear. Objective This review aimed to identify the characteristics of mHealth interventions (eg, study locations, health topic, and modality) evaluated with First Nations populations and to summarize the outcomes reported for intervention use, user perspectives including cultural responsiveness, and clinical effectiveness. In addition, the review sought to identify the presence of First Nations expertise in the design and evaluation of mHealth interventions with First Nations populations. Methods The methods of this systematic review were detailed in a registered protocol with the International Prospective Register of Systematic Reviews (PROSPERO, CRD42019123276). Systematic searches of peer-reviewed, scientific papers were conducted across 7 databases in October 2018. Eligible studies had a primary focus on mHealth interventions with experimental or quasi-experimental design to respond to a health challenge with First Nations people from Canada, Australia, New Zealand, and the United States. Two authors independently screened records for eligibility and assessed risk of bias using the Joanna Briggs Institute checklists. Data were synthesized narratively owing to the mix of study designs, interventions, and outcomes. The review was reported in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses statement. Results Searches yielded 1053 unique records, after review and screening, 13 studies (5 randomized controlled trials and 8 quasi-experimental designs) were included in the final analysis. Studies were conducted in Australia (n=9), the United States (n=2), and New Zealand (n=2). The most common health challenge addressed was mental health and suicide (n=5). Intervention modalities included text messaging (n=5), apps (n=4), multimedia messaging (n=1), tablet software (n=1), or a combination of short messaging service (SMS) and apps (n=1). Results showed mixed engagement with the intervention (n=3); favorable user perspectives, including acceptability and cultural appropriateness (n=6); and mixed outcomes for clinical effectiveness (n=10). A diverse range of risks of bias were identified, the most common of which included a lack of clarity about allocation and blinding protocols and group treatment for randomized controlled trials and a lack of control group and single outcome measures for quasi-experimental designs. First Nations expertise informed all mHealth studies, through authorship (n=8), affiliation with First Nations bodies (n=3), participatory study design (n=5), First Nations reference groups (n=5), or a combination of these. Conclusions mHealth modalities, including SMS and apps, appear favorable for delivery of health interventions with First Nations populations, particularly in the area of mental health and suicide prevention. Importantly, First Nations expertise was strongly embedded within the studies, augmenting favorable use and user engagement. However, evidence of efficacy is limited.

An Evaluation of School Improvement Grants Using Regression Discontinuity and Quasi-Experimental Designs

2017 ◽  
Author(s):  
Jonathan Nakamoto ◽  
Staci J. Wendt ◽  
John A. Rice ◽  
Juan Carlos Bojorquez ◽  
Anthony Petrosino
Keyword(s):  
School Improvement ◽  
Regression Discontinuity ◽  
Experimental Designs ◽  
School Improvement Grants ◽  
Quasi Experimental

scholarly journals Quasi-Experimental Designs For Measuring Impacts Of Developmental Highways In Rural Areas

1992 ◽  
Vol 24 (1) ◽  
pp. 199-207 ◽  
Author(s):  
Josef M. Broder ◽  
Teresa D. Taylor ◽  
Kevin T. McNamara
Keyword(s):  
Decision Making ◽  
Rural Areas ◽  
Economic Activity ◽  
Regression Discontinuity ◽  
Experimental Designs ◽  
Economic Decline ◽  
Economic Changes ◽  
Control Models ◽  
Quasi Experimental ◽  
Per Capita

AbstractQuasi-experimental techniques were developed to provide decision-making tools for documenting the impacts of developmental highways in rural areas. Regression discontinuity analysis (RDA) with limited observations was used to compare economic changes in highway counties to those in adjacent and non-adjacent control counties. The RDA models found statistically significant changes in population, per capita income, and taxable sales related to highway development. The study found that some counties benefitted from developmental highways, some were unchanged, while some experienced economic decline. RDA models with adjacent controls had better explanatory powers while those with non-adjacent controls were more sensitive to highway-related changes in economic activity. When significant non-highway activities were present, adjacent control models may have understated highway-related impacts, while non-adjacent control models may have overstated these impacts. Arguments for using adjacent and non-adjacent experimental designs are discussed.

scholarly journals Methods to Estimate Causal Effects - An Overview on IV, DiD and RDD and a Guide on How to Apply them in Practice

2021 ◽  
Author(s):  
Matthias Collischon
Keyword(s):  
Social Sciences ◽  
Instrumental Variable ◽  
Regression Discontinuity ◽  
Estimation Method ◽  
Causal Effects ◽  
Small Scale ◽  
Regression Discontinuity Design ◽  
Difference In Differences ◽  
Estimation Techniques ◽  
Online Appendix

The identification of causal effects has gained increasing attention in social sciences over the last years and this trend also has found its way into sociology, albeit on a relatively small scale. This article provides an overview of three methods to identify causal effects that are rarely used in sociology: instrumental variable (IV) regression, difference-in-differences (DiD), and regression discontinuity design (RDD). I provide intuitive introductions to these methods, discuss identifying assumptions, limitations of the methods, promising extension, and present an exemplary study for each estimation method that can serve as a benchmark when applying these estimation techniques. Furthermore, the online appendix to this article contains Stata syntax that simulates data and shows how to apply these techniques in practice.

Maximum Likelihood Analysis for a Generalized Regession-Discontinuity Design

1984 ◽  
Vol 9 (1) ◽  
pp. 45-60 ◽  
Author(s):  
Ronald A. Visser ◽  
Jan De Leeuw
Keyword(s):  
Maximum Likelihood ◽  
Regression Discontinuity ◽  
Bivariate Distribution ◽  
Causal Effects ◽  
Regression Discontinuity Design ◽  
Maximum Likelihood Analysis ◽  
Design Data ◽  
Likelihood Analysis ◽  
Quasi Experimental ◽  
Tests Of Hypotheses

The regression-discontinuity design (RDD) offers the possibility of making inferences about causal effects from observations on selected groups. The quasi-experimental groups are formed by dividing the scores of a premeasurement in two halves. The treatment effect is inferred from the differences between the regression of a postmeasurement on the premeasurement for the two groups. We discuss a generalized form of this design: (a) Apart from parallel shift of the regression lines, differences in variance and covariance are considered; (b) pretest and posttest may be multivariate; and (c) more than two groups may be involved in the design. Data from such a design are considered to have a truncated bivariate distribution. For the RDD, maximum likelihood parameter estimation procedures and tests of hypotheses are presented.

scholarly journals The Effect of Education on Health and Mortality: A Review of Experimental and Quasi-Experimental Evidence

2018 ◽  
Author(s):  
Titus Galama ◽  
Adriana Lleras-Muney ◽  
Hans van Kippersluis
Keyword(s):  
Peer Group ◽  
Twin Studies ◽  
Convincing Evidence ◽  
Causal Effects ◽  
Quality Of Education ◽  
Market Returns ◽  
Randomized Controlled ◽  
Quasi Experimental ◽  
Health And Mortality

Education is strongly associated with better health and longer lives. However, the extent to which education causes health and longevity is widely debated. We develop a human capital framework to structure the interpretation of the empirical evidence and review evidence on the causal effects of education on mortality and its two most common preventable causes: smoking and obesity. We focus attention on evidence from randomized controlled trials, twin studies, and quasi-experiments. There is no convincing evidence of an effect of education on obesity, and the effects on smoking are only apparent when schooling reforms affect individuals’ track or their peer group, but not when they simply increase the duration of schooling. An effect of education on mortality exists in some contexts but not in others and seems to depend on (i) gender, (ii) the labor market returns to education, (iii) the quality of education, and (iv) whether education affects the quality of individuals’ peers.

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