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Questions tagged [causalimpact]

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

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2answers
209 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 ...
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1answer
688 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 ...
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1answer
65 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, ...
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1answer
108 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 ...
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1answer
55 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 ...
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1answer
38 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 ...
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1answer
72 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 ...
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1answer
58 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 ...
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1answer
49 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 ...
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1answer
86 views

How can you quantify the effect of a campaign in CausalImpact?

I have been working with the CausalImpact R-package to check whether new campaigns or features had a significant impact on a time-series. I would like to know if it is possible to quantify this ...
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1answer
131 views

BSTS employing purposedly spurious regressors for causal impact analysis

I'm employing Google Correlate time series to evaluate the causal impact of an intervention on a variable of interest y. I made sure that the Google series are highly correlated with y during the pre-...
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1answer
357 views

CausalImpact with Custom BSTS Model

I'm wanting to use a custom bsts model within the CausalImpact package, and I understand that I need to use a control group in my data; however, I don't really understand where that control group fits ...
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0answers
62 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 ...
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0answers
301 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 ...
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0answers
354 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 ...
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0answers
339 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 ...
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0answers
53 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+...
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0answers
26 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 ...
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0answers
155 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 ...
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0answers
280 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-...
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0answers
146 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 ...
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0answers
94 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 ...
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0answers
73 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 ...
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0answers
16 views

Endogenous subgroups in impact estimation

I am using RCT data to estimate the impact of a program. After doing the straightforward analysis, I decided to estimate the program impact by subgroups (treatment status*subgroup). The subgroups were ...
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0answers
38 views

Impact of propensity model

I have built a propensity model, which gives out probabilities of a customer paying given a collection intervention using a xgboost model. The model has an AOC-ROC of 81% with an accuracy of 77% ...
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0answers
144 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 ...
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0answers
113 views

Can I use a list (or similar) of multiple date ranges for pre and post periods?

In the documentation (https://google.github.io/CausalImpact/CausalImpact.html) for CasualImpact there is an example of setting pre and post periods of the treatment: ...
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0answers
293 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 ...