Biostats

Question 1

testing frequency of disease and frequency of risk related factors

asks “what is happening?”

Answer 1

cross-sectional study

Question 2

compares a group of people with disease to a group without disease

looks to see if odd of prior exposure or risk factor differ by disease state

asks “what happened?”

Answer 2

case control study

Question 3

compares a group with a given exposure or risk factor to a group without such exposure

looks to see if exposure or risk factor is associated with later development of disease

Answer 3

cohort study

Question 4

are cohort studies prospective or retrospective

Answer 4

can be either

Question 5

compares frequency with which both monozygotic twins vs both dizygotic twins develop the same dz

Answer 5

twin concordance study

Question 6

compares siblings raised by biological vs adoptive parents

Answer 6

adoption study

Question 7

what does the likelihood ratio mean

Answer 7

likelihood that a given test result would be expected in a patient with the target disorder

compared to

the likelihood that the same result would be expected in a patient without the target disorder

LR+ > 10 indicates highly specific test

LR- < 0.1 indicates highly sensitive test

Question 8

hawthorne bias

Answer 8

subjects changing behavior when they know they’re being observed

Question 9

berkson bias

Answer 9

cases and/or controls selected from hospitals are less healthy and have different exposures than general population

Question 10

attrition bias

Answer 10

participants lost to follow up have a different prognosis than those who complete the study

Question 11

recall bias

Answer 11

patients with disease recall exposure after learning of similar cases

Question 12

measurement bias

Answer 12

information is gathered in a systemically distorted manner

ex: using a faulty automatic sphygmomanometer to measure BP

Question 13

procedure bias

Answer 13

subjects in different groups are not treated the same

ex: patients in treatment group spend more time in highly specialized hospital units

Question 14

observer-expectancy bias

Answer 14

researcher’s belief in the efficacy of a treatment changes the outcome of that treatment (pygmalion effect)

ex: an observer expecting treatment group to show signs of recovery is more likely to document positive outcomes

Question 15

confounding bias

Answer 15

factor related to both exposure and outcome (but not on causal path) distort effect of exposure on outcome

ex: an uncontrolled study shows an association between drinking coffee and lung cancer, however coffee drinkers also smoke more, which can account for the association

Question 16

lead time bias

Answer 16

early detection is confused with increased survival

Question 17

lag time bias

Answer 17

screening test detects disease with longer latency period, while those with shorter latency period become symptomatic earlier

ex: a slowly progressive cancer is more likely detected by a screening test than a rapidly progressive cancer

Question 18

compare relative risk, relative risk reduction, attributable risk, and absolute risk reduction

Answer 18

relative risk: risk of developing disease

relative risk reduction: the proportion of risk reduction attributable to the intervention as compared to the control

attributable risk: difference in risk between exposed and unexposed groups

absolute risk reduction: difference in risk attributable to intervention as compared to the control

Question 19

phase 1 trial of clinical trial

Answer 19

small number of healthy volunteers or patients with disease of interest

Question 20

phase 2 of clinical trial

Answer 20

moderate number of patients with disease of interest

Question 21

phase 3 of clinical trial

Answer 21

large number of patients randomly assigned to either treatment under investigation or the standard of care (placebo)

Question 22

phase 4 of clinical trial

Answer 22

postmarketing surveillance of patients after treatment is approved

Question 23

with receiving operating characteristic curves (ROC curves), what indicates a test with higher accuracy

Answer 23

higher area under the curve

(a test with 0 accuracy is a straight diagonal line, higher accuracy causes the line to curve upwards)

the highest accuracy causes the curve to form a rectangle shape

Question 24

how to calculate standard error

Answer 24

SE = standard deviation / square root of sample size (n)

Question 25

how to calculate confidence interval

Answer 25

CI of mean = mean +/- (z score for confidence level) x SE

Z score:

• 68%: CI - 1
• 95% CI - 1.96
• 99%: CI - 2.58

Question 26

how does sample size affect power

Answer 26

increased sample size –> increased power