Questions tagged [causalimpact]

CausalImpact R package for estimating the effect of an intervention on a time series.

Filter by
Sorted by
Tagged with
1 vote
0 answers
25 views

Causal impact: noisy controls lead to strange results

I am using R causal impact to measure the effect of a campaign intervention. Doing some tests, I found some consistent but very strange results. What I did is to generate a time series with weekly ...
user avatar
0 votes
0 answers
16 views

Causal Impact: How can I cross-validate the Causal Impact model?

I have been able to implement Causal Impact in R. But I want to cross validate the model to see the reliability of the model. I want to calculate how well the covariate align with the test data. Is ...
user avatar
1 vote
0 answers
33 views

Methods for evaluating a geo-experimental research design (DiD, CausalImpact or a third option?)

I'm doing my undergraduate thesis on an experimental design of the incrementality of clicks using Google Ads vs not using Google Ads. I've created a geo-experimental design, where I've made a split of ...
user avatar
0 votes
0 answers
17 views

Causal Impact plot: why if control serie has no data in the test period I see predicted serie droppping down?

I was playing a little with causal impact and just tried to have 0 data in the control serie in the test period, assuming that during test period causal impact is predicting and plotting the estimated ...
user avatar
  • 1
0 votes
0 answers
27 views

What is the right econometric model to use

I want to evaluate how the cultivation of a particular crop has impacted several socioeconomic variables at the municipality level. I have a map that identifies the municipalities where this crop can ...
user avatar
  • 1
0 votes
1 answer
37 views

Causal impact: how can i determine the incremental impact of campaign 1 when campaign 2 was so live in same markets and dates?

0 I have a theoretical / stats related question. I've run the package in R and it's easy. Question: How can I know the incremental impact of Campaign #1 during a period when Campaign #2 was also ...
user avatar
  • 113
0 votes
0 answers
15 views

What metric can be considered to find if causal impact has determined the best combination of synthetic controls

I'm new to Causal impact. I read the paper and video by Kay which has a detailed description of the package. Can someone suggest any metric which can describe the accuracy of the synthetic control ...
user avatar
0 votes
0 answers
65 views

How are Judea Pearl's Bayesian Nets different from Google's Causal Impact?

At a high level, how are these two approaches, similar and different? I understand that both use Bayes rule, however, I'm unclear on how they differ. Causal Impact uses structural time series to ...
user avatar
  • 1,650
3 votes
1 answer
148 views

Can we talk about statistical significance using Bayesian Inference?

In short: can we use the words statistical significance when interpreting the hypothesis testing results in the bayesian inference field ? Or is it only correct to use it in the frequentist approach ? ...
user avatar
  • 31
0 votes
1 answer
70 views

Causal Inference where the treatment assignment is randomized

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 ...
user avatar
3 votes
1 answer
139 views

Custom model using BSTS does not match with CausalImpact in R (please help!)

I am trying to match the results from using CausalImpact with those from using BSTS for a custom model. I followed exactly what the package instruction says but the results completely do not match. ...
user avatar
1 vote
0 answers
66 views

CausalImpact package - results summary inconsistent with the result plots

I'm trying to get some experience with the `CausalImpact` [package][1] in python. I'm using this seemingly simple example: ...
user avatar
  • 163
0 votes
0 answers
34 views

How can I test for what drives changes in time series data?

I am using the CausalImpact package in R to look at how a documentary affected visits to Wikipedia pages of different species. The website visits are time series data based on page views and the ...
user avatar
  • 53
0 votes
0 answers
81 views

Causal Impact confidence interval and statistical significance

I am analyzing effect of a regional marketing campaign using the causal impact R package. I am getting posterior tail-area probability p: 0.02951, which I understand should be a significant result. ...
user avatar
  • 1
1 vote
0 answers
53 views

Evaluating causal impact of a treatment at various time units

I am trying to understand the causal impact of a treatment (T) that can be offered to people at different (and multiple) days until a desired outcome is reached. (for ex: a customer may be offered a ...
user avatar
  • 81
0 votes
1 answer
89 views

CausalImpact for a single individual time series of physiological data

I am using CausalImpact for the first time and I am not completely sure whether it would be statistically correct for my case. We wanted to test if the change of enclosure did significantly impact the ...
user avatar
  • 1
0 votes
0 answers
60 views

Picking a suitable performance metric when comparing the same model but using different sets of training data (Causal inference model)

I am comparing the same models prediction accuracy (Causal Impact) using different control variables as predictors and looking for a metric to decide which set of controls to use. Reading into AIC and ...
user avatar
0 votes
1 answer
487 views

Generalized difference-in-differences where all units are treated, but at a different intensity

Is it possible to run a generalized difference-in-differences analysis where all units are treated, but at a different intensity? In my situation, a policy was introduced in 5 countries, designed to ...
user avatar
  • 1
2 votes
1 answer
321 views

Inferring causal effects on a time series from a forecast

Part of my job is measuring the effect of marketing interventions using experiments when possible, or estimating their effect when it's not possible to experiment. I know relatively little about ...
user avatar
  • 23
1 vote
1 answer
688 views

difference-in-difference: Dynamic treatment group/timing

I want to use difference-in-difference (DiD) to estimate a treatment effect. However, my problem is a little different from the standard DiD application in that: The items in the treatment group may ...
user avatar
  • 191
2 votes
0 answers
88 views

how to measure the causal impact of interventions which happen at different times on different time series?

My data consists of a bunch of time series of daily clicks on some merchandises on a website, a portion of which have an intervention (only 1 intervention per time series), others don't. The ...
user avatar
2 votes
0 answers
47 views

how to get the confidence interval of accumulative effect when using Difference-In-Difference

say i have a dataframe like below: ...
user avatar
  • 191
1 vote
1 answer
100 views

Causal Inference on test scores

I administered a test and wanted to know if the exam scores were influenced by watching videos. The participants were randomly entered into 2 arms. I have one control arm that did not watch videos, ...
user avatar
2 votes
1 answer
131 views

Difference in difference with similar units over 2 periods of time

I have ESG (Environmental, Social & Governance) scores for 20 companies over a period of 10 years. In the fifth year a policy was introduced and I want to estimate the impact/effect of the policy ...
user avatar
  • 21
5 votes
2 answers
229 views

causal impact estimation

say i have following causal model: outcome variable: Y (e.g. sales) treatment variable: T (e.g. price) covariate variable: x2 (e.g. traffic) unobserved variables: U (unobserved) causal relation: ...
user avatar
  • 191
1 vote
0 answers
111 views

how to run causalImpact on a time series with multiple interventions?

In CausalImpact package, one defines pre-period and post-period for a single intervention. However, in the scenarios where there are multiple interventions at irregular time intervals, is there a way ...
user avatar
  • 161
0 votes
0 answers
92 views

Why diff-in-diff over regression with control variable for measuring treatment intervention in time series?

Let's suppose we have a time series data set, with an intervention period for the treatment where the mean of the independent variable increases by 10. The goal is to measure the effect of the ...
user avatar
1 vote
1 answer
99 views

CausalImpact plot upper and lower bounds

Below is a screenshot of causal impact result. Upper and lower bounds of point wise results plot hovers around 10k and -10k. In summery statistics, sd shows 1879 with 95 CI of -4674 and 2736. Is the ...
user avatar
  • 11
0 votes
1 answer
198 views

CausalImpact estimates a statistically significant impact for multiple intervention-free validation periods

While trying to validate the estimated impact by CausalImpact package I ran backtests on several dummy pre and post time-periods prior to the actual intervention but ended up with statistically ...
user avatar
1 vote
1 answer
308 views

Causal impact R - Is it possible to model multiple the pre and post periods? Indivudally for participants

I would like to use the causal impact algorithm, however, not in the context of marketing, but in medicine. The problem is that the intervention does not take place at the same time, but on an ...
user avatar
  • 11
2 votes
1 answer
4k views

Staggered Diff-in-Diff: multiple treatments equation

I wonder if you can help me to figure out how to rewrite basic difference-in-difference equation (pictured) so that it takes into account the fact that treatment has occurred at different times for ...
user avatar
  • 23
1 vote
0 answers
87 views

Combine Different Metrics to CausalImpact

I am currently trying to understand the Google package of CausalImpact, to be more concrete the python implementation. My current state is that I have for example the sales of a car on different ...
user avatar
  • 111
0 votes
1 answer
110 views

How to test the stability assumption when using the CausalImpact package in R?

In the case of CausalImpact it is assumed that the relationship between covariates and treated time series, as established during the pre-period, remains stable throughout the post-period. Why is it ...
user avatar
  • 1
1 vote
0 answers
168 views

How to use CausalImpact in R to construct an interrupted time series model with >2 periods of interest?

I would like to conduct an interrupted time series analysis on data with three time periods: Pre intervention During intervention Post intervention My outcome variable is a continuous biological ...
user avatar
  • 143
1 vote
0 answers
108 views

Logistic Regression Coefficient Intrepretation - Impact On Churn

I am using logistic to see the relationship between churn and minute seen. I get something like this ...
user avatar
-1 votes
1 answer
142 views

Using CausalImpact to estimate uplift attributed to a promotion for logged-in users

I'm working for an online travel agency, and we've been exploring the use of the causalImpact algorithm for the following problem: Hotel owners that sell room-...
user avatar
  • 861
1 vote
1 answer
256 views

These summary statements seem contradictory, or have I misunderstood something?

So here's the output summary I got when running an analysis. This means that, although it may look as though the intervention has exerted a negative effect on the response variable when considering ...
user avatar
  • 11
0 votes
1 answer
477 views

Causal Impact: how to show all data points in predicted series? [closed]

This might be a very basic code question, but thank you for your help. I have used the Causal Impact package to run a regression on a data set with 144 monthly observations, cutting at point 88. I ...
user avatar
2 votes
1 answer
338 views

Estimate the time series like an event was never happened

I have data from a website where a specific advertising campaign happened a couple of years ago. What I want to do is to estimate how the signups on that website would have been without that big ...
user avatar
  • 93
1 vote
1 answer
97 views

Matching subjects with themselves when evaluating short term outcomes

I am considering a simple causal inference scenario; Let's say we want to examine the effect of paracetamol (treatment) on curing headache (outcome). When performing matching, is it okay to match ...
user avatar
1 vote
0 answers
54 views

Ok to use PSM to create treatment groups and then plug into CausalImpact? [closed]

Is it ok to use propensity score matching to create treatment and control groups and then plug these two time series into CausalImpact to estimate your treatment effect? I might want to do this, for ...
user avatar
  • 11
1 vote
1 answer
540 views

CausalImpact Conflicting Results - Posterior prob. v Confidence Interval

I'm getting conflicting results from a Causal Impact analysis I'm running. The 95% C.I. indicates that 0 is included and thus the impact is not significant; however the Posterior Probability is <....
user avatar
  • 13
1 vote
0 answers
545 views

How should I specify seasonality in CausalImpact? [closed]

I am working with the Python implementation of Google's CausalImpact package. My data is at daily frequency (365 observations per year); however, to inspect the effect of intervention, my pre-period ...
user avatar
0 votes
1 answer
114 views

Using CausalImpact in R, observed data affected by event that could not affect priors

I am just starting out using the Causal Impact package in R. I am looking at observed data where I know there will be periods of extra traffic due to outside forces. However I cant find any unbiased ...
user avatar
7 votes
3 answers
404 views

How to calculate causal effects with repeated exogenous shocks over a time series

A rather frequent problem in causal inference is that we come across various shocks over time and try to measure their impact. In the case of a single shock we can use bayesian methods to predict how ...
user avatar
  • 165
1 vote
0 answers
186 views

Default CausalImpact Package

I am trying to gain an understanding of the CausalImpact package and the BSTS approach. Consider the following model: $y_t = \mu_t + z_t + \epsilon_t$, where $\epsilon_t \sim N(0,s^2)$, and $\mu_{t+1} ...
user avatar
0 votes
1 answer
274 views

How is the posterior tail-area probability calculated?

I am currently using the CausalImpact package for some research and in this context I need to know and be able to explain, how the posterior tail-area probability is calculated in order to reproduce ...
user avatar
  • 1
1 vote
0 answers
74 views

inclusion of static variables as covariates [closed]

Is there a clear way to include static variables e.g. elevation as covariates in the CausalImpact pacakge. Any guidance would be greatly appreciated. Anand
user avatar
0 votes
1 answer
165 views

Incorporating Fixed Effects with Causal Impact

I have observations on a dependent variable of interest, $Y_{ijt}$, where $t \in [1,2,...T]$ denotes the time, $i$ denotes a particular brand and $j$ a specific product item. At $t=k$, there was an ...
user avatar
3 votes
1 answer
602 views

Synthetic control and unobserved confounders

The synthetic control (cohort) method is a very promising approach to causal inference that has been used in a number of interesting studies. It's particularly useful in situations where data are only ...
user avatar
  • 33