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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Methods to deal with latent variables

I had a general question about methods to adjust for the effect of latent variables (specially variables that are suspected to be confounder) in observational studies. In particular, I'm working on a ...
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53 views

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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62 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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In two places at once: treatment and control groups

When performing a treatment study (e.g. a difference-in-differences design) in multi-dimensional panel data (e.g., firm-individual-time, bank-firm-time, etc.) is it ok if the "smaller" cross-sectional ...
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Isolating distinct components of a treatment effect

The effect of a drug on blood analytes is to be studied. Blood analytes are measured before and after administration of the drug, which shows that several of them have decreased after treatment. A ...
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25 views

Large standard errors in IV regression [duplicate]

I am encountering very large standard errors of the endogenous regressor (bigger than the size of the coefficient) in the second step of my treatment-effects model (...
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25 views

Multiple interactions are hard… Difficult difference-in-difference design UPDATE

I am trying to estimate a difference-in-differences model with some complicated interactions. I have panel data on the supply of some production input to firms from two groups. The supply of this ...
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30 views

propensity score matching and difference in difference

I am trying to analyse the impact of a cash stipend program, onto child learning outcomes. I have first modeled the conditional probability of each student receiving this program. So basically I have ...
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1answer
22 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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21 views

Regression analysis for a clinical trial with repeated measures

I am currently working with a dataset that was collected from a depression study at baseline and 6 months for a group of 60 participants. Also these participants are divided into 4 groups based on ...
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37 views

Exploring effect of treatment on count data

I've collected data on animal visitation at four different points in time. The four time points represent the total animal visitations over a three day period, i.e. 3 days of monitoring at four ...
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2 views

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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19 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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18 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
51 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
74 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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51 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
72 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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40 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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16 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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65 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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104 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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45 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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48 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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12 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
159 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
21 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
298 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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24 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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124 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
190 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
58 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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34 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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2answers
251 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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134 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
57 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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244 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
68 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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1answer
106 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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406 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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326 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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36 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
170 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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92 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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136 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
124 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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125 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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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 ...