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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Significance of treatment effect when interactions are present

I am conducting an experiment in which I am testing the effect of some treatment, $X$, on some result $Y$. Every subject in both the treatment and control group is being measured multiple times (at ...
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Identifying treatments with non-zero effects

I have a complete block design experiment with a large number of treatments were I am trying to identify treatments with significant effects (positive or negative). I know the Friedman/Durbin tests ...
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Treatment variable not in control data set-how to make a dataframe suitable for regression?

I would appreciate some feedback on this particular problem I'm stuck at. Experiment: Between Subjects; Treatment Vs Control. 10 subjects per condition. The subjects are measured over 10 trails. (so ...
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27 views

How to incorporate the customers leaving (addition of new ones) in the measurement of treatment effectiveness?

Consider I have taken a random sample for forming control group in month of January with sample size 5k and treatment group size being 95k. I am Sending offers to treatment group which are intend to ...
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Regression: Potential Ouctomes Frameworkw with Heterogeneous Treatment Effect

This question came up as part of the practice problems in the Econometrics course I am taking. Its is the following. In the potential outcomes framework with heterogeneous (non-constant) treatment ...
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32 views

Not including main effect term in subgroup analysis?

I know there are plenty of previous Cross Validated posts regarding if one must include the main effect term if the interaction term is included. The general consensus is: no if you have a very good ...
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Mixed models in repeated measurement with one treatment

I have an experiment that includes 8 subjects during one treatment, measuring response variable. The hypothesis is that there is some correlation between AV and lactate during the treatment. Some ...
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Treatment effect in a balanced randomized experiment

In an ideal balanced randomized experiment where every profile's propensity score is 0.5 (under binary treatment), regardless of the value of the profile, the best we can know of the treatment effect(...
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Checking if treatment is effective without control group

I am experimenting with few treatments to see which one is effective. I do not have luxury of control group to compare against. In such scenario, is there any method to see if the treatment has been ...
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Predicted individual treatment effect with continous treatments

I'm trying to apply Rubin's counterfactual model in an observational setting using machine learning predictions to simulate the unseen treatment-outcome pairs, according to https://www.ncbi.nlm.nih....
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Path Model with (endogenous) Treatment - which model?

I have collected data on the intention to create a new business of my students. I measured it before the course (t1) and after it (t2). I have data on their absenteeism in class and the time they ...
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How are the Average treatment effects using Causal Trees (CT) and Causal Forest (CF) decision-trees estimated?

I have read the following paper: https://iopscience.iop.org/article/10.1088/1748-9326/aafa8f/pdf . The paper seem to be understandable, however, several questions I have got about causal trees. As I ...
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Is this a well-known source of small-sample bias?

Suppose we have an outcome $Y$ which is caused by a binary treatment $T$ and some continuous covariate $X$, such that: $$E[Y\mid X,T=1] = E[Y^1\mid X] = \beta_0 + \delta + \beta_X X$$ $$E[Y\mid X,T=...
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Formula for E(MSE) from Recursive Partitioning for Heterogeneous Causal Effects (Athey and Imben 2015)

I'm reading Recursive Partitioning for Heterogeneous Causal Effects (Athey and Imben 2015) and I'm confused about the formula for $\hat E[\mu(x;\Pi)]$ on page 8. The formula offered in the paper is ...
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How to handle studies that don’t provide an estimate of effect size in a meta-analysis?

Say we want to survey the literature to find out the effect of Treatment A on Value B. Some studies provide an effect size estimate with confidence intervals and t-test results (e.g., “Treatment A ...
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Bias in average treatment effect with least-squares when continous interaction terms

I hope someone can clarify this for me: When I am estimating treatment effects with a regression model, I can use interactions between the treatment indicator $W_i$ and covariates $X_i$ to model ...
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Difference-in-difference to estimate gradual (i.e. slow) policy effect

I want to evaluate the impact of a policy on a variable $Y$. In the figure, I plot the mean of $Y$ over time in both the control and treatment groups (the vertical line represents the reform). The ...
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Powering versus statistical significance in clinical trial design

I think I have a simple question that I have not seen directly answered elsewhere, and as a stats beginner, I'm wary to translate answers that are not directly answering this question - apologies if ...
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Expectation of potential outcomes formula

In Mostly Harmless Econometrics, the author uses the following identity to derive an estimator for the causal effect: $$E \left[ \frac{Y_i D_i} {p(X_i)} \right] = E \left[Y_{1i} \right]$$ where: $...
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Multiple Imputation with categorical variable for treatment: Do I have to impute stratified by treatment?

I want to impute data for a clinical trial with four treatments and analyze the data to determine if there is a treatment effect. Normally I would perform the imputation stratified by treatment so ...
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Assess temporary effect of treatment

Imagine that I have a treatment that reduces the likelihood of response to a stimulus. This could be anything you like, but the simplest example is of a treatment (e.g., hand washing, mask wearing, ...
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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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17 views

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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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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How do I apply weights to a Cox Regression Model in R? [closed]

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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117 views

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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1answer
92 views

Propensity Scores: What is this estimator?

I'm reading The Central Role of the Propensity Score in Observational Studies for Causal Effects in order to understand why Propensity Scores work. I'm kind of new to this and I'm not understanding an ...
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27 views

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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28 views

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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72 views

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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70 views

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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1answer
34 views

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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102 views

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 ...