https://imgur.com/gallery/DFtcMju

Image linked for reference.

Problem: I’m trying to follow along with the results in this chart, but the odds ratio that I seem to come up with for the non-vaccinated group is 2.13, whereas the chart shows it as being 2.34.

The way I’ve been taught to calculate an odds ratio is by using the following formula: (a/b)/(c/d), where a involves the number of things with the presence of two properties, b and c each involve the presence of only one of these properties, and d involves all the things with the presence of neither property. If the two properties at hand here are “being unvaccinated” and “being a case patient,” it seems plugging the values into the formula would result in (179/284)/(50/169) or (179/50)/(284/169), both of which result in roughly 2.13. Is there an obvious mistake I’m making?

The chart comes from this study, if anyone wants a link to the source: https://www.cdc.gov/mmwr/volumes/70/wr/mm7032e1.htm

.

Important: The point of these charts / tables is to show how things are trending over time. They are based on the Vaccine Surveillance Report data, which overestimates the number of unvaccinated and therefore underestimates the risk for unvaccinated people. Do not read too much into the absolute number, it's the trend we're after here.

I've very much abstained from doing these plots before because of the issue with the VSR and the danger of giving fuel to anti-vaxxers. However, I saw someone respectable ask the question off how these odds ratios were varying over time on Twitter and what this implied for waning (and now I can't find it) so I thought I'd do the basic plots.

So, first, the odds ratio for cases over time:

https://preview.redd.it/eht70qh1drx71.png?width=679&format=png&auto=webp&s=2db0743ca5ea9fafb6d129526098f161d9efd469

Note that yes, according to these (known to be underestimate unvaxxed risk rates) stats, if you're over 30, you're more likely to test positive if vaxxed than unvaxxed. No, I don't believe this is true, but we only really care about the trends here.

The trend is steadily downwards in all cases except for a slight recent rise in the over 80's (booster effect?). I strongly suspect this is largely due to increasing immunity in the unvaxxed (at least in the younger age groups).

Corresponding charts for admissions:

https://preview.redd.it/0xwejwk2drx71.png?width=679&format=png&auto=webp&s=c1ab08a590282c21a3c35e80245ab3be81a86dc6

And deaths (note I haven't included the under 40's here - too few deaths for a valid plot)

https://preview.redd.it/tmprahw3drx71.png?width=679&format=png&auto=webp&s=38a7e8cb960bea8688f459bddbe561abec147239

Having made these plots, I do feel there's clearly a big effect caused by the effect of increased immunity amongst the unvaccinated (obviously so in younger age groups, where there's not going to be a lot of waning), and so it's very difficult to really get much information about waning (without some idea of changing attack rates amongst the unvaccinated elderly).

Raw Tables:

Cases

Hello there. I am still a novel user of r studio and was curios how I can create an odds ratio plot. I already have the values for odds ratios and the CI's for the difference variables if that helps. I want it to look like this graph below. Any help would be appreciated

https://preview.redd.it/8w9jn60rc2081.png?width=2854&format=png&auto=webp&s=008e74730ca39b5d8d17631e6e6e6dfb4e69885d

I have a predictor that I want to log transform because it is strongly positively skewed. I am conducting a negative binomial regression and will need to report on this predictor in terms of odds ratio. Is there a clean way to interpret the odds ratio of this log transformed predictor?

Ok in this example they look and men, women being republican or democrat

Democrat Republican

Female 8 4

Male 4 9

They do it in python like this:

data = [[8, 4],
         [4, 9]]

import scipy.stats as stats
print(stats.fisher_exact(data))
(4.5, 0.1152)

does that 4.5 odds ratio mean being risk of republican is higher if you are male?

I am performing a meta-analysis and I have compiled some adjusted odds ratios from a categorical variable, age. I have 18-30 years (reference group) versus 31-50 years and 60-100 years as my age groups (so I have two adjusted odds ratios). I am more interested in a 18-30 years (reference group) versus 31-100 years as a comparison. Is there a way to estimate what this adjusted odds ratio is for this comparison from my data? I think I can use the weighted average of the point estimates (from 31-50 and 60-100 year groups) but not sure if it is possible to get confidence intervals or p-values? Interested in any thoughts or experience in this area, thank you!

I'm new to statistics and I have been trying to recalculate the odds ratio for the covid study published by the CDC, infection rate for unvaccinated vs vaccinated. I tried to apply the odds ratio method that I found online but I'm for missing something. I would appreciate some help thanks.

https://www.cdc.gov/mmwr/volumes/70/wr/mm7044e1.htm?s_cid=mm7044e1_w#T2_down

https://www.cdc.gov/mmwr/volumes/70/wr/mm7044e1.htm?s_cid=mm7044e1_w#T2_down

An odds ratio (OR) is a measure of association between an exposure and an outcome. The OR represents the odds that an outcome will occur given a particular exposure, compared to the odds of the outcome occurring in the absence of that exposure

Example:

Results: Fifty (55.0%) of 91 persons taking paroxetine and 22 (23.9%) of 92 persons taking placebo were much improved or very much improved at the end of treatment (odds ratio [OR], 3.88; 95% confidence interval [CI], 2.81-5.36).

why are odds ratio at 3.88 here? I mean how can they know that giving paroxetine to 91 people gives a ~x4 chance of that being associated with a reduction of social phobia symptoms?

Basically: how does this odds ratio calculation work/go on? How is it made?

Hi All,

Any help/ pointers welcome! I have some stats background (taught A-Level, physics phd) but limited formal training beyond that.

So, I've got a longitudinal study whereby a cohort (with one medical condition) were assessed for a second medical condition and compared to matched case controls several years ago. This process has more recently been repeated with a largely similar cohort (some dropped out) and a new set of matched case controls.

What I'm largely trying to assess if is there is any statistical difference in the odds/risk across time for the cohort relative to their contemporary case controls. They're not so far apart that the CI's don't overlap, which is a shame!

1. Suggestion on establishing whether I'm better comparing odds ratios or relative risks?
2. Can I just compare the point estimates by calculating the z-statistic, or am I missing something?
3. Anything else you can think of!

Thanks, happy to provide more details, bit of a side project!

To me, option D and option A are equal. but apparently they are different. can someone please shed a light? Thank you.

The odds ratio for the above case control study is 4.95

In the above study, which of the following is the best way to describe the outcome:

A) The odds of developing cancer is higher among those who smoke compared to those who do not smoke.

B) The risk of developing cancer is higher among those who smoke compared to those who do not smoke

C) Smokers have a higher risk of developing cancer than non-smokers

D) Smokers have a higher odds of developing cancer than non-smokers

How to write odds in favor of rolling a 1,2,3,4,5, or 6 with one roll of a six sided die. Probability I understand is 1 or 100% of rolling a 1-6. Question is, how to write this as an 'in favor of' rolling a 1-6 odds ratio. Such as 6:0? Is this right?

I just saw their post & video recipe for V60 and the water temp is "80-95°C (rises with the number of days since the coffee was roasted)"

• in the post they're using: 18g to 240ml of water (1:13.333)
• in the video: 16g to 220ml of water (1:13.75)

Theoretically, the post quantity is what they use in the shops and while it's not my favorite V60, it's pretty good, not bitter, doesn't taste too concentrated.

I'm still new at brewing and still have a way to go until I get consistently good brews, but in most recipes I see ratios of 1:15-1:18. And also never seen a temperature below 90°C. How come?

What's your go-to, tried and tested ratio?

I've been trying 1:15-1:16 but I still get bitter, flavorless brews often (this time I tried adding some water to it and it made it better, but definitely didn't have the *right* aroma still, I only managed to do 1 good brew out of 4-5 with this coffee yet).

I usually get odds ratio from logistic regression by taking exp(beta).

Lets say you wanted to make a scatter plot of odds ratios from two studies. Its common to log transform the odds ratios before plotting like this, but which log to use for transformation, natural, base 2, base 10?

I'm discussing a retrospective article that uses odds ratios to establish an association between gross mucosal appearance during gastrointestinal endoscopy and histopathology findings. The authors attempt to make arguments using positive odds ratios that don't seem particularly impressive. Just like a Pearson correlation coefficient has established values with associated strengths of association (i.e. >0.7 = strong), can the same be said for odds ratio?

I don't know anything about genetics or whether this is a simple answer, so please excuse my ignorance.

Essentially I have two risk alleles for Alzheimer's on a SNP rs744373.

AlzGene, a very reputable source, states the OR is 1.17, but I assume that is for one allele?

Therefore, what would the odds ratio of having two alleles be? SNPedia states it is 1.28, but I couldn't find their source.

Thanks again

I am writing my manuscript and i have a variable (the quadratic term of a non-linear continuous variable) that has an odds ratio of 0.9999186 that is significant in the logistic model (95% CI 0.9998753, 0.9999619). The journal i hope to publish in doesn't have any guidelines regarding how to round and present an odds ratio that is significant, but approaching 1 with a finite number of 9's after the decimal. I know the odds ratio of this term cant be interpreted, and I'm using a margins plot for that, but i was wondering if there is a convention for reporting the odds ratio and confidence interval of these results in a table where i need to report the odds ratio and 95% CI