<p>I am running an event study analysis (I am still very new to this method) and I tested the impact of belonging to a certain age cohort on vaccine uptake (conditional on belonging to a minority group). The policy change occurred in 2007, and it was not anticipated. However, the impact of the event (policy) was not significant for vaccine uptake (Figure 1) but had statistically significant impact on other unintended health outcomes (FIgure 2). Am I interpreting this correctly based on the attached event study graphs?</p>
<p><a href="https://i.sstatic.net/RU8Av.png" rel="nofollow noreferrer"><img src="https://i.sstatic.net/RU8Av.png" alt="Impact of policy change on vaccine uptake" /></a></p>
<p><a href="https://i.sstatic.net/C5kEw.png" rel="nofollow noreferrer"><img src="https://i.sstatic.net/C5kEw.png" alt="Impact of policy change on GP visits" /></a></p>

CC BY-SA 4.0
2023-10-04T18:34:17.557Z
How exactly you carried out the study? Based on graphs there does not seem to be any significant effect (assuming intervention was at T=0). There is no jump, at a point of intervention or before, just a continuous declining trend in both cases. I wonder how did you exactly got significant difference there if you accounted for the trend
1muflon1
CC BY-SA 4.0
2023-10-04T19:06:41.380Z
So I used Stata and the package eventdd written by Clarke and Tapia-Schythe (2021). I use age at the time of the policy change where I standardized ages by differencing 2007 from year of birth. Then I ran the outcomes I was testing using the following code
'''eventdd vacchest  $controls2 i.state i.province, timevar(timetotreat) ci(rcap) clust(districtia) accum leads(10) lags(9) '''
Lorien
<event-study>
Interpreting event study estimates
Lorien
# Interpreting event study estimates

(Asked by: username_0 on 2023-10-04)

I am running an event study analysis (I am still very new to this method) and I tested the impact of belonging to a certain age cohort on vaccine uptake (conditional on belonging to a minority group). The policy change occurred in 2007, and it was not anticipated. However, the impact of the event (policy) was not significant for vaccine uptake (Figure 1) but had statistically significant impact on other unintended health outcomes (FIgure 2). Am I interpreting this correctly based on the attached event study graphs?

[![Impact of policy change on vaccine uptake](https://i.sstatic.net/RU8Av.png)](https://i.sstatic.net/RU8Av.png)

[![Impact of policy change on GP visits](https://i.sstatic.net/C5kEw.png)](https://i.sstatic.net/C5kEw.png)

**Tags:** event-study

> **Comments:**
> **username_1**: How exactly you carried out the study? Based on graphs there does not seem to be any significant effect (assuming intervention was at T=0). There is no jump, at a point of intervention or before, just a continuous declining trend in both cases. I wonder how did you exactly got significant difference there if you accounted for the trend  
> **username_0**: So I used Stata and the package eventdd written by Clarke and Tapia-Schythe (2021). I use age at the time of the policy change where I standardized ages by differencing 2007 from year of birth. Then I ran the outcomes I was testing using the following code '''eventdd vacchest  $controls2 i.state i.province, timevar(timetotreat) ci(rcap) clust(districtia) accum leads(10) lags(9) '''  

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## 0 answers

