The command rdmc applies to noncumulative and cumulative multicuto rd settings, following recent work incattaneo, keele, titiunik, and vazquezbare2016a, 2019b. Regression discontinuity rd is an observational research design which can be used to make causal inference of program effects in nonexperimental situations. Regression discontinuity for causal effect estimation in. Regression discontinuity design rdd is a quasiexperimental evaluation option that measures the impact of an intervention, or treatment, by applying a treatment assignment mechanism based on a continuous eligibility index which is a variable with a continuous distribution. I am running a regression discontinuity model to assess the use of a medical education intervention for prescription guideline adherence, where the intervention or discontinuity in question the time when a guideline dosage for a particular medication changes. Is there a command for running a regression discontinuity desgin in stata. The costeffectiveness of regression testing techniques varies with characteristics of. The lines were handdrawn to show an approximate example of how the final result should look. Local linear regression discontinuity analyses were conducted using the rdrobust program in stata 14 for information about this software and corresponding techniques, see calonico et. Hi, i am new to this forum so i hope the format in which im asking this question makes sense. In this article, we describe a major upgrade to the stata and r software package rdrobust calonico,cattaneo,andtitiunik2014a,2015b,whichprovidesawidearray. Problem using rdrobust and rdplots command in stata 14.
There has been a growing use of regression discontinuity design rdd, introduced by thistlewaite and campbell 1960, in evaluating impacts of development programs. Lets begin by showing some examples of simple linear regression using stata. Regression discontinuity design regression discontinuity rdd is a research design for the purposes of causal inference. It is one of the most credible quasiexperimental research designs for identi. Even though researchers do not control the assignment, substantive knowledge about the threshold serves as a basis for a strong identification claim. How to graph a tendency line in a discontinuous regression in. The running variable is age and the two cutoff points are at 60. For example, assignment to a treatment group might be determined by a schools average achievement score on a statewide exam. For example, perhaps students in a school take a test in 8th grade. A practical introduction to regression discontinuity designs. Philippe van kerm asked me that same question in 2008, and in the absence of any new insight, my answer is the same. Extensions,cattaneo, idrobo, and titiunik, collects and expands the instructional materials we prepared for more than 30 short courses and workshops on regression discontinuity rd methodology taught over the years 20142018. Rd relies on regression, yet rd identication is distinct. Manipulation testing based on density discontinuity.
If y has any features one would like to account for for example, it could be a count variable then this can be done in an rd framework. How to conduct a regression discontinuity on stata statalist. What he was working on and the conclusions of the paper was interesting but even more interesting was a release by him and coauthors of a stata package that implements rd design for easy. Regression discontinuity world bank sief aphrc impact evaluation training 2015 owen ozier development research group the world bank 6 may 2015 owen ozier the world bank regression discontinuity 6 may 2015 1 9. The main trouble with the design is that there is vanishingly little data exactly at the cutoff, so any answer strategy needs to use data that is some distance away from the cutoff. Estimating causal effects using a regressiondiscontinuity approach stata textbook examples. Linear regression analysis in stata procedure, output and. I mean for getting the graphs and carrying out the local regression. Regression discontinuity rd designs with multiple cutoffs or multiple scores are. As ive said im beginning to study statistics and have read a bit on regression discontinuity designs but i dont know if all the computations to get the discontinuity graph and the local average effect should be done by hand or if theres a stata command that may help im thinking of a sharp regression discontinuity design as a. How to graph a tendency line in a discontinuous regression in stata. The regressiondiscontinuity rd design is widely used in applied work. We describe a major upgrade to the stata and r rdrobust package, which provides a wide array of estimation, inference, and falsification methods for the analysis and interpretation of regression discontinuity designs. It presents the basic theory behind the research design, details when rd is likely to be valid or invalid given economic incentives.
If there are thresholds whereby some observations receive the treatment above it, other those below it do not, and those immediately above or below that threshold are similar, we can use the difference of the outcome between those just above and those just below the threshold to estimate the causal effect of the treatment. Stata module for regression discontinuity estimation. Local linear regression is used to construct point estimates. For example, i would use local poisson regression coupled with local. It provides point estimators, confidence intervals estimators, bandwidth selectors, automatic rd plots, and other related features. Rddtools is a new r package under development, designed to offer a set of tools to run all the steps required for a regression discontinuity design rdd analysis, from primary data visualisation to discontinuity estimation, sensitivity and placebo testing. Stata module for regression discontinuity estimation econpapers. It can be used in cases where treatment is assigned based on a cutoff value of a running variable. The success case method scm involves identifying the most and least successful cases in a program and examining them in detail. We thank stephane bonhomme, david drukker, kosuke imai, michael jansson, lutz kilian, pat kline, xinwei. Ive got no specific experience with regression discontinuity in stata.
Mar 07, 2020 the rdrobust package provides stata and r implementations of statistical inference and graphical procedures for regression discontinuity designs employing local polynomial and partitioning methods. You may also be interested in our propensity score analysis workshop register overview. Estimating causal effects using a regression discontinuity approach stata textbook examples. In the standard regression discontinuity design setup, the probability of treatment changes discontinuously if a scalar covariate exceeds a cuto. Regression discontinuity designs identify a local average treatment effect.
If i specified the model and most importantly the ivs correctly as i have never worked on a rdd before. In rd, you have a situation where you assigned some treatment based on a hard cutoff on a score. Copy the do and help files into your stata working directory or use statas net install command to access them remotely from a web page. This command now offers datadriven bandwidth selection for ei ther one. The main new features of this upgraded version are as follows. General description of estimator examples detailed syntax description of options. However, it doesnt sound like this is a regression discontinuity problem to me. The rdrobust package provides stata and r implementations of statistical inference and graphical procedures for regression discontinuity designs employing local polynomial and partitioning methods. In part 2, a comparison of userwritten stata estimation packages is provided. Graphs in regression discontinuity design in stata or r.
We describe a major upgrade to the stata and r rdrobust package, which provides a wide array of estimation, inference, and falsification methods for the analysis and interpretation of regressiondiscontinuity designs. Regression discontinuity designs in economics david s. Regression discontinuity rdrobust with curvinlinear post. This approach was developed by robert brinkerhoff to assess the impact of organisational interventions, such as training and coaching, though the use of scm is not limited to this context. This book is composed of four chapters covering a variety of topics about using stata for regression. Regression discontinuity practical applications basic intuition ii we see these institutional rules all the time cannot get medicaid unless income is below 150 percent of the poverty line must have a gpa of 3. In this article, we describe a major upgrade to the stata and r software package rdrobust. Regression discontinuity design in stata part 1 stata. Regression discontinuity design in stata part 1 stata daily. This article describes a major upgrade to the stata and r rdrobust package, which provides a wide array of estimation, inference and falsi cation methods for the analysis and interpretation of regression discontinuity rd designs. Improving causal inference in educational and social science research by richard j. If there are thresholds whereby some observations receive the treatment above it, other those below it do not, and those immediately above or below that threshold are similar, we can use the difference of the outcome between those just above and those just below the threshold to estimate the causal effect of the. The regression discontinuity design rdd is a quasiexperimental approach that was developed specifically to minimize confounding bias in the assessment of policies, treatments and interventions that are based on a cutoff rule or threshold.
How to graph a tendency line in a discontinuous regression. We should emphasize that this book is about data analysis and that it demonstrates how stata can be used for regression analysis, as opposed to a book that covers the statistical basis of multiple regression. Statistical software components from boston college department of economics. This second empirical example is not discussed in the text to conserve space, and because it is already analyzed in our companion software articles. We focus on estimation by local linear regression, which was shown to have attractive properties porter, j. In part 3, validation or falsification tests are discussed.
There will be units with the same values of the controls matches but with di. Local linear regression discontinuity analyses were conducted using the rdrobust program in stata 14 for information about this software and corresponding techniques, see calonico et al. Linear regression analysis using stata introduction. Software for regressiondiscontinuity designs matias d. For example, i would use local poisson regression coupled with local logit estimation for the treatment. Regression discontinuity designs identify causal e. Regression discontinuity designs for evaluating programs. Regression discontinuity and practical applications. Regression discontinuity rd analysis is a rigorous nonexperimental1 approach that can be used to estimate program impacts in situations in which candidates are selected for treatment based on whether their value for a numeric rating exceeds a designated threshold or cutpoint. Regression discontinuity world bank sief aphrc impact. The difference to the usual case is that im considering not just one but two cutoff pointsdiscontinuities. Regression discontinuity rd analysis is a rigorous nonexperimental1 approach that can be used to estimate program impacts in situations in which candidates are selected for.
The command rdmc applies to noncumulative and cumulative multicutoff rd set. The main new features of this upgraded version are. In the standard regression discontinuity design setup, the probability of treatment changes discontinuously if a. Schools scoring below a certain threshold are selected for inclusion in the treatment group, and schools scoring above. Linear regression, also known as simple linear regression or bivariate linear regression, is used when we want to predict the value of a dependent variable based on the value of an independent variable. Default is sharp rd design and hence this option is not used. This variable may be continuous, meaning that it may assume all values within a range, for example, age or height, or it may be dichotomous, meaning that the variable may assume only one of two values. Regression testing is an expensive testing process used to validate software following modifications. Browse other questions tagged r regression datavisualization stata regressiondiscontinuity or ask your own. Example regression discontinuity data owen ozier 2015 vars. As ive said im beginning to study statistics and have read a bit on regression discontinuity designs but i dont know if all the. Regression discontinuity designs with rd package and binary. Lee and thomas lemieux this paper provides an introduction and user guide to regression discontinuity rd designs for empirical researchers.
A practical guide to regression discontinuity mdrc. However baseline labour supply rates for the treated sample 68% are lower. Dec 16, 2015 regression discontinuity design in stata part 1 posted on 16 december 2015 by mitch abdon there has been a growing use of regression discontinuity design rdd, introduced by thistlewaite and campbell 1960, in evaluating impacts of development programs. The stata journal analysis of regression discontinuity.
Regression discontinuity rd designs, sharp discontinuity. Login or register by clicking login or register at the topright of this page. Regression discontinuity designs exploit substantive knowledge that treatment is assigned in a particular way. In regression matching we hope that treatment is as good as randomly assigned after conditioning on controls. In statistics, econometrics, political science, epidemiology, and related disciplines, a regression discontinuity design rdd is a quasiexperimental pretestposttest design that elicits the causal effects of interventions by assigning a cutoff or threshold above or below which an intervention is assigned. This workshop provides an introduction to the practical application of regression discontinuity design in evaluating programs and policies. In this type of regression, we have only one predictor variable. He was presenting some of his work on nonparametric regression discontinuity design which i found interesting. We investigate the choice of the bandwidth for the regression discontinuity estimator. A practical introduction to regression discontinuity. Notes for matlab and stata regression discontinuity software. It can be obtained using the lowess command in stata.
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