News Gulf [1991] War vets risk paralyzing disease

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Recent studies indicate a notably high incidence of incurable ALS among Gulf War veterans, with 40 cases reported out of 696,000 troops, compared to 67 cases among 1.8 million who did not deploy. The statistical analysis reveals a significant difference in ALS rates between the two groups, with a p-value of 0.02852, suggesting that the likelihood of observing such a difference by chance is low. Despite the small number of cases, the large sample sizes allow for meaningful comparisons. Concerns about potential inaccuracies in case reporting are acknowledged, but the statistical significance remains robust, indicating that Gulf War veterans may be more susceptible to ALS than their non-deployed counterparts. The discussion emphasizes the importance of the rates of ALS rather than just the number of cases, reinforcing the findings of a potential link between Gulf War service and increased ALS risk.
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With numbers so small (40 or so total cases), its tough to identify cause and effect or analyze statistical deviations. It may simply be (for example) that als is found sooner in military people because they are more physically active and get more physical exams than the rest of the population.
 
The numbers actually aren't small at all. They say 40 of the 696,000 Gulf War troops now have ALS, compared to 67 of nearly 1.8 million who stayed home. The number of positive cases is small, yes, but the sample sizes themselves are very large.

We have pALS|Gulf War = 40/696,000 = .0000575, compared with pALS|Stayed Home = 67/1,800,000 = .0000372. The p-value for a double tailed hypothesis test with H0: pALS|Gulf War = pALS|Stayed Home and HA: pALS|Gulf War != pALS|Stayed Home is 0.02852-- in other words, if there is no real difference between the odds of Gulf War troops contracting ALS vs troops who stayed home, there is only a 2.852% chance that we would see the sample statistics that have been compiled. I haven't done a power test since the equation is long and nasty, but with sample sizes that big it's almost certainly a safe bet that we can rule out a Type II error as well as Type I. In other words, the numbers are statistically significant-- something strange went on in the Gulf War, making American troops who fought in it more susceptible to ALS than American troops who did not.
 
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Originally posted by hypnagogue
The number of positive cases is small, yes, but the sample sizes themselves are very large.
Its the number of cases, not the sample size that matters because the comparison is of the rates themselves. If for example their number is off by 1 for some reason (maybe a false positive or by chance someone got hit by a truck before being diagnosed) that's a 2.5% change in the incidence rate. Thats huge.
 
Any random factors affecting the number of ALS cases recorded in one group should theoretically apply equally well to the other, especially with such large sample sizes-- so they should more or less cancel out. Even if they don't, from the numbers posted it's clear that the number of ALS cases on either side could be off by a bit and still yield us statistically significant results. This is especially true since the quick statistical analysis above is based on a conservative double tailed test. If I had tested a one tailed alternative hypothesis (which is really what is in question here-- are the Gulf War troops more likely to contract ALS?) HA: pALS|Gulf War > pALS|Stayed Home, the results would be even more statistically significant and thus even more resistant to small errors in measurements.
 
Similar to the 2024 thread, here I start the 2025 thread. As always it is getting increasingly difficult to predict, so I will make a list based on other article predictions. You can also leave your prediction here. Here are the predictions of 2024 that did not make it: Peter Shor, David Deutsch and all the rest of the quantum computing community (various sources) Pablo Jarrillo Herrero, Allan McDonald and Rafi Bistritzer for magic angle in twisted graphene (various sources) Christoph...

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