Questions tagged [causality]

The relationship between cause and effect.

331 questions with no upvoted or accepted answers
Filter by
Sorted by
Tagged with
0
votes
0answers
43 views

Are feature importances from tree based models directly actionable for business?

If my response variable say is "has_repurchased" [0 or 1] and I have all customer level features. Can I rank the features in order of importance from the random forest model and report them as whats ...
0
votes
0answers
101 views

IPW for the effect of treatment on treated with a continuous treatment

I've been banging my head against the wall trying to figure out how to construct inverse probability of treatment weights (IPTW) for the population average effect of treatment on treated (PATT) with a ...
0
votes
2answers
207 views

Difference-in-difference: common trend

I'm new to this concept, and I'm referring to the book Mastering Metrics: The Path from Cause to Effect by Joshua D. Angrist and Jörn-Steffen Pischke. It states that an important assumption of ...
0
votes
0answers
40 views

Causality logic appears reversed. What's the explanation?

In reading Detecting Causality in Complex Ecosystems I came across the following passage: Our alternative approach [...] tests for causation by measuring the extent to which the historical record ...
0
votes
0answers
104 views

Is this causal effect identifiable? It includes a mixture of observational and interventional data with selection effects

The DAG of the model is below. We wish to estimate P(attitude | do(exposed)). moving up from the bottom of the dag: we ...
0
votes
0answers
81 views

Causal model: Controlling for moderating effect of confounder (rather than the confounder itself)

My linear regression model can be described by the following causal graph: I want to explain the sign of the causal effect of $X$ on $Y$, but unfortunately cannot measure $Z$ directly. Thus, I can ...
0
votes
0answers
38 views

do not need many controls with big data?

I am looking at a paper which uses a large panel data, 1 million observations, a dozen variables. I recall that in a discussion another one has the following comments: In structural models like ...
0
votes
0answers
59 views

Deterministic Assignment to Treatment

When estimating causal effects, you want to compare individuals as similar as possible. It is from this need that stems the exchangeability (/ignorability) or conditional exchangeability (/ ...
0
votes
0answers
63 views

Problem in creating causal model for delay analysis

knock-on" are defined as delays caused by previous late departures or arrivals. I am trying to create a model which can help predict the arrival delay of the next flights. But I don't know where to ...
0
votes
1answer
119 views

Pre.intervention and post.intervention should be contiguous in CausalImpact?

I am running a CausalImpact analysis on a time series and my pre.period goes from 01.01.15 to 30.03.15. I want my post period to be from 15.04.15 to 17.04.15. Is it ok if I create a time series that ...
0
votes
0answers
65 views

Potential bias in a study design

I am trying to design a study regarding Diabetes. I have patients with test results of some indicator about their situation - sugar levels, but not in the classic sense that you may know. Every ...
0
votes
0answers
245 views

In Inverse Propensity Score Weighting, is it possible to find an explicit solution to the estimator by way of Jacobians?

In IPSW, a propensity score model is specified (usually an inverse logit) on a set of covariates, then from that, we use Weighted Least Squares regression to obtain the estimates. However, I am ...
0
votes
0answers
16 views

Matching with partially-observed covariates?

Context I have a randomized controlled trial where units $i \in N$ have one of two possible values (A or B) on variable x such that $x_i \in \{A,B\}$. Assume equal numbers of observations for all ...
0
votes
0answers
74 views

How to sample $N$ Bernoulli random variables given a fixed number of successes ahead of time without collisions?

Suppose that I have $N$ units and that each unit has a probability of being treated, $p_i$ for $i = 1, \ldots, N$. Treatment is indicated as $1$ and non-treatment is $0$. Suppose that $p_i$ turns out ...
0
votes
0answers
48 views

Sharp Regression Discontinuity (RD) for one part of the sample, RCT for another?

I have a study where schools' 4th graders are randomized into treated and controls (at the school level, i.e. there are treatment and control schools). Within each treated school, treatment follows a ...
0
votes
0answers
59 views

How can a valid conclusion be drawn despite the presence of many unknown confounding variables?

Specifically, I am trying to understand the above question in the following context: 'John thought that there was a difference in breathing when lying down compared with when sitting on a chair. He ...
0
votes
0answers
132 views

How to estimate Complier Average Causal Effect?

In an experiment, in addition to the assignment for every experimental unit, you also know the identity of some of the compliers, but not all. How to use this information to estimate the causal ...
0
votes
0answers
276 views

Reverse causality between predictors, interactions and results' interpretation

In my model I have clear reverse causality between two predictors. I am mainly interested in esitmating the interaction between the two predictors mentioned above. I am wondering how this form of ...
0
votes
0answers
190 views

How can I infer causal relationships in this case?

I have a philosophical question about causal relationships inference. Suppose we have UCBAdmission data, where different gender and different department have different admission rates. ...
0
votes
0answers
425 views

Causal Impact and using multiple control series with their regressors

Hi all I am analyzing several DMA's for campaign effectiveness using the CausalImpact package by Kay Brodersen. I have data for participants and non-participants INCLUDING their contemporaneous ...
0
votes
0answers
186 views

Adjusting for confounders when the investigated exposures are gene mutations

I'm delving into causality and directed acyclic graph for choosing the right covariate structure for multivariable regression analysis. Reading Pearl work, I understood that one should adjust only ...
0
votes
0answers
226 views

How to distinguish a causal chain model from a double effect model?

I am used a linear mixed model on two datasets (two different species), with the same explanatory variable (an environmental variable) for fixed effects. I then select the top 0.1% response ...
0
votes
1answer
27 views

normalizing predictor by another predictor

I'm fitting a linear model with outcome $Y$. I have measurements for variables $X_1$ and $X_2$. I hypothesize that $X_1$ and $Y$ are linearly related. I want to know the slope and significance of ...
0
votes
0answers
170 views

Explaining why the slope varies in varying slope model?

When I fit a multilevel varying slope model, it is easy to summarize the variation in slope. However, I have not yet seen any materials that discusses how to explain such variation (i.e. what about ...
0
votes
1answer
60 views

How to find three probabilities with two different values or ratings?

I would like to know how to find three probabilities of two values.... Specifically...I want to know the three soccer venues (HOME DRAW AWAY) proabilities with two ratings... Example: I have two ...
0
votes
0answers
133 views

Is this mediation or a simple path?

This is my model adapted from a study. I want to know whether I can only study it as a path analysis without studying mediation effect (1 $\longrightarrow$ 5 direct effect, as well as indirect effect) ...
0
votes
0answers
25 views

Dropped cases from matched studies

We have cohort data and a rare exposure which we are matching to controls in a large epidemiologic dataset. The matching variable is a deidentified neighborhood indicator (cluster) which guarantees ...
0
votes
0answers
98 views

Google trends data for interest

I was discussing about the popularity of some terms and used google trends to conclude in the decrease of their popularity. Here is an exemple of the queries for some of the biggest french engineering ...
0
votes
1answer
25 views

What are the best methods for analyzing: X, Y, and Z change over time, and I want to see whether X and Y cause changes in Z

I have a data-set, and the details are not crucial, but if it helps: The variables are (A) country, (B) investment, (C) campaign type, (D) external event. Obviously A is a categorical variable, B is ...
0
votes
1answer
25 views

Aggregating observations with missing into group counts to compute treatment effects

I have observations from $n$ groups where half of the groups were assigned to a treatment and the rest to a control condition. As observations within groups are dependent, I aggregate data into ...
-1
votes
1answer
302 views

Generalizing “Causal Impact” synthetic controls, to multiple outcomes

Does anybody know a way to generalize the use of the Causal Impact google R package to multiple outcome time series? Say I ran a time series experiment and was able to set up multiple test outcome ...

1
3 4 5 6
7