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Flashcards in Behavioral Science/Stats Deck (57)
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1

Study type that establishes prevalence

Cross-sectional

2

Case-control study measure?

Odds ratio (What was "odd" about their history?)

3

Case-control study design?

People with disease v. people without disease. Looking for prior exposure or a RF

4

Cohort study measure?

Relative risk (Increased risk for disease)

5

Cohort study design?

People with exposure v. people without exposure

6

Twin concordance study design?

Frequency of disease between twins

7

Pharm phase I asks?

Is it safe? Safety, toxicity, pharmacokinetics

8

Pharm phase II asks?

Does it work? Efficacy, dosing, AE's

9

Pharm phase III asks?

Is it as good or better?

10

Pharm phase IV asks?

Can it stay? Post-marketing surveillance

11

Sensitivity =

TP / (TP + FN) = Pr (T+|D+)

12

Specificity =

TN / (TN + FP) = Pr (T-|D-)

13

PPV =

Pr (D+|T+) = TP / (TP + FP)

14

NPV =

Pr (D-|T-) = TN / (TN + FN)

15

Prevalence is related to incidence how?

Prevalence is approx incidence rate x avg disease duration

16

Incidence rate =

# of new cases in specified time period / population at risk during same time period

17

Odds and Probability related how?

Odds = Pr / (1-Pr) ; Pr = O / (1 + O)

18

What parameters are only dependent on the test itself?

Sensitivity, specificity, likelihood ratio

19

Odds ratio and relative risk?

OR = (a/b) / (c/d) = ad/bc; RR = [a / (a+b)] / [c (c+d)] 

20

RRR =

1 - RR

21

Difference between effect modification and confounding bias?

Effect modification is something to be studied; Present when effect of the main exposure is modified by presence of another variable.

22

Power

= 1 - Beta; Beta = Pr(type II error) = Pr of rejecting null hypothesis when it is truly false = Pr difference when there IS one = Maximize for clinical trials!

23

Type 1 v. type 2 error

1st and foremost, making something out to be when there isn't anything. (Rejecting H0 when it is true). 2nd, saying nothing when there is (Fail to reject, when H0 is false)

24

Berkson's bias

Selection bias - selecting hospitalized patients as the control

25

Hawthorne effect

The tendency for a study population to affect an outcome due to the knowledge of being study. e.g. behavioral studies

26

Pygmalion effect

Researcher's beliefs in efficacy of treatment potentially affecting the outcome

27

Number needed to harm?

1/AR

28

Precision vs. accuracy?

Accuracy has to do with close to REAL number. Precision has to do with ability to REPRODUCE a result

29

Lead-time bias vs. recall bias?

Lead-time bias occurs when the early detection of a condition is interpreted as increased survival. Recall bias is when awareness of the condition leads to increased recall (e.g. retrospective studies)

30

Observer-expectancy bias?

The Pygmalion effect - researcher's belief in efficacy changes outcome of treatment