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Questions tagged [intervention-analysis]

Intervention analysis estimates the effect of an external intervention on a time-series.

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Modelling longitudinal pre-/post-intervention data

I have longitudinal data of a number of patients for which some biomarker was measured at irregular time intervals over the course of several years before treatment and over a shorter period of time (...
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How to estimate the parameters of an Intervention model for time series

If we consider the simple of a single intervention: $$Y_t=m_t+N_t$$ where $m_t$ is the change in the mean function and $N_t$ is modeled as some ARIMA process, possibly seasonal. I have been trying to ...
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How can we apply sensitivity analysis in comparing two ARIMA models, both measuring intervention effect?

I have a dataset of reporting rates collected over an 8-month period obtained from the baseline (4 months) and during intervention (4 months). The goal is to determine if the intervention has a ...
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Modeling longitudinal change in outcome per unit of change in a continuous explanatory variable

My question is related to How do you deal with "nested" variables in a regression model? However, my issue is slightly different. I'm analyzing RNA-seq gene expression data (>10 000 genes)...
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Please can I have some guidance on analysing policy change on time series data?

Firstly, I am not a statistician, merely a consumer of statistics (NHS Pharmacist). I am undertaking a project looking at the impact of a new clinical test on antibiotic prescribing across multiple ...
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Assessing bivariate change (pre- and post-intervention) when sample size is small and there is no control group?

I have data from a randomised control trial of approximately 60 people (30 people in the intervention group, 30 in the control group). I would like to assess whether change in one variable (M) is ...
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can I use causalimpact (BSTS) to forecast without an intervention?

As a data scientist without much formal training, I'm looking to get some professional feedback on the following question: Is it ever advisable to use causalimpact (or I guess BSTS generally) to ...
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Statistical Test or Regression for Intervention Effectiveness?

I'm looking to model the effectiveness of an intervention on human behavior. I have control groups and treatments groups for the outcome of interest and pre and post measurements (just 1 for each) for ...
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Do operator on a 2 node system

If my causal structure consists of $y$ influencing $x$ (so the DAG would simply be $y\to x$), my understanding is that $p(x|do(y=1))=p(x|y=1)$. But what is wrong with the following argument? $$p(x|do(...
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How to assess effect of event within group

I'm trying to conduct an analysis for my organisation of a change in the our complaints processing system with regards to whether it has had any adverse impact relating to a couple of demographic ...
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standardizing an indicator variable and coefficients to 0

I am fitting a distributed lead, lag models to understand the impact of an event that took place in 2017. My outcome y is a continuous variable. The event took place in 2017. I am interested in ...
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Causal inference on time-series data: is intervention needed?

I'm working on the topic of causal inference, I use time-series data. I have two scenarios in front of me and I don't understand the difference: Given X and Y "time" features. I would like ...
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Intervention in pgmpy causal given evidence

The .query method in pgmpy computes the effect of one variable X on Y given evidence Z. I'm not sure Z is a set of observed covariates; if that is the case, isn't ...
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Interpretation of interaction (time x intervention) in an intervention study when baseline values are unequal

I came across an intervention study that measured a significant decrease in a specific treatment group. However the starting conditions where not the same and are like*: So there is a difference ...
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Evaluate time lag between an event in exogenous variables, and the response of a endogenous variable in regression SARIMAX model

I am currently using autoregressive models to assess the influence of exogenous variables on the dynamics of a shellfish population. These exogenous factors are water temperature, salinity, and food ...
Daniele Pinton's user avatar
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Propensity scores with past observations

Theoretical question here: is it possible (and justifiable) to do propensity score matching when all control units come from a different time period? For example, imagine there is a programme for 18 ...
Rob_research's user avatar
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Is the conditional probability fallacy exising in the case of an individual with full control [closed]

Hello I had a very interesting discussion and I need your help in clarifying the correct answer. TLDR: Problem statement for a layman: Given I am a woman and I want to become professor, and given that ...
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Can I do a multilevel analysis for my study?

Some details about my design can be found below: There are 2 groups: Group 1 and Group 2. There are different numbers of people in each group. A pre/post (measurement) of stress is taken several ...
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Using Box-Jenkins methodology for intervention analysis

I'm trying to follow B-J methodology for my intervention analysis. My understanding of of the first step is that, one should detrend any systematic trends such as seasonality then determine the lag ...
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Quantifying the impact of multiple time series on another time series

I have a few time series that correspond to the popularity of various documentaries about food, and other time series that correspond to outcomes of interest (various dimensions of food consumption). ...
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Is there any way I can improve my interrupted time series analysis on this data?

I ran a simple ordinary least squares (OLS) model of the form y = b_0 + b_1 * T + b_2 * D + b_3 * P + e where y is the number of murders in a given month, T is the number of months passed from the ...
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Interrupted time series with continuous treatment

I am intending to conduct interrupted time series analysis of a public health intervention applied nationally. Since the intervention is national, I'm not intending to do a controlled ITS unless I can ...
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Comparison of Two Populations in ARIMA Interrupted Time Series

I am trying to do a comparison of the impact of COVID-19 on cancer diagnoses in the US. I have fit an ARIMA model to all cancer site monthly incidence rates for the US from January 2018 to December ...
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Equation for Interrupted Times Series Analysis with Multiple Intervention with Control Series

I have used STATA to conduct an ITSA but am having trouble writing the equation for it. Period A: 2005-2010 Intervention 1 Period B: 2011-2015 Intervention 2 Period C: 2016-2020 I understand the ...
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Best statistical test for comparing pre and post intervention (but the intervention happens repeatedly?)

The intervention: before each new appointment with a student the guidance counsellor is reminded to consult with the student about proper information on contraceptives. The control group measures how ...
Flooreen's user avatar
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Testing if volatility increases during ECB-Monetary Press Releases

I'm currently writing a thesis where I am trying to disect the ECB monetary press releases and their impact on the European stock market. I am using an event study methodology. Computing Daily Excess ...
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Stationarity in an interrupted time series

I am using proc autoreg in SAS to conduct an ITS analysis and I have a question about stationarity. Proc autoreg is able to ...
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Mean difference (95% CI) between paired samples

I have some results from a study pre- and post-intervention. It's for an underpowered feasibility study, hence I am not performing formal hypothesis testing but I'd like to calculate mean difference (...
Josh's user avatar
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Computing counterfactual query given an SCM and how it differs from computing interventional query?

Assuming we have the following structural causal model (SCM), with a confounder DAG structure, as follows: Noise variables: $$U_1 \sim \mathcal{N}(0,\,1)$$ $$U_2 \sim \mathcal{N}(0,\,1)$$ $$U_3 \sim \...
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How to handle previous interventions within the pre-period of the same time series using causalimpact?

Below you can view the univariate sales dataset for a particular product with x3 promotional interventions/campaigns (highlighted in grey and green); each promotion campaign stretched for a length of ...
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What do we exactly mean by P(Y=y|do(X=x), M=m)?

I know that P(Y=y|do(X=x)) is different from P(Y=y|X=x) in that the former is an interventional probability where the intervention is applied to the entire population, whereas the latter is a ...
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Does "Regression Discontinuity" Require the Presence of an Intervention?

I have been trying to learn more about "Regression Discontinuity". This appears to be a statistical method designed at testing the effectiveness of some sort of intervention. The Wikipedia ...
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Testing the impact of a events on time series

Context I'm working with product data for a retail company. I have the daily impressions (number of times it was viewed online) for all products over a 30 day period (can get more data). Here is the ...
OrangeChutney's user avatar
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Compare subgroups on before and after intervention

Assume the following research experience. A group of researchers went to a school. On the first day, they gave a questionnaire about a topic for the students to fill. The next day, the researchers ...
user3199227's user avatar
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Comparing intervention/control group

I am planning to conduct a study which is based on an RCT design. I am intending to conduct an intervention. During this intervention, participants and control group enter some medical data on daily ...
Jens's user avatar
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1 answer
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Interrupted Time Series Design with multiple groups

More of a conceptual question The standard ITS design is pretty simple, regress: Y ~ Time + Treatment_Dummy + Time_Since_Treatment However, what if the scenario was ...
zaberfire's user avatar
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Propensity score matching sample size

I am considering doing a propensity score matching to evaluate the effectiveness of a intervention. However, i only have 193 cases in my treatment group. I have a lot in control group. My outcome is a ...
Jane Li's user avatar
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Best way to compare income of two groups of people over time

I am planning a research study where, among other things, I want to understand how an intervention changes income in two groups. I plan to collect income data from each individual at three time points....
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2 answers
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Compare paired before and after composition proportions

I have some data on the composition of purchases by households, before and after an intervention. This composition is known at the number of items or amount spent level within 7 categories, and can be ...
Stephen Clark's user avatar
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Finding lagged time series effects

I have a time series with the number of customers and discounts. I suspect that the percentage of discount has a postponed effect. I tried just lagging the variable and calculating the correlation, ...
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Causal Inference Short Time Series

I am trying to analyse causal inference associated with an intervenion using either Difference-in-Differences or Interrupted Time Series Analysis. I have a discrete time series consisting of data ...
j.rahilly's user avatar
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1 answer
701 views

How to decide on parameters for transfer function in intervention analysis using ARIMA?

I'm very new to Time-Series Analysis and ARIMA so, although I've read a ton of stuff trying to figure it out, I'm sorry if this has already been answered elsewhere. I'm doing an analysis that's very ...
eliseabril's user avatar
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497 views

What does the superscript triangle (△) symbol mean in graph/causality notation?

I am reading a paper called Robustly Disentangled Causal Mechanisms: Validating Deep Representations for Interventional Robustness and in stating a proposition the authors use a triangle superscript ...
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Omitting dummies in panel regression?

I am running a regression studying the effects of different interventions (which appear as dummy variables - they either did or did not have that particular intervention). I don't have a control group ...
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How can i use an ARIMA model to explain the an effect of news regarding COVID-19 on a stock market index?

My thoughts were to model the time series of the stock index up until the particular day for the news I am looking at and forecast using my model. Then I would compare the forecasted result to the ...
Daniel's user avatar
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Influence of TV spots on the number of visits to the website (time series problem)

I have hourly data regarding the number of visits to the website. A single record consists of date, time(0-23) and number of visits. In a separate table I have data about the display of advertising ...
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3 answers
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What kind of analysis to use to compare time series trade data

I have a time series data set that gives me the adjusted imports and exports for the period 2003-2016. Suppose a trade agreement was signed in 2009. I want to compare the bilateral trade before and ...
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Time series (or Survival) analysis looking at effect of multiple policy changes over time

I'd like to look at the effect of lockdown policies(announcements) over time on features of the COVID-19 epidemic. I'm not very familiar with different time-series, so i'd like advice on what type of ...
RNB's user avatar
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2 votes
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Subject level variation in repeat measurement designs - representing treatment effects

Consider an experimental situation where each of $n$ participants are randomised to one of two treatments (e.g. active versus placebo). Our measuring device is known to have some variability in the ...
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What's a proper method for analyzing an intervention in a seasonal time-series?

My data has the following structure (I cannot post the real data): The data contains 20 shapes (round, squared, triangle), 2 were chosen for simplicity. The data is recorded for almost 2 years (aprox ...
cristian hantig's user avatar