Introduction to Epidemiology

Question 1

epidemiology

Answer 1

the study of the distribution and determinants of disease and health related events in populations
AND
the application of this study to controlling and preventing health problems

Question 2

p value

Answer 2

probability of the data being compatible with the null hypothesis

Question 3

null hypothesis

Answer 3

assumes there is no association between X and Y

Question 4

high P value

Answer 4

high probability that there is NO association between X and Y

do not reject the null hypothesis

p > 0.05 means that you’d expect to obtain the data you did >5% of the time, therefore there is likely no association between X and Y

Question 5

low P value

Answer 5

low probability that there is NO association between X and Y

reject the null hypothesis

p < 0.05 means that you’d expect to obtain the data you did <5% of the time, therefore it is likely that there is an association between X and Y

Question 6

hypothesis testing

Answer 6

start by assuming the null hypothesis is true and determine the probability (p-value) of getting your results if the null hypothesis was true

Question 7

alpha level

Answer 7

level of significance; cutoff value of P for rejecting/not rejecting the null

usually 0.05 or 5%

Question 8

type I error

Answer 8

willing to err on the side of wrongly rejecting the null hypothesis 5% of the time

Question 9

does statistical significance always correlate to clinical significance

Answer 9

NO
- low P value can reflect minimal clinical effects
- high P value can reflect significant clinical effects

Question 10

what are P values a function of

Answer 10

sample size

large sample size = greater precision

statistically insignificant data from a study with a small sample size could be significant if the sample size was larger (type II error)

Question 11

type II error

Answer 11

even if a difference between groups does exist, the study may not be statistically powerful enough to find those differences

ex. small sample size = low statistical power

Question 12

confidence intervals

Answer 12

interval with an associated probability (confidence) of 1-alpha

“we are (1-a)% confident that the confidence interval contains the true population meausre

Question 13

what does it mean if 1 is included in the confidence interval

Answer 13

no association - means that the risk could be equal to 1 (equal risk in both groups)

Question 14

what are the source of error in a study

Answer 14

random: variance
systematic: bias

Question 15

validity

Answer 15

unbiased/accurate data

what we are measuring is what we want to be measuring

Question 16

precise

Answer 16

variances/standard deviations/standard errors are small (minimal variability in the data)

Question 17

confounding bias

Answer 17

comparing study populations that would have different health or disease outcomes even if they had the same treatment/exposure

comparing things that shouldn’t be compared

Question 18

how can confounders be controlled for

Answer 18

randomization

Question 19

what is confounding by indication

Answer 19

treatment is not randomized but deliberately chosen for specific reasons (clinical indication, cost, availability)

Question 20

selection bias

Answer 20

choice of individuals selected to be in studies leading to invalid results

Question 21

follow up bias

Answer 21

not following up with all individuals over time (censoring) leading to bias

Question 22

information bias

Answer 22

occurs when the treatment/exposure and/or the outcomes are measured with error

Question 23

specification bias

Answer 23

doing the statistical analysis wrong