UTF-8 U+6211 U+662F wrote:Nerd_Bunny wrote:I'm going to try to do "hard" questions.
Info:
You perform a test. You learn that you got 22 false positives, 10 false negatives, 75 true positives, and 38 true negatives.
1. Calculate the sensitivity and interpret your results.
2. Calculate the specificity and interpret your results.
(The following questions do not pertain to the info.)
3. Which organisms contain two types of nucleic acid? (Bacteria, virus, animal, etc.)
4. Define antigen.
5. Define animal in an epidemiology context.
6. Which case studies are used to calculate prevalence?
7. Define and give an example of Simpson's paradox.
8. Define and give an example of Late-Look bias.1. 75/(75+10) = 75/85 = 15/17; The test detects 15/17 of positive cases. 2. 38/(38+22) = 38/60 = 19/30; The test correctly rules out 19/30 of negative cases. 3. I'm not so sure about this, but I would guess all eukaryotes 4. A foreign substance in response to which antibodies are produced 5. Not sure what you mean here, but arthropods often act as vectors to disease, and vertebrates often act as natural reservoirs to disease. People can contract disease from such vertebrates by zoonosis. 6. You can calculate the prevalence of a disease using a descriptive study, e.g. time series analyses, ecological studies, and surveys (cross-sectional studies). 7. When data has one correlation when separated into groups but the opposite (positive vs negative) correlation when combined, e.g. if the prevalence of the disease increases with increasing age in the age groups of 20-30 and 70-80, but the group of 70-80 has a much smaller prevalence of disease, the prevalence of the disease actually has a negative correlation with age. 8. No idea.
1 + 2: Correct, although sensitivity and specificity are expressed as percents. 3. Bacteria, protozoa, fungi, and animals. Not all eukaryotes. 4. Correct. 5. I wasn't really looking for a really specific answer, but you got it right. :) 6. Correct. 7. Correct. 8. Late-look bias is when the late diagnosis of a disease is falsely perceived as a longer survival rate. An example would be a case-control study performed on a disease where half of those affected die within 2 weeks, while the other half have an average survival of 8 years. Most patients included in the study are those who survive beyond two weeks.
