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.

109 questions with no upvoted or accepted answers
Filter by
Sorted by
Tagged with
7
votes
1answer
3k views

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 ...
6
votes
0answers
374 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 ...
4
votes
0answers
44 views

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, ...
4
votes
0answers
366 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 ...
3
votes
1answer
355 views

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[\...
3
votes
0answers
431 views

Panel data regression on the effect of a treatment without control group

I have a panel data set. The dependent variable is a certain numerical score for each individual and time period. I have a number of independent variables that vary by individual, by time, or by both. ...
3
votes
0answers
69 views

How to deal with treatment effects that occurs multiple times at different time for each individual ID

I've been searching for a long time for this issue and couldn't find the proper answer so I post a question here. Here I put the data set example first. ...
3
votes
0answers
97 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 ...
3
votes
0answers
356 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
votes
0answers
12 views

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 ...
2
votes
1answer
46 views

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 ...
2
votes
0answers
627 views

Parallel trend assumption in difference-in-differences

I want to run a difference in difference model to evaluate the impact of a policy change using panel data with 30 individuals in the control group and 35 individuals in the treatment group. When ...
2
votes
1answer
497 views

Computing and interpreting treatment effects for binary outcome using multiply imputed and matched data

I am using genetic matching, implemented through the MatchIt package (dependent on Matching and ...
2
votes
0answers
330 views

Before and after effect with logistic regression, what method to use?

So I have a test subject A which consist of a binary variable 0 and 1. I want to see if this binary variable is decided by some independent variables (plus interactions) which are continuous, which in ...
2
votes
1answer
60 views

Estimating Equations for Treatment Model in Treatment Effects Estimation — How is this Equation Derived?

While reading the STATA 14 Treatment Effects Reference Manual (http://www.stata.com/manuals14/te.pdf), I'm having difficulty understanding how they arrive at the equation for the treatment model, that ...
2
votes
0answers
585 views

Which is the best approach? Difference in Difference with Heterogeneous Effects

I am interested in the performance of two competing approaches to estimate a treatment effect, for which one would expect heterogeneous effects. The point of origin is a treatment conducted from ...
2
votes
0answers
188 views

How to set sum contrasts for unbalanced factors

Let's say that I have a model where the response time depends on accuracy (0/1, coded either as categorical or numerical) and another categorical variable (pres: idem/diff), both interacting with the ...
2
votes
0answers
68 views

Repeated measures binomial effect confidence intervals

I have a repeated measures study design with two separate conditions in a memory task where one must recognize previously seen items in a list. The conditions are concrete vs. abstract. I'd like to ...
2
votes
1answer
111 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 ...
2
votes
0answers
300 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 + \beta_{01}*{x_1}...
2
votes
0answers
295 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 ...
2
votes
0answers
161 views

Testing endogeneity against decision probability

I am working with a model where the literature suggests there is potential endogeneity between the dependent variable and the primary independent variable of interest (a binary treatment). However, ...
2
votes
1answer
176 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 ...
1
vote
0answers
25 views

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 ...
1
vote
1answer
21 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 ...
1
vote
0answers
21 views

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)....
1
vote
0answers
54 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)...
1
vote
0answers
29 views

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 ...
1
vote
1answer
12 views

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 ...
1
vote
0answers
77 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=...
1
vote
0answers
45 views

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 ...
1
vote
1answer
62 views

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 ...
1
vote
0answers
13 views

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). ...
1
vote
0answers
32 views

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 ...
1
vote
1answer
42 views

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, ...
1
vote
0answers
209 views

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 ...
1
vote
0answers
20 views

Randomized Treatment within treated group

I don't know if this situation has a particular name. I'll just give the example and my question. Suppose we have two naturally concurring groups, $A$ and $B$. By that, I mean there is a naturalistic ...
1
vote
0answers
65 views

Post dummy in multiple groups and time periods DiD estimation

I have a question regarding an answer of another question posted here. My dataset seems comparable and has different policy treatment timings for different firms. The answer outlines how to construct ...
1
vote
0answers
59 views

Performing a two-way ANOVA, I get a non significant Levene's and a significant interaction effect. What it the next step?

In the case described above, our Professor instructs as to interpret the simple effects by using MSwithin of the two-way ANOVA. In case the Levene's test is significant though, he instructs us to ...
1
vote
1answer
39 views

Is augmentation of treatment effect caused significantly by mediator?

I want to find out if the influence of potential mediator P on treatment effect D is significant. In the two models below $\beta_1$ and $\lambda_1$ are different and I don't know how to test if the ...
1
vote
0answers
316 views

What distinct matching routines do exist?

In a seminar paper I'm discussing all possible matching routines. It turned out that there are quite many of them. Now I am looking for several answers: First, I discovered that some routines happen ...
1
vote
0answers
1k views

How to assess for balance of propensity score matching covariates in Stata?

I am comparing outcomes of a treated cohort (n=127) to a control cohort (n=732) using teffects propensity score matching in Stata. I did initial comparisons of baseline characteristics between the two ...
1
vote
0answers
496 views

Difference in difference model with multiple time periods and treatment/control pairs

I am trying to estimate a difference in difference model with 10 time periods (t=10) and many different plots of land, which are the unit of observation. Each plot of land which becomes treated at ...
1
vote
0answers
147 views

Interpreting DD estimates in terms of their economic magnitude

I'm currently doing the statistical part of my final thesis and I am having troubles with correctly interpreting my regressions results. The models I am using (with the plm package in R) are pretty ...
1
vote
0answers
35 views

Combing panel data with cross -section counter-factual?

I have a panel dataset of a treatment group with no control group panel. It has been proposed to me that I use cross-section from a a national survey, taken at baseline and same time as post-...
1
vote
0answers
288 views

Calculating the CACE using instrumental variables

In randomized trials with non-compliance among the treatment group, a common estimator is the Complier Average Causal Effect (also called the Local Average Treatment Effect), which (conditional on a ...
1
vote
0answers
20 views

Matching / imputing between experimental and control group on a specific (i.e. latent) variable

I am currently researching the impact of survey participation on subsequent behavior, i.e., does merely participating in an intention survey about fitness products influence post survey spending. As ...
1
vote
0answers
244 views

Longitudinal measures mixed model in lmer in R

I would like to build a mixed model using the lme4 package in R. The study design is like this: We have measured the change in a variable over time in mice under different Diets. The mice under ...
1
vote
1answer
270 views

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 ...
1
vote
1answer
43 views

What is the optimal small-sample experimental design for multiple treatments and costly trials?

I have an experimental outcome in three outcome variables, y1, y2, y3. My objective function is: a * ln(y1 - y1*) + b * ln(y2 - y2*) + ln(y3 - y3*) for a, b, c, y1, y2, y3 >0. The starred ...