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Questions tagged [treatment-effect]

A treatment effect is the causal effect of some "treatment" or policy intervention on an outcome variable. Such effects can be estimated with data from randomized or quasi experiments, and clinical trials or with observational data and methods for causal inference.

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Which Theories of Causality Should I know?

Which theoretical approaches to causality should I know as an applied statistician/econometrician? I know the (a very little bit) Neyman–Rubin causal model (and Roy, Haavelmo etc.) Pearl's Work on ...
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Unconfoundedness in Rubin's Causal Model- Layman's explanation

When implementing Rubin's causal model, one of the (untestable) assumptions that we need is unconfoundedness, which means $$(Y(0),Y(1))\perp T|X$$ Where the LHS are the counterfactuals, the T is the ...
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Using control variables in experiments?

Why would one want to control for any number of baseline covariates in a situation where the assignment to treatment group is random? My understanding is that randomly assigning treatment should make ...
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What is the best way to visualize difference-in-differences (multi-period) regression?

What's the best way to visualize difference-in-differences for both binary and continuous treatment? Do I regress the outcome variable on the set of controls but exclude the treatment variable and ...
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487 views

Instrument Variables and Exclusion Restriction from a Mediation perspective

I'm having trouble making sense of the exclusion restriction in instrumental variables. I understand that the unbiased treatment effect is $B = \frac{Cov(Y, Z)}{Cov(S, Z)}$, where $Y$ is the outcome,...
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733 views

Treatment Effect Bounds

My supervisor and I have run a randomized experiment in a developing country. Due to administrative problems there we unfortunately have the problem of non-response. This non-response is also not ...
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3k views

ATT vs ATE in propensity score matching when using DiD estimates

According to Lee and Little 2017, when using propensity score (PS) methods, weighting on odds will generate the Average Treatment Effect on the Treated (ATT), while using subclassification and ...
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514 views

Analysis strategy for rare outcome with matching

I'm working with a dataset of ~100,000 individuals where ~500 (0.5%) individuals received treatment. I have several continuous and count outcomes for all observations that I would like to compare ...
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14k views

How do I interpret a “difference-in-differences” model with continuous treatment?

How do I interpret the ATE coefficient (i.e., the post-treatment indicator interacted with the continuous variable)? Does it make sense? Should I break it down into subgroups and just run a fixed ...
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366 views

Propensity Score Matching – How do the mechanics lead to a different result than unmatched?

The gist of propensity score matching, as I understand it, is as follows: You want to estimate the average treatment effect (ATE) of a treatment on some outcome. However, if you simply calculate the ...
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190 views

When is it valid to use race/ethnicity in causal inference?

It seems that often in social science, race is examined in causal terms, as researchers are interested in the differences between various ethnic groups in outcomes when controlling for other ...
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239 views

Propensity Score can be used as a covariate in regression?

I have treated and control groups with a problem of selection in the treatment group. I am interested in the identification of the following model: $y= exp(X^\prime\beta + \alpha\cdot T)$ where $T$ ...
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Propensity Score Analysis with continuous treatment

I have an observational dataset of about two dozen observed variables (continuous or discrete), plus a continuous variable of which I would like to measure the causal impact of on my dependent ...
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608 views

Statistical tests for comparing a skewed clinical sample

I recently surveyed 350 low-income families -- they were randomly split into two groups: control and treatment. One of the variables I am very interested in is the amount of savings of each family. ...
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Propensity Score Matching with Panel Data

I have a Panel Data Set from 2000 to 2013 and I want to use Propensity Score Matching to analyze it. The treatment variable varies between individuals over time, an individual can get treated any time ...
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796 views

Can p values be used to show impact of treatment

Does it make sense to use the differences in p value to show a tendency or the 'importance' of the effect of a treatment. for example, I have treated a contaminated soil and I test the treatments ...
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Dynamic treatment timing in a panel-DiD framework

I have a question regarding the timing of treatment effects and how one could use the difference-in-difference estimator on a panel data set. Let me begin by saying that I have a big firm level ...
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how to include distance buffers in cluster randomized trial

I need to incorporate distance buffers into the selection of treatment and control units in a randomized-controlled trial in order to minimize spillovers between arms. Cluster in this study is a ...
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Standardized mean decomposition (Oaxaca-Blinder decomposition)

How does standardized mean decomposition differ from the simpler dummy variable regression? How does the average in mean outcomes or interpretation of results attributable to a particular treatment or ...
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Interactions in Propensity Score Models

I am doing an analysis to see if a first-year seminar has an effect on student retention in college. Students choose whether or not to enroll in the seminar on their own, so it seems like it makes ...
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687 views

Seasonality of treatment and Average Treatment Effect

I have panel data of sales for many stores in two comparable cities. One of the cities holds a special event once a month (the treatment) which is expected to boost sales across the board on that day. ...
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Why do my boostrapped CI's (using boot.ci in R) not include the point estimate?

I'm interested in estimating an average treatment effect $$ \operatorname{ATE}\left(A', A''\right) = \mathbb{E}\left( Y\ |\ A'' \right) - \mathbb{E}\left( Y\ |\ A' \right) $$ with a generalized ...
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Adjusting for baseline as covariate in observational studies

The scenario is regarding treatment effect in an observational study (i.e. not randomised): those given the treatment would be more unwell at baseline. A clinical trials statistician suggested adding ...
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One-to-many matching of propensity scores and average treatment effect on the treated

I've been working on a propensity score matching project, but having no stats classes under my belt I'm struggling to calculate the so called "average treatment effect on the treated" (ATT) so that it ...
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Standard error clustering under treatment assignment in groups of varying size

Basic setup: Unit of observation is the individual. Treatment (binary) is assigned on city level. Every state contains 4 cities, 2 get randomly chosen for treatment, 2 control. There are only few (e....
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Difference between marginal and conditional treatment effect? Relating to regression vs. propensity score methods

Peter Austin has a nice introduction to propensity score methods (citation below), and he states that one of the differences between PS methods and plain regression is that PS methods give you a ...
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Can covariance be derived from means and variances?

In treatment studies it is common to report multiple outcome measures from the same subjects. The treatment effects on these outcomes are typically correlated so this should be taken into account when ...
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Hypothesis testing - Wilcoxon test, bootstrapping, or something else?

A colleague has developed a treatment for to "prevent falls" in cognitively impaired, psychiatric patients. Since this would be very useful treatment in this population, we especially do not want to ...
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536 views

Continuous Treatment effect to assess the impact of Early vs Late treatment

I have an observational dataset with only treated observations with different ages, but treated at different times for 7 years. Each treatment had different durations; from 2 days to 160 days. The ...
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1answer
734 views

How to correctly measure effect on heavy-tailed distribution

I ran an experiment on my website where I randomly assigned users to either the treatment or control group, and have two questions about how to correctly compute significance of the results. Some ...
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1answer
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IPTW for multiple treatments

I am dealing with a dataset where patients are subjected to multiple treatments A or B or C or D . Since there are four treatment options I am using multinomial regression to estimate the propensity ...
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2answers
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Propensity score matching on panel data with treatment varying by periods

I have a panel data of 200 individuals around 100 weeks. A latent ability issue for individual may cause the estimation for one IV biased. This IV is continuous variable. Except for panel fixed-...
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2answers
510 views

Difference-in-difference model with mediators: Estimating the effect of different elements of a policy

How do I conduct a mediation analysis in a difference-in-difference setting? For example, a city selects some neighborhoods for a new crime fighting strategy (the treatment $D$) that involves an ...
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1answer
3k views

Difference ATE and ATET?

I have some problems understanding the difference between ATE and ATET and the Selection Bias. To explain what my understanding is I have done the following representation so you can correct me: We ...
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1answer
651 views

How to test significance of pre-post difference scores on 8 measures (1 group)

I have a set of pre and post treatment scores on 8 measures. I'd like to test which of these show significant improvement after treatment. If I use within-subjects t tests it will mean carrying out 8 ...
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271 views

multiplicative treatment effects with standard errors

I simplified this a fair bit after finding a draft version of the Imbens and Rubin chapter. I am interested in estimating a constant multiplicative treatment effect from a randomized experiment. I ...
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1answer
367 views

Diff-in-Diff with multiple treatment groups

I have monthly panel data and I want to estimate the effects of two different treatments that occur in different time periods. The treatment groups are not the same. An individual can belong one, both ...
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418 views

Panel data regression on the effect of a treatment without control group

I have a panel data set. The dependent variable is a certain numerical score for each individual and time period. I have a number of independent variables that vary by individual, by time, or by both. ...
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How to deal with treatment effects that occurs multiple times at different time for each individual ID

I've been searching for a long time for this issue and couldn't find the proper answer so I post a question here. Here I put the data set example first. ...
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Family-wise error of dependent tests?

Say you have a drug of which you want to test wether it increases the number of immune cells in your blood. You divide your sample in two groups where one group receives the treatment and the other ...
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1answer
999 views

Significant difference from regression confidence intervals

I have a question about statistical significance in relation to confidence intervals from linear regression. I'm obviously far from a stats expert, and I've been searching for the answer to this, ...
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349 views

Heterogeneous Treatment Effects - How to test differences in the ATE?

I want to conduct a simple propensity score estimation where the treatment $D_i$ is a binary variable ($D_i=1$ individual $i$ participates in the labor market program, zero otherwise). I estimate the ...
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1answer
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Testing the significance of differences in frequencies across treatments using $\chi^2$ test

I've run a small experiment and need to test the data by comparing the frequencies of different treatments, specifically, whether they are significantly different. I think the chi-squared test is ...
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1answer
67 views

Average treatment effect in binary choice model

All the random variables below are defined on the same probabiluty space $(\Omega, \mathcal{F}, \mathbb{P})$. Consider the following model $$ Y\equiv 1\{\epsilon > \beta_0+\beta_1X\} $$ where $1$...
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1answer
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Cox Model vs. Logistic Regression for comparing two treatments? [closed]

I am trying to choose which statistical test(s) to use for my study. It is a retrospective cohort study comparing the outcomes of 2 different surgical oncology techniques (Let's call them Treatment X ...
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1answer
141 views

Experimental Design: Number of treatments and replications

I am learning about experimental design. I have been provided the following definitions: Factors: Variable(s) manipulated by researchers in order to observe response(s) Levels: Values of ...
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1answer
419 views

Not understanding reason for demeaning covariates in program evaluation regression

I am reading the Imbens et al. 2009 paper on program evaluation methods: http://dash.harvard.edu/bitstream/handle/1/3043416/imbens_recent.pdf?sequence=2 On page 24, discussing simple regression ...
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1answer
299 views

Treatment effect Analysis: What is Stratification and explanation/interpretation?

In this paper by Angrist a stratification estimator is used (page 16 formula (4)) to calculate the Average Treatment Effect on the Treated (ATOT). The formula is given by: \begin{align} \widehat{ATOT}...
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1answer
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How do I apply weights to a Cox Regression Model in R?

I am trying to answer the question of whether service in a certain organization has an effect on age of first marriage, and am interested in using the Cox model to understand the difference in the ...
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1answer
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Cluster RCT with different timing and exposure to treatment

We are currently evaluating a government Microenterprise program using a cluster RCT design. The treatment involves the provision of a grant to a poor household to start a micro-enterprise. We are ...