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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Comparing change in lateral root densities between treatments for different genotypes

I have been growing 4 genotypes of the same plant and been recording their lateral root density under both control conditions and a salt treatment. I have calculated the decrease in lateral root ...
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11 views

Weighting supercedes fixed effects?

I came across a surprising "result" when analyzing some data and I'm wondering if it is actually a known result, and why it works. I have a dataset that has been partitioned into ...
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12 views

For which data can propensity score matching be applied?

I wondered if besides controlled experiments (random distribution of treatments) and observational studies (treatment for homogeneous individuals), other settings apply for propensity score matching. ...
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1answer
41 views

Check if density plots are significantly different (with R) [closed]

I have daily data on cars per minute passing certain points. The data covers weekdays of 4 months, July and August, for 2013 and 2014. In August 2014 a toll (treatment) was introduced. I would like to ...
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2answers
65 views

Model for exponential decay with lots of zeros

I am trying to test for the effect of a treatment on a response variable. The response variable decays over time in what I believe is an exponential way. The measurement doesn't go below zero, so ...
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38 views

Subject-specific graphics for repeated-measure design

I am doing linear mixed effect modelling testing the effect of treatment on pitch, with ...
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1answer
58 views

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 ...
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3answers
36 views

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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12 views

Recommendation for type of analysis to measure whether intervention is effective

I have a dataset of about 90,000 cases. In something like 10% of these cases, an intervention was applied to hopefully bring about a specific outcome. The intervention was not equally applied across ...
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44 views

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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1answer
94 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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30 views

Mixing ITT and TOT/LATE Effect Sizes in Meta-Analysis

I have a question concerning the coding of Effect Sizes for a large (educational) Meta Analysis with mostly latent outcome variables. Some studies provide "Intent to Treat" Data from which I ...
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39 views

Creating a treatment group to measure uplift in sales for an advertising campaign

I have sales by state and week. Alabama|Alaska|Arizona|... 231|139|277|... 256|154|307|... 267|160|320|... 256|154|307|... 267|160|320|... I need to create a treatment group that bunches up the ...
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11 views

test to be applied

I have applied 3 treatments at 10 different concentrations of each on a bacteria to see if they affect its existence. my response variable is binary i.e. 1 for effective and 0 for ineffective. basic ...
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1answer
117 views

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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2answers
19 views

Multiple drug treatment effects

Suppose I have five vitamins VA VB VC VD VE, and wish to study the effects of each drug on the weight of patients with data measured at daily frequency. The typical data look like this Patient 1 take ...
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1answer
195 views

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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22 views

Two repeated measures treatment analysis. Regression of the delta or mixed effect model?

We want to study the effect of a certain treatment on performance on a test and I would like to have some suggestion from you. We want to use a regression model in order to control for confounders. ...
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95 views

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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1answer
120 views

Difference in difference model with 2 treatment groups

I have an experiment which has 2 treatment groups(effects) and a control group. Up until this point in my analysis, I've been carrying out a DID using a regression equation of the form: Y= γD_t + ...
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1answer
53 views

Is there such thing as correlation trees? Clustering rows of X based on correlation between A and B

I have been searching for several days for a method that fits this description, though cannot find one. I'm pretty sure it must exist. The problem (short version): I'd like to run something like a ...
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32 views

Constructing Counterfactuals and Estimating Prevalence

I'm a social scientist working on a research project where I try to estimate the prevalence of lying in responding to a certain sensitive question. The way I estimate it is to rely on a ...
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1answer
191 views

Confused about the basic maths in Incremental/Uplift modelling

I have recently gotten to study Incremental modelling, which is used in Marketing to study the incremental impact of a certain action on a treatment group against a control group. However, I am very ...
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123 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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1answer
50 views

Pre-post treatment design: accounting for reduced effect of treatment in baseline high scorers

I'm planning a study in which I want to test the effect of a treatment on a dependent psychometric variable. I expect subjects who score lower at baseline to benefit more from the treatment (larger ...
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210 views

Modeling Difference-in-Difference with Multiple Treatments

I ran a field experiment across 100 cities. The cities belong to two types: Type_A(50 cities) and Type_B(the other 50 cities). From January 1 to February 30(The Pre-Treatment Period), I only collected ...
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1answer
60 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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18 views

Two Step estimation of treatment effects

I want to estimate the treatment effect of a selection Model without a preimplemented package in R. I allready have the probit estimates for the inverse mills ratio. How can I estimate the switching ...
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1answer
94 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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1answer
354 views

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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22 views

Measuring treatment effect on top-ranked subjects selected at point in time from longitudinal data

I am trying to measure the effect of treatment after some time on a group of subjects who were selected for treatment because they were the highest (top 1200) ranked subjects during a single period ...
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2answers
294 views

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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15 views

Inferring treatment start date for comparison group

I'm trying to work out the effect of treatment on a group using a counterfactual approach. However, I don't know how I can infer the treatment start date for the comparison group. For both groups I ...
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0answers
34 views

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
153 views

Endogenous treatment effects: exogenous covariates

I am interested in estimating an endogenous treatment effects model of the following form: \begin{eqnarray} Y_i = \alpha + \beta_x X_i + \beta_{z1} Z_{1i} + e_i \\ X_i = a + \beta_{z2} Z_{2i} + v_i ...
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86 views

Simulation setting for the average treatment effect on the treated (ATT)

I have a question about a simulation set up. Assume there are two groups (Z = 0 and Z = 1). The outcome for Z = 0 and Z = 1 are generated by the following equations: $Y_0 = \alpha_0 + ...
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0answers
131 views

Constructing the OLS standard error by hand to avoid regression

I am having trouble deriving the standard error of a simple regression estimator by hand. Stata code and output for a toy example using the cars dataset is below. The basic idea is that I have a ...
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1answer
111 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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122 views

What to input into Wilcoxon rank sum test when three pre and three post measurements are compared?

I have measured 23 patients three times pre and three times post treatment. Now I would like to see if the treatment had a significant effect. I thought about using a Wilcoxon rank sum test for this ...
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44 views

Weighting FE regression with full matching

I have a dataset that has been partitioned into propensity-score-based matching groups using the optmatch package in R. We used full matching, so this allows any number of treatment observations to be ...
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1answer
97 views

Controlled before-and-after

I've got a study, a before-and-after controlled design. I have pre-intervention data and post-intervention data, the intervention is an educational intervention, given to general practitioners and ...
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2answers
553 views

R Package for Treatment Effect Analysis?

I could not find a package in R about Treatment Effect Analysis. So is there a R package about Treatment Effect Analysis? This means, estimating the average treatment effect, average treatment ...
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1answer
113 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} ...
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2answers
740 views

Plot normal probability for effect estimates in factorial design in R

I have 2 level Design (DOE) with 4 factors (A,B,C,D). I've already calculated the estimates for each main effect and all the interaction effects. How can I construct the normal probability plot to ...
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1answer
166 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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1answer
476 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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0answers
85 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 ...
2
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1answer
113 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
1k views

Deriving effect sizes form pre-post treatment design in R?

This question is related to my previous post. In case of a meta-analysis of a pre-post treatment design I have data given from 5 studies that tested subjects pre- and post-treatment on a continuous ...
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2answers
102 views

What would be the most appropriate significance test for my scenario?

I have three groups of users $-$ $G1$, $G2$ and $Control$. The users in each of these three groups are different but are carefully selected and have similar properties. I treat each group with a ...