The Stack Overflow podcast is back! Listen to an interview with our new CEO.

Questions tagged [causalimpact]

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

Filter by
Sorted by
Tagged with
7
votes
1answer
744 views

Using Google Causal Impact package to assess the significance of a planned intervention

I am using the Causal Impact package in R to infer the causal effect of an intervention in some data which are highly correlated and seasonal. Specifically, i got 17 days of hourly data, intervetion ...
3
votes
2answers
603 views

Odd behaviour in CausalImpact (R)

I'm finding some odd behaviour in Google's CausalImpact R package and wondered if anyone has found the same and knows the cause. If you feed the package a certain length time series, the model snaps ...
3
votes
1answer
889 views

Bayesian Structural Time Series in BSTS package: implementing mixed model

I have been using BSTS package for quite a while and I have found it pretty effective with respect to ARIMAX models. I was wondering whether it would be possible to share regression coefficients in ...
3
votes
1answer
186 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 ...
3
votes
0answers
91 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 ...
3
votes
0answers
367 views

Pro and cons between Bayesian structural time series (BSTS) vs difference-in-differences?

Google's paper markets BSTS's benefits over DID such that "In contrast to classical difference-in-differences schemes, state-space models make it possible to (i) infer the temporal evolution of ...
3
votes
0answers
445 views

Specifying seasonality component in Causal impact

How do I supply yearly(month/week of the year) + day of the week seasonality in causal impact? I have 1 year of data in the pre period at daily granularity i.e. 365 data points. would, nseasons =52 ...
2
votes
2answers
427 views

How to choose Control groups for Causal Impact algorithm?

I'm running an experiment and want to use the Causal Impact function to assess how well it performs. I have 10 different cities. I'm looking to find out what is the best method for choosing which ...
2
votes
1answer
370 views

Reduce credible intervals in Causal Impact model

I'm hitting an issue with a causal impact model that I'm building. I'm trying to create a counter factual for daily sales at one store (nseasons = 7). I've included sales for 5 other stores nearby. ...
2
votes
1answer
963 views

causal impact - adding multiple control groups

I want to run an analysis using causal impact tool. I have one test group but multiple control groups. Can I use multiple control groups all together in one model? Eg: Y = test and A,B,C as control ...
2
votes
1answer
140 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 ...
2
votes
0answers
388 views

Remove price and promotion effects from sales time series

I'm trying to measure the effect of an in-store media campaign on the sales. I have sales data along the time for test (treated) stores and control (not treated) stores. Before comparing test and ...
1
vote
2answers
984 views

How to study the causal impact on multiple time series of interest against multiple baselines

My data consist of time series of Wikipedia hits for football players. I want to use the CausalImpact package to explore the effect of the World Cup on their ...
1
vote
1answer
197 views

How to reason about causal effect in time series when the treatment group reacts even before treatment?

Context: I'm running into a strange phenomenon about treatment effect and causality that I'll try to recreate here. Let's say I'm doing an observational study: Do people spend more time online as a ...
1
vote
1answer
585 views

Difference between using propensity score matching and CausalImpact for causal inference?

I'm investigating causal effect in some financial data, and I'm using two different approaches: propensity score matching with stratification and the CausalImpact package for Bayesian structural time ...
1
vote
1answer
152 views

Evaluating the Impact of National Policies Using Panel Data

I have a panel data set covering various countries over various years. I have information about the years in which these countries published an entrepreneurship policy - some countries only published ...
1
vote
2answers
132 views

CausalImpact: Valid for Single Market [closed]

Is it possible to use the R package CausalImpact (Brodersen et. al, 2015) to estimate the incremental lift of running a local TV ad campaign in Iowa City,IA? We are also running national TV ads across ...
1
vote
1answer
393 views

Scaling control time series with CausalImpact

I'm doing Causal Impact analytics with this python package. Since my control time series have a much larger scale (100-10000 times larger) than my modeled variable, at some point I tried to scale the ...
1
vote
1answer
240 views

Synthetic Control and Causal Analysis

I am creating a synthetic control variable in which I want to use in order to perform a causal impact analysis of our marketing campaign. The goal is to find a set of predictor time series that are ...
1
vote
1answer
291 views

Causality Analysis and test of Independence

First the problem: I am refering to lecture note, on page 480, 2nd paragraph, it mentions If X is in fact useless for predicting Y given Z, then an adaptive bandwidth selection procedure (like ...
1
vote
1answer
388 views

CausalImpact: model in the paper and default in the package

I was utilising CausalImpact for a study. Only recently did I realise that the model described in the associated paper was different to the default model implemented in the package. The paper was ...
1
vote
1answer
889 views

What does Posterior tail-area probability mean in Causal Impact?

I'm new to CausalImpact package in R. I'm trying to understand what the p-value or Posterior tail-area probability mean in the summary. Does it mean that because the p-value is very low, the chance ...
1
vote
1answer
127 views

Estimation of treatment effect when there is an unknown and variable coverage of the population

I am not sure if I am using the correct terminology, something must be written about the following problem, but I cannot find it by searching. I am presently analyzing data about the effect of ...
1
vote
1answer
260 views

Missing Data in CausalImpact and Additional Covariates

I am looking at the fantastic R package CausalImpact and had a couple questions hopefully someone can help with. What should be done when there are 0 values in a ...
1
vote
0answers
33 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 ...
1
vote
0answers
66 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 ...
1
vote
0answers
84 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
vote
0answers
37 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
1
vote
0answers
31 views

Assesing impact for rolling enrollment data

I'm running an experiment where some of the users are shown a new widget when they become eligible (some conditions that are unrelated to the experiment itself). I have a control counterfactual group ...
1
vote
1answer
85 views

Is it possible to predict the pre-intervention period rather than the post-period using Google's CausalImpact function?

I want to use to Google's causal impact function to impute the effect of an intervetion. However, my data is structured as: pre-period=1991-1995, intervetion occurs, post-period=1996-2017. To clarify, ...
1
vote
1answer
136 views

Explaining the results of the CausalImpact package where effect is not statistically significant

I've been using the CausalImpact package to compare patent renewal rates across different classes of patents (to determine whether subject matter decisions have particular impacts on the rise or fall ...
1
vote
0answers
220 views

Causal Impact: Continuous Pre-Intervention to Post-Intervention Time Periods?

Within the context of using R package CausalImpact (Brodersen et. al, 2015), is it valid to use time Periods that are noncontinuous for the Pre-Intervention and Post Intervention time periods? For ...
1
vote
2answers
233 views

Meta-Analysis on Effect Sizes with 95% Bayesian CI from CausalImpact R package

I am using the CausalImpact package in R to calculate the impact of a marketing intervention using Bayesian Structural Time Series. This methodology and package is explained in Broderson et al. 2015 ...
1
vote
0answers
297 views

Bayesian structural time series with few data points (using CausalImpact)

I am experimenting with the CausalImpact package https://google.github.io/CausalImpact/CausalImpact.html (Brodersen et al. 2015) which uses Bayesian structural time-...
1
vote
0answers
151 views

Chow Test and Structural Breaks

I am an economics student and we are tasked to make a mini thesis. I was thinking in getting smoking demand determinants and the effect of sin tax (excise tax on tobacco here in the Philippines and ...
1
vote
1answer
63 views

Comparing store sales based on time period

I am trying to refine the way my company validates tests in retail stores for products that we sell. The prior way was only to look at immediate change in dollar and unit sales without taking into ...
1
vote
0answers
99 views

Counterfactual analysis in the absence of an exogenous intervention

I am interested in exploring the causal effect of poverty on the adoption of a number of climate-resilient agriculture practices in sub-Saharan Africa. In exploring the causal effect of poverty (a ...
1
vote
0answers
78 views

Use of accelerated longitudinal designs with interrupted time series or difference and difference models

I am seeking some resources or specific equation specifications for whether or not it is possible to specify comparative interrupted time series models or difference and difference models with some ...
0
votes
1answer
517 views

Q: R - CausalImpact | order of control time series [closed]

My colleagues and I have been using Google's R-package CausalImpact for a while but recently discovered something that we can't quite explain. Depending on the order of including the different control ...
0
votes
1answer
790 views

Extracting Statistics from CausalImpact Summary

Say I have a CausalImpact Summary like this: ...
0
votes
1answer
71 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 ...
0
votes
1answer
91 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 <....
0
votes
1answer
111 views

How to use a custom model in CausalImpact where preperiod.start is not right after preperiod.end?

I want to train on a period that isn't immediately preceding the prediction period. You can do this using the default causal model but I'm not sure how with a custom model. Straight from the ...
0
votes
2answers
356 views

Interpreting Mediation Output when ACME is stat. sig but ADE and Total are not

The mediation package in R returns results in which: The Average Causal Mediated Effect (ACME) (the effect of the mediator alone) is positive and statistically significant Average Direct Effect (ADE) ...
0
votes
1answer
333 views

The Causal Impact Package in R could not trace the right number in the test group

I have this sample dataset which is as follow: head(data) ...
0
votes
1answer
311 views

How does CausalImpact Prevent Overfitting

I'm using Google Research's Causal Impact package, and I'd like to understand more fully how the package prevents overfitting and selecting a bad batch of the covariates by chance. Here's the ...
0
votes
1answer
659 views

What does the error “pre.period must span at least 3 time points” in the CausalImpact R package mean?

I've been encountering the error "pre.period must span at least 3 time points" when using the package. Can someone help me understand why the package requires me to have at least 3 time points and ...
0
votes
0answers
30 views

How to aggregate individual results with CausalImpact

In this answer, the author's suggestion is to: aggregate the individual MCMC traces and then summarise the result in terms of an expectation and a credible interval I understand that the MCMC ...
0
votes
1answer
27 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 ...
0
votes
1answer
32 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 ...