Uploaded by luca.nulens2

Statistics report

advertisement
Luca Nulens
I6265001
08/11/2022
Statistics report
A case control study was conducted and investigated the correlation between lead paint
exposure and ADHD diagnosis. A total of 63 children already diagnosed with ADHD and 337
children who were not diagnosed with ADHD participated in the study. Whereas 34 out of
the 63 children with ADHD were also exposed to lead paint (more as half of them) and 71
out of the 266 children who were not diagnosed with ADHD were exposed to lead paint.
Firstly, the OR was calculated. The odds ADHD and exposed are 34/71 = 0.479 and the odds
ADHD and not exposed are 29/266 = 0.109 so the OR is 0.479/0.109 = 4.392. Therefore, we
can say that childred with lead exposure have a 4.392 times higher odds of having ADHD
compared to children without lead exposure.
The null-hypothesis is b1 = Ln (OR) = 0 and the confidence interval of the odds ratio doesn’t
include 1 so therefore, we can say that it seems significant.
Furthermore the stratified OR was calculated. The OR for children who’s father do have
ADHD was 27 x 37 / 39 x 7 = 3.66 and for children who’s father do not have ADHD was 7 x
229 / 32 x 22 = 2.28. This means that for the OR of 2.28, the odds of people exposed to lead
exposure are 2.28 times higher of having ADHD compared to people who were not exposed.
However, 1 lays within the CI of 95% and therefore we can say it is not significant.
For the children who’s father does have ADHD, the OR is 3.66 which means that the odds of
people exposed to lead exposure are 3.66 times higher of having ADHD compared to people
who were not exposed. Here, 1 lays outside the CI of 95% and therefore, we can say that the
results remain significant. Since the values differ between the groups, this may imply that
lead exposure is the independent variable that should be investigated but yet the status of
the father. In this case, the status of the father is more like an effect modifier. Therefore, it is
important to stratify the data so we can see what effect a third variable might have on the
outcome and on the independent variable. __
Download