Questions tagged [causalimpact]

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Causal Inference where the treatment assignment is randomized [closed]

I have mostly worked with Observational data where the treatment assignment was not randomized. In the past, I have used PSM, IPTW to balance and then calculate ATE. My problem is: Now I am working on ...
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21 views

Is it possible to use roc auc metric in uplift modeling (class transformatio approach)

I do not understand why in uplift modeling (Class Transformation approach) not used ROC AUC score for changed target Z. I have a problem with a task where I tried to use this approach, but ROC AUC ...
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17 views

Identify causal feature in a classification model

Assume I have a model $f(x;b_1,b_2,b_3,b_4)$ which maps a 4-dimensional vector into a binary classifier e.g logistic regression with 4 parameters to create churn-classifier. Say, for instance, that $...
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1answer
65 views

Google's Bayesian Structural Time-Series

I am attempting to get my head around Google's Causal Impact paper, which isn't completely clear to me. In the methodology part of the paper, the authors say: "The framework of our model allows ...
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17 views

Quantifying treatment effect in Interrupted Time Series

I have a multivariate time series dataset, from which I am building an ITS (Interrupted Time Series) model by using facebook's Prophet to construct the counterfactual. Let's say I have a y variable ...
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0answers
25 views

Cross correlation

I am trying to find a good algo (low latency) that is able to take two time series and determine which one is leading on the other one if any. The time series do not necessarily have the same ...
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14 views

Where is publically available time-series RCT data?

Our team is writing a paper about uplift modeling considering time heterogeneity using Machine Learning model and Causal Inference theory; the example would be like, in marketing, a model maximizing ...
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1answer
37 views

What is the difference between causal discovery and inverse modeling?

I do not see these words used interchangeably, but they seem to be similar. In inverse modeling we are trying to find causal factors given an effect. In causal discovery, we are also looking for ...
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43 views

How far or close would feature importance information from an ML model is from causal diagrams?

The title pretty much covers my question, but to elaborate it: given data (let's assume, for simplicity, it is good enough representation of the underlying distribution) for a binary classification ...
1
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1answer
59 views

Treatment and Control selection in A/B Testing

I'm hoping to get a better understanding of A/B Testing design. In particular, I'm interested in understanding how treatment and control units are selected. I read that these 2 groups are selected ...
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31 views

Exploratory statistics, how to idenify and remove driver (bias)

I am looking at customer data, and created frequency tables (+histograms) for customers with different professional statuses and what the best time is to reach them. Status ranges here from employed, ...
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1answer
255 views

difference between feature interactions and confounding variables

Let me define the problem space. I am working a binary classification problem. I am trying to build a causal model as well as predictive model. My aim is to find list of significant features (based ...
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174 views

Which are valid covariates in CausalImpact?

I am working lately with CausalImpact developed by Google. The paper described it is this one Inferring Causal Impact Using Bayesian Structural Time-Series Models In short, what you can do with ...