Disease Detectives B/C

[yang573]

Something something no posts.

George sneezed in Lucas' face and Lucas caught his cold. Ptady, who was sitting across the room, also gets sick.

What two types of transmission are responsible here? Be specific.

[Private Wang Fire]

Something something no posts.

George sneezed in Lucas' face and Lucas caught his cold. Ptady, who was sitting across the room, also gets sick.

What two types of transmission are responsible here? Be specific.

Are we gonna revive this :o (answer) (Click to Show Hidden Text)

Lucas - droplet
Ptady - airborne

[yang573]

Something something no posts.

George sneezed in Lucas' face and Lucas caught his cold. Ptady, who was sitting across the room, also gets sick.

What two types of transmission are responsible here? Be specific.

Are we gonna revive this :o (answer) (Click to Show Hidden Text)

Lucas - droplet
Ptady - airborne

That is correct. Your turn.

[Private Wang Fire]

You are conducting a study on [some disease] when a helpful friend tells you age may be a confounding variable.

1. What is confounding?
2. How can you modify your study design to account for this?
3. Which test statistic would you use after data collection?

[Unome]

Something that I know! (Click to Show Hidden Text)

1. If a variable is associated with both the exposure being tested and the disease/treatment being studied, but is not causally related to the exposure, then it is a confounding variable, or confounder.
2. Stratify or match the participants by age group, or just restrict the study to a certain age group (though the second may create further confounders).
3. Not sure exactly what's being asked; is this asking for a type of statistical test?

[Private Wang Fire]

Something that I know! (Click to Show Hidden Text)

1. If a variable is associated with both the exposure being tested and the disease/treatment being studied, but is not causally related to the exposure, then it is a confounding variable, or confounder.
2. Stratify or match the participants by age group, or just restrict the study to a certain age group (though the second may create further confounders).
3. Not sure exactly what's being asked; is this asking for a type of statistical test?

yup! Number 3 should be: (Click to Show Hidden Text)

Cochran Mantel-Haenszel (statistical test for stratified data) (idk how to calculate it or use tho lol)

You got next?

[Unome]

About #3 (Click to Show Hidden Text)

Does that count as a test statistic? I always thought of those as being like Fishers exact or chi-squared, and Cochran-Mantel-Haenszel being a method of finding risk. And calculating it is iirc somewhat like a weighted mean using the total population of each stratum (I know this because my partner BS'ed it at the last tournament and got full credit - unfortunately her attempt at BS'ing a chi-squared problem didn't work as well :geek: )

In preparation for MIT, here's an [strikethrough]extended[/strikethrough] semi-extended case study (hopefully my question actually makes sense, I don't know much about writing these types of questions) (Click to Show Hidden Text)

An investigator is collecting data on an outbreak of botulism in the town of Milford in southern Delaware. The investigator suspects that a steak joint in the town may have been transmitting the disease. The investigator determines that of the 12 living cases (3 cases have died, and the investigator couldn't find information about them) 7 of them can remember having eaten at the steak joint. Using as a control a sample of 18 people randomly selected from Sussex County (the southernmost of Delaware's three counties), the investigator determines that 2 of those people remember having eaten at the steak joint.

1. What type of study is this?
2. Give three potential sources of bias in the study, and explain how each of them affects the data.
3. Choose one of the sources of bias that you listed above and explain how the study should have been conducted to mitigate that bias.

Assuming that the study was conducted accurately (without systematic biases) and the same data was collected:

4. Choose an appropriate measure of risk, explain why the measure is appropriate, and calculate it (show work).
5. Choose an appropriate measure of statistical significance, explain why the measure is appropriate, and calculate it (show work).

[yang573]

Yeah, I'd call CMH RR and OR as a form of analysis/adjustment rather than a statistical test.

answers of dubious correctness (Click to Show Hidden Text)

1. case-control
2. rumination bias - exposure of controls may be underrepresented; Neyman's bias - dead not included, possibly underrepresenting the exposed group; interviewer bias - nature of questions asked may lead to overrepresentation of the exposed group
3. Neyman's bias: find a medium

4. Odd ratio is used because incidence can't be calculated. The actual size of the exposed group is unknown
OR = ad/bc = [(7)*(18-2)] / [(12-7)*(2)] = 11.2
5. I think a z-test would do, because you're working with proportions rather than numbers. I believe you're only required to understand statistics and not expected to calculate them. :P

My question is, how does a steak joint transmit botulism? Canned beef?

[maxxxxx]

I think a z-test would do, because you're working with proportions rather than numbers. I believe you're only required to understand statistics and not expected to calculate them.

On the statistics handout from soinc.org it lists the equation for z tests, so I'd assume we're expected to know how to calculate it. I'm pretty sure the only ones we're just supposed to understand are CMH, Fisher's Exact, and McNemar's.

[yang573]

I think a z-test would do, because you're working with proportions rather than numbers. I believe you're only required to understand statistics and not expected to calculate them.

On the statistics handout from soinc.org it lists the equation for z tests, so I'd assume we're expected to know how to calculate it. I'm pretty sure the only ones we're just supposed to understand are CMH, Fisher's Exact, and McNemar's.

Oddly enough, I've never been expected to complete a statistical test, but I've been asked to perform adjustments. At states last year, I had to do a CMH-RR.

but here you go (Click to Show Hidden Text)

Assume the conditions have been met.
H0: p = 1/2
HA: p > 1/2
significance level: 0.05

SD(p-average) = sqrt( (p-exact * q-exact) = sqrt( [(1/2) * (1/2)] / 30 ) = 0.00617284

z = (p-average - p-exact) / SD(p-average) = ((7/9) - (1/2)) / 0.00617284 = 3.042903097
p of z = 0.001172
p < 0.05
Reject the null hypothesis. The proportion of cases among exposed is greater than 1/2.

I'm not sure I trust those calculations.

While working on this problem, I found this interesting read: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2938757/ I'm not sure if a z-test is appropriate with a contingency table; a confidence interval may be more suitable

Thinking about it, I think a Fisher's Exact Test would also work.

calculations (Click to Show Hidden Text)

Assume conditions are met.
H0: a/c = b/d
HA: a/c =/= b/d
significance level: 0.05

p = [(a+b)! * (c+d)! * (a+c)! * (b+d)!] / [a! * b! * c! * d! * n!] = [9! * 21! * 12! * 18!] / [7! * 2! * 5! * 16! * 30!] = 0.008469611

p < 0.05
Reject the null hypothesis. There is an association between the exposure status and disease status.