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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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Test if treatment effect is different between samples

I want to determine if there is significant variation in the effect of a treatment amongst my replicates. The treatment effect is measured as a proportion. Let me describe: I study heart defects (in ...
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Before/After unpaired study with control villages analysed in R

For the implementation of a project, we have been following household access to services in two groups of villages, one an intervention group (I) and one a control group (C). Access as a Yes/No ...
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Treatment effect on the non treated if there are no never-takers and no defiers

$Y$ is my outcome variable, $D$ is the treatment, $Z$ is the instrument, $Y_i$ is the outcome when $D=i$, $D_i$ is the treatment when $Z=i$ I don't understand the following result : when ...
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Regressing the “fixed effect” on time invariant characteristics. Is it possible? [duplicate]

I would like to use estimations of "fixed effect" from my panel data model as a dependent variable and study whether this depends on time invariant characteristics. I've not been able to find an ...
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Testing socio-economic differences in an experiment

I am just a beginner in statistics and currently i am doing a research. I have conducted an experiment with a control group and a treatment group. Although the difference overall is not significant I ...
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Propensity score: which treatment effect is easier to infer?

I'm currently working on a study where the goal is to estimate the treatment effect of a binary exposure. I want to calculate the Average Treatment Effect (ATE), Average Treatment Effect in the ...
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How exactly to evaluate Treatment effect after Matching?

In Elizabeth's Stuart's 2010 paper "Matching methods for causal inference: A review and a look forward", she states the following: "Section 5: Analysis of the Outcome: ... After the matching has ...
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Best method to investigate treatment effect after creating a Matched control group using Gentic Matching (with replacement)?

Project background: I have data on patients who received varying amounts of therapy dose during treatment of stroke-induced paralysis. I wish to investigate if there are differences in motor-function ...
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Comparison of 2 treatment groups using proportions

I have two treatment groups (lets say A and B) with pre/post data for two diffirent populations and there are statistically significant differences (p<0.05) between before and after treatments, ...
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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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In causal inference, why is the uncounfoundedness assumption interpreted as the treatment assignment being conditionally independent of the outcomes?

In causal inference, the unconfoundedness assumption is usually stated as: $$ Y(1), Y(0) \perp Z \mid X $$ or $$ P(Z \mid Y(1), Y(0), X) = P(Z \mid X) $$ where $Z$ is the treatment assignment, $(Y(1)...
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Two group clustering in residuals - not sure how to fix

My only really significant finding in this study has strange residuals - two clusters. It's a study of the treatment effect of education on psychological capital pre vs. post-test, so I'm assuming the ...
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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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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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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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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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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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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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Proving equation 3.3.12 in Angrist Pischke Mostly Harmless Econometrics (inverse probability weighting formula for ATT effect)

On page 82 in Mostly Harmless Econometrics, there is a formula for the average treatment effect on the treatment, using propensity score, that is $$\tag{1} E(Y_{1i} - Y_{0i}\vert D_i =1) = E\bigg[\...
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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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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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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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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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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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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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Specification of longitudinal mixed-effects model with varying treatment times, varying observation times in lme4

I am familiar with fixed-effects linear regression models, and have done reading on mixed-effects models. I am attempting to fit a model based on observational data, where treatments come at varying ...
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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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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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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 calculate ATT using Propensity Score Matching method

I am working on thesis work for Mphil. I am interested to estimate the average treatment on treated effect (ATT) by using propensity score matcing method. The primary data on 320 respondents, out of ...
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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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Using the ED function in R for 4 parameter log logistic functions to give 'absolute' values

This problem has been stalling me for months now, and I can't seem to get to the bottom of it. I'm able to fit a 4-parameter log logistic model to my data of (increasing dose ~ decreasing response) ...
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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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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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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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1answer
110 views

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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1answer
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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 ...