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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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Treatment effect (DID) heterogeneity conditional on a continous variable

as stated in the title, I'm thinking about exploring the heterogeneity of treatment effect result from a DID design based on a continuous variable. To be specific: \begin{align} & \mathrm{Profit}...
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Hypothesis testing with matrix of measurements

I need to test if a treatment has taken effect in a certain group of patients for which I make a measurement of the relevant variables before doing the treatment and afterwards. Usually, I would do a ...
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Control group + Treatment group - no post-test for the control group, many variables. Please help! [on hold]

So grateful for any help here... I have an experiment with a control group (n=80) and a treatment group (n=270) - both did pre-tests. I only have paired post-test data for 63 of the treatment group ...
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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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How to think of compliance (and IV and LATE) in phase-in RCT designs

How should we think of compliance in a phase-in RCT design? What are the assumptions recovering the LATE by instrumental variables in this case? Details: In a traditional (simultaneous) RCT, in case ...
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Estimation of average treatment effect based on nearest neighbor matching [closed]

I would like to use R to duplicate the treatment effect estimation method used in Stata. Specifically, this is the Stata method I would like to duplicate. I have tried the package ...
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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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Difference-in-differences with individual-level panel data

Main Idea I want to estimate the effect of a treatment that affected a group of individuals that are scattered over a larger geographic area in a short matter of time (a week) via DID. I have reason ...
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Treatment evaluation: Measuring statistically / clinically significant change in level over time

I am conducting a treatment evaluation. I am using an interrupted time series design (generalised linear mixed model; 42 monthly measurements per patient [18 pre-treatment, 24 post-treatment). I have ...
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Treatment effect estimation: year is treatment

I want to estimate the effect of tax increase on the consumption at the regional level. I have 100 regions in pre-treatment period (year 2010) and the same regions in post-treatment period (year 2011)....
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Standardized Difference to compare prevalence between 4 groups

In this article, https://www.tandfonline.com/doi/abs/10.1080/03610910902859574 Peter Austin describes how to calculate the standardized difference between two groups, pg 1229 and pg 1230. However am ...
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can I use a multilevel model for my situation? Pre/post, no control group

I have a question about whether multilevel modeling is appropriate in my situation. I’m working on an analysis looking at the effect of a treatment for patients with a disease. There is one pre ...
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Difference-in-differences model with time-fixed effects only

Assume that we have a panel data set with individuals' income (Y) over multiple years and a certain event (POST) in one year that is hypothesized to affect Y for a subgroup of these individuals (TREAT)...
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Pursuing meaningful questions about pre- post- intervention outcome measures in single condition treatment

If you are not fortunate enough to have a control group and have a single condition only, what meaningful questions can you ask about the change in pre to post intervention scores? If ANOVA or ANCOVA ...
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Finding most effective sequence of treatments

I am looking for (any) pointers on how to approach the following abstract problem. Not: my statistics background is very limited, so I might very well be missing something obvious. We have subjects ...
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comparsion of treatment groups based on different controls

I have experimental results from two days where I wasnt able to keep the same conditions from day1 to day2, so I have two sets of data: control day1 -- 2x treatment groups day1 control day2 -- 2x ...
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chi squared to assess the effectiveness of a treatment?

this is probably a weird situation: I am an assistant in a course teaching research methodology, yet I can't quite come up with an answer that satisfies me... My students are drafting a mock research ...
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What does it mean if the Average Treatment Effect (ATE) in causal inference is not identifiable?

I read from the following slides on observational studies, pg. 16, Observational Studies, Keio, that given: $$ ATE ≡ E[Y_i(1) − Y_i(0)] $$ They pose the following question: Can we identify the $ATE$...
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Stabilized propensity weights: intuition and ATT formula

The average treatment effect (ATE) of binary treatment T on outcome Y can be estimated using inverse propensity weights: \begin{equation}\nonumber \frac{\sum_{i=1}^{N}t_i\hat{\pi}_i^{-1}y_i}{\sum_{i=...
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How to Estimate Treatment Effects using Heckman two steps (Heckit)?

I need a help on how to find a treatment effects using Heckman two steps method (Heckit), I need to find ATE (Average treatment Effects), TT (Treatment on treated) and MTE. I tried to do a simulation ...
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Linear Regression: Calculating a treatment effect directly in regression vs. averaging potential outcomes

Suppose I have the following true model, where an individual $i$ at a particular point in time $t$ is either treated ($W=1)$ or untreated ($W=0$). The outcome for individual $i$ at time $t$ under ...
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DnD - Parallel trends in subgroups?

I am estimating a standard two period difference in differences model, where I estimate whether a policy change was associated with an individual level behavior change in a state that implemented it ...
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Propensity score matching: bias adjustment

I'm using propensity score matching to match similar individuals. I.e., I first estimate a propensity score (the probability of treatment conditional on some set of variables) and then match on the ...
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Comparing two difference-in-difference models when making the treatment group larger

I have a question regarding some potentially existing empirical tests in the difference-in-difference context. Assume that I have the usual setting of observing some hypothetical outcome for a ...
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Sample selection in difference-in-differences

I have a dependent variables with a significant amount of zeros (and the share of zeros is different between the control and treatment groups, and changes between the pre- and post-treatment periods). ...
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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 ...
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Best way to measure treatment effect across two treatments

I have two sets of patient-level data for two distinct treatments, unfortunately, the data is only over a 14 week period and I'm hoping to build a predictive model to estimate/simulate what the data ...
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Treatment (equivalent to experimental groups) in Experiment as Fixed AND Random Effect in Mixed Model Linear Regression

I have data from a sociology experiment with three groups. Each group is equivalent with a different treatment for a subject (n=700). The treatment were surveys, differing in the amount of information ...
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Testing two potential interaction variables (or potential sources of effect heterogeneity) against each other

I have an experiment I have run, and I am testing for heterogeneous treatment effects (pre-registered and not fishing for any particular result!). Let's call the outcome $Y$ and the treatment variable ...
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Deterministic Assignment to Treatment

When estimating causal effects, you want to compare individuals as similar as possible. It is from this need that stems the exchangeability (/ignorability) or conditional exchangeability (/ ...
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Do propensity score matching methods need to factor in the index date in a matched cohort context?

I am working on a comparative effectiveness study where we estimated the propensity of treatment between two groups and are exploring matching on the propensity score. The study period is long, ...
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IV-estimation vs. Heckman's selection model

I am trying to grasp the difference between IV-estimation and Heckman's selection model. I do that by considering the following set-up. My outcome if interest is y ...
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Shortfalls of using Machine Learning algorithms to predict counterfactual outcome of the treated

To see the effect of a treatment we would like to know the difference between a person in a world in which she received the treatment and one in which she does not. Since we never observe the ...
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Difference-in-Differences combining 3 periods prior to, during and after treatment

I have Difference-in-Differences models with 3 periods: pre-treatment, treatment and post-treatment periods. Normally, we could do DID in the following way: run DID between pre-treatment and ...
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Propensity score matching: covariate balance

I have one concern about propensity score matching's assumption. It seems that what propensity score is doing is to say that the choice of treatment depends on pre-treatment covariates. Suppose I am ...
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Model subgroup- and covariate-specific effects for binary outcome over time

I am currently planning an analysis, in which I try to separate the change in the level of a binary outcome into a subgroup- and a covariate-related effect. Let's say there are three kind of ...
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Identifiyng mutual trends between treatments

(WARNING: Not a statistician - do not get mad) We have two different treatments $A,B$, each was tested separately ($A$ treated group vs control, $B$ treated group vs control). In each comparison, the ...
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Variance of ATE (Average Treatment Effect) from log-linked gamma model

I have matched my sample using propensity score matching such that each individual has an estimated propensity score of being assigned to a treatment group. Let $T_i$={0,1} be the actual treatment ...
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Is there a commonly accepted effect size parameter for pairs of Bernoulli processes?

Let $f(x|\rho)$ be the Bernoulli pmf with probability $\rho$ of success. \begin{align} f(x|\rho) = \left\{ \begin{array}{ll} \rho & x = 1 \\ 1-\rho & x=0 \end{array} \right....
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Looking for methological advice (“decomposing” treatment effect)

I'm looking for methodological advice on the undertaking described below. I tried to simplify as much as possible and hope its comprehensible this way - if not, please pardon my ignorance and shoot ...
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Difference-in-differences with unbalanced panel data

I am working on a quasi-experimental study with a large unbalanced panel dataset. There are N=300,000 and T=20, where roughly 50,000 individuals receive treatment since several different periods. I ...
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Diff-in-diff with mactched control group

I want to run a diff-in-diff model. To choose an appropriate control group, I use a nearest-neighbor matching model based on several determinants of the outcome variable that I study. I was ...
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231 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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Average treatment effect using relative risk difference?

So I'm designing a RCT to evaluate the effectiveness of a smoking cessation intervention. For my analysis I've decided to look at three different things. 1) the point prevalence of smoking cessation ...
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Conditional treatment effect and average treatment effect under no unmeasured confounders (ignorability)

The conditional treatment effect (CATE) is defined as: $$ \tau(x) = \mathbb{E} \left[ Y^1- Y^0 \mid X = x \right], $$ the average treatment effect (ATE) is defined as $$ \tau_{ATE} = \mathbb{E}\...
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Diff in diff model with multiple treatments in multiple perdiods?

Can I estimate a diff in diff model to compare the effects of two different treatments that apply in different time periods in different countries? I have 30 countries for an average time span of 34 ...
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1answer
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IPTW ATE Significance Test

Does anyone have any experience using propensity weighting schemes such as IPTW (Inverse Probability of Treatment Weighting) estimation? I have a model that uses IPTW to estimate the Average Treatment ...
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34 views

Experimental Analysis with Several Discrete Treatments

I am analyzing data that are originating from an randomized experiment and I am new to this. There was one control groups and three different treatment groups. The treatment groups are discrete and ...
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What statistical tests can I use? Repeated measures design, two groups, each is control and experimental at different points in time

I need to determine if an intervention had an effect. In the experimental design, measures were taken at three points in time: pre-test, post-test #1 and post-test #2. One group (group A) received the ...
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Marginal independence sufficient for showing that ATE is identified?

I have a basic question on the relation between counterfactual outcomes and treatment. In what follows ATE means average treatment effect. Notation: Let $D$ denote the treatment, taking value in $\{...