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Step One R&M > Biostats definitions and equations > Flashcards

Biostats definitions and equations Flashcards

1
Q

Compares people with DISEASE to people without disease

A

Case-control study

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1
Q

Patients serve as their own control

A

Crossover study (reduced confounding bias)

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2
Q

CI between two groups overlaps

A

No difference, fail to reject HO

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3
Q

Hawthorne effect

A

Groups who know they’re being studied behave differently (measurement bias)

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4
Q

PPV =

A

TP/TP+FP

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5
Q

Measured by a cross-sectional study

A

Prevalence

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5
Q

1 standard deviation = __%

A

68

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6
Q

Attributable risk

A

Difference in risk between exposed and unexposed group

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6
Q

Mean > median > mode

A

Positively skewed

(Tail to the right)

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7
Q

Mean < median < mode

A

Negatively skewed

(Tail to the left)

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7
Q

Incorrectly rejecting the null hypothesis

A

Type I error

(Saying there is a difference when there isn’t)

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8
Q

Information is gathered in a way that distorts it

A

Measurement bias

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10
Q

Collects data from a group of people to asses disease prevalence

A

Cross-sectional study

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11
Q

Which bias? Patients in treatment group spend more time in in-patient treatment

A

Procedure bias

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11
Q

Mean=median=mode

A

Normal distribution

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12
Q

AR =

A

% risk in exposed group - % risk in unexposed group

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13
Q

NNT =

A

1/risk difference

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14
Q

Specificity =

A

TN/TN+FP

1 - false positive rate

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15
Q

Increases with increasing prevalence

A

PPV

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16
Q

3 standard deviations = ___%

A

99.7

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16
Q

Coefficient of correlation =

A

r2

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18
Q

Nonrandom assignment to participate in a study group

A

Selection bias

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18
Q

95% CI includes 0

A

HO not rejected

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19
Q

RRR =

A

1 - RR

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20
Q

Berkson bias

A

Study looking only at inpatients (a selection bias)

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21
Q

Two means

A

T-test

22
Q

Ways to increase power and reduce ß

A

Increase sample size

Increase expected effect size

Increase precision of measurement

23
Q

Subjects in different groups are not treated the same

A

Procedure bias

24
Q

ß

A

Probability of making a type II error

(Failing to reject the null hypothesis)

25
Q

Which bias? Study over effectiveness of CRC screening concludes that their screening method leads to increased survival

A

Lead-time bias

26
Q

Berkson bias

Loss to follow-up

Healthy worker and volunteer biases

A

Selection bias

27
Q

Power =

A

1 - ß

(ß = type II error)

28
Q

Alpha

A

Probability of making a type I error

(Falsely rejecting the null hypothesis)

29
Q

Failing to reject the null hypothesis

A

Type II error

(Stating there isn’t a difference when there is one)

30
Q

RR =

A

Incidence in exposed group/incidence in non-exposed

a/(a+b) / c/(c+d)

30
Q

SEM =

A

σ/√n

32
Q

Which bias? Researcher expects those receiving drug to show more signs of improvement, so he documents those signs in the treatment group more frequently than the placebo group

A

Observer-expectancy bias

33
Q

Which bias? Coal miners more likely to have lung disease but also more likely to smoke

A

Confounding bias

34
Q

Z of 95% CI? 99% CI?

A

95% CI Z = 2

99% CI Z = 2.5

35
Q

Categorical differences

A

Chi-square

(“Chi-tegorical”)

37
Q

Early detection is confused with increased survival

A

Lead-time bias

38
Q

Relative risk reduction

A

Proportion of disease reduction attributable to intervention compared to control

39
Q

Decreases with increasing prevalence

A

NPV

40
Q

Hawthorne effect is an example of:

A

Measurement bias

41
Q

Bias reduced via randomization and ensuring the right comparison group

A

Selection bias

42
Q

3+ means

A

ANOVA

(Remember: ANOVA = 3 words)

43
Q

Bias reduced via multiple studies, crossover studies, and matching

A

Confounding bias

45
Q
A
46
Q

CI =

A

[mean - Z*SEM] to [mean + Z*SEM]

47
Q

CI between two groups doesn’t overlap

A

Difference exists, reject HO

49
Q

OR =

A

ad/bc

51
Q

Don’t change if sample size increases

A

Specificity and sensitivity

52
Q

95% CI includes 1

A

Reject H0

53
Q

Sensitivty =

A

TP/TP+FN

1 - false negative rate

54
Q

Measured by a cohort study

A

RR

55
Q

Bias reduced via “back-end” survival (measuring survival based on severity of disease at diagnosis)

A

Lead-time bias

56
Q

2 standard deviations = __%

A

95

57
Q

Prevalence =

A

Incidence x disease duration

(TP + FN)/(TP+TN+FP+FN)

(a+c)/(a+b+c+d)

58
Q

NPV =

A

TN/TN+FN

59
Q

Bias reduced via placebo and blinding

A

Measurement bias (makes sure participants and researchers don’t change their behavior)

60
Q

A factor is related to both exposure and outcome, but not on the causal pathway, so it distorts the effect of the exposure on the outcome

A

Confounding bias

61
Q

Compares people with an EXPOSURE to those without to see if exposure increases likelihood of a disease

A

Cohort study

63
Q

Increases with decreasing cut-off value of a test

A

Sensitivity

NPV

64
Q

Measured by a case-control study

A

OR

Step One R&M (38 decks)

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