All Questions
32
questions
2
votes
1
answer
79
views
Granular difference-in-differences with non-repeating unit of observation
I want to analyze changes in characteristics of job postings around an (exogenous) event. However, rather than conducting the analysis at the job poster level (e.g., a company or geographic area), my ...
- 77
0
votes
1
answer
32
views
conditional-on-positives bias
I am reading the Bad COP section on https://matheusfacure.github.io/python-causality-handbook/07-Beyond-Confounders.html#bad-cop. I am confused if
$$
E[Y|T = 1] - E[Y|T = 0] = \\
E[Y|Y > 0, T = 1]...
- 113
1
vote
0
answers
46
views
Regression Discontinuity Design, staggered treatment allocation
I'm unsure if this complex allocation rule is appropriate for RDD. I will have data for a staggered rollout treatment where there will be about 10 rounds of selection over two years for services (...
- 362
4
votes
2
answers
217
views
Variable selection with a theoretical DAG vs algorithmically discovered DAG
I'm analysing data from an electronic health record and determining what variables to include in a model to close back doors and omit bias.
I've read that it is important to have a subject specific ...
- 741
2
votes
0
answers
60
views
Bias and Variance of a Honest Random Forest
I am trying to read the paper Estimation and Inference of Heterogeneous Treatment
Effects using Random Forests. In the section 3.1(Theoretical Background), page 13 paragraph 2, The authors have ...
- 137
1
vote
1
answer
43
views
Are missing variables an important factor when considering instrumental variable analysis?
I'm currently reading some papers that deal with the effects of education on health (smoking and obesity). Mostly they use an IV approach (college availability).
However in several analysis, only a ...
- 87
1
vote
0
answers
38
views
Conditioning group effect on values post-treatment variable
I'm relatively new to causal inference, so please be gentle.
I have the above DAG, which represents the following variables:
G: exposure variable, two factors (control and treatment)
S: Pre-...
- 31
5
votes
1
answer
103
views
VanderWeele bias calculation
In his book "Explanation in Causal Inference Methods for Mediation and Interaction", Tyler VanderWeele gives the following formula for bias (also Cinelli & Hazlet).
Let $\beta'$ be the ...
- 911
2
votes
1
answer
177
views
Does an endogenous variable bias the coefficient of the exogenous one?
We have the following model:
$$ y = \beta_0 + \beta_1 x_1 + \beta_2 x_2 + \epsilon. $$
We know that:
\begin{align*}
\operatorname{Cov}(x_1, \epsilon) &\neq 0 \\
\operatorname{Cov}(x_2, \epsilon) &...
- 2,301
2
votes
0
answers
92
views
Expectation of Difference in Means estimator
Given i.i.d. observations $(Y_i, X_i)$ where $Y_i$ is the response and $X_i$ is binary valued, the difference in means estimator is
$$
\hat{\theta} = \frac{1}{n_0} \sum_{i=1, X_i=0} Y_i - \frac{1}{n_1}...
- 1,501
1
vote
0
answers
54
views
How can I understand ATT estimator for matching discrepancies in Causal Inference Mixtape?
While studying 'Causal Inference: Mixtape' by myself, something I didn't know happened.
link: https://mixtape.scunning.com/matching-and-subclassification.html#bias-correction
$\begin{align} \...
- 73
1
vote
1
answer
603
views
OLS Estimation, Bias and Causality
I wish to ask about the bias of an OLS estimator. In what follows I assume that the regression that we are dealing with is an approximation to a linear conditional expectations function. That is we ...
- 303
3
votes
0
answers
88
views
All-subsets regression and parameter shift to estimate or identify omitted variable biases?
I have multiple ($12$) predictors ($X$) for an outcome (spending) where it's likely/possible that:
Some predictors are correlated
Some predictors could (partially) mediate the effect of others
There ...
- 435
4
votes
1
answer
2k
views
Addressing the Ashenfelter’s dip
I am running a difference in difference (DiD) model on the effects of job-training on earnings. My data consists of a staggered adoption design whereby units receive treatment at different times, but ...
- 141
4
votes
1
answer
157
views
Modeling and counteracting exposure bias in recommender systems
I am looking for best strategies to train a new recommendation model from the biased data (due to modeling bias from the previous model).
For e.g. Lets assume I have an e-commerce site and initially I ...
- 221