d. It will always be equal to the underlying population mean.
It is the best strategy for getting the sample whose characteristics imperfectly mimic the population.
a. Random sampling
b. Non-random sampling
c. Running observation cohort studies
Potential confounders are issue in the following type of study design.
a. Both observational cohort and case-control studies
b. Observational cohort studies
c. Case-control studies
Suppose I take a sample of 500 employed Baltimore City residents and ask them their commute time to work today (how long it took them to get to work today in minutes). The standard deviation of these 500 values is 24.2 minutes and the standard error of the sample mean is 1.1 minutes. What do each of these values (standard deviation and standard error) quantify?
a. Standard error quantifies the variability of individual commute times in the sample of 500; standard deviation quantifies the variation in sample mean commute times across multiple random samples of 500 employed Baltimore City residents.
b. Both quantify the variability of the individual commute times in the sample of 500.
c. Both quantify the variation in sample mean commute times across multiple random samples of 500 employed Baltimore City residents.
d. Standard deviation quantifies the variability of individual commute times in the sample of 500; standard error quantifies the variation in sample mean commute times across multiple random samples of 500 employed Baltimore City residents.
A randomized prospective study is conducted to estimate the association between taking a drug and remission for patients with a specific type of cancer. The estimated incidence rate ratio of remission for the treatment group relative to the placebo is 1.35. What is the proper interpretation of this value?
a. An individual (from the same cancer population) who does not take the drug is 35% less likely to go into remission as compared to an individual who has taken the drug.
b. In a random sample of 1,000 persons from the same cancer population, there would be 650 less remissions if these 1,000 persons took the drug as compared to if they did not take the drug.
c. In a random sample of 1,000 persons from the same cancer population, there would be 350 more remissions if these 1,000 persons took the drug as compared to if they did not take the drug.
d. An individual (from the same cancer population) who takes the drug is 35% more likely to go into remission as compared to an individual who has not taken the drug.