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Behavioral Science > Epi/Biostats > Flashcards

Epi/Biostats Flashcards

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0
Q

Negative predictive value

A

Chances that a person does not have disease when test is negative.
TN/(TN+FN)

Inversely proportional to pretest probability (and prevalence)

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1
Q

Incidence

A

Looks at new cases

Number of new cases per year / total population at risk (not including those who already have it)

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2
Q

How are prevalence and incidence related?

A

Prevalence = (incidence) x (time)

- This is given a stable population with little migration

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3
Q

How can a population have a stable incidence but a rising prevalence?

A

Improved quality of care means higher survival, so the same number of people get it but fewer die each year.

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4
Q

Number needed to harm

A

Number of pts exposed for 1 pt to be harmed.

NNH = 1/attributable risk

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5
Q

Attributable risk

A

The difference in risk between exposed and unexposed groups. Proportion of disease occurrences that are attributable to exposure.

AR = (event w risk factor / total w risk factor) - (event w no risk factor / total w no risk factor)

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6
Q

Absolute risk reduction

A

Control event rate minus treatment event rate. Difference in risk attributable to intervention, compared to control.

Just subtract the percentages!

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7
Q

Which of the following are affected by disease prevalence: sensitivity, specificity, positive predictive value, negative predictive value.

A

Only PPV and NPV

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8
Q

What kind of bias is loss to follow up, aka attrition bias?

A

This is a form of selection bias. Common when studying diseases with early mortality

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9
Q

Selection bias

A

Bias involved in recruiting and assignment to study group. Includes Berkson bias, attrition bias, and healthy worker/volunteer bias.

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10
Q

Berkson bias

A

A type of selection bias where a study only looks at inpatients

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11
Q

Healthy worker/volunteer bias

A

Selection bias where study populations are healthier than general population

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12
Q

Recall bias

A

Inaccurate recall of past exposure status based on having disease. Common in retrospective studies.

Can be reduced by getting info very soon after exposure.

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13
Q

Measurement bias

A

Information is gathered in a way that distorts it. Hawthorne effect is when people behave differently when being studied.

Reduced by using placebos and blinding

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14
Q

Procedure bias

A

Subjects in different groups are not treated the same

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15
Q

Observer bias

A

Researcher’s beliefs change outcome. Self-fulfilling prophecy. Prevented by blinding investigators

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16
Q

Confounding bias

A

A factor is related to exposure and outcome, but not on the causal pathway.

Pulmonary disease common in coal workers confounded by smoking, which is also more common in coal workers.

Reduce with multiple studies, crossover studies, and matching treatment and control groups

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17
Q

Lead-time bias

A

A screening test diagnoses a disease sooner than it would appear clinically. Falsely increases survival time, seen with improved screening tests.

Reduce by adjusting survival according to severity at diagnosis.

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18
Q

Cohort study

A

Compare a group with a given exposure to one without the exposure. Can be prospective or retrospective. Observational.

Given this exposure, who will develop disease?

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19
Q

Cohort study is good for measuring

A

Relative risk

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20
Q

Case-control study

A

Observational and retrospective. Compares a group with disease and group without disease.

Given disease status, who had exposure?

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21
Q

Case control study is good for measuring:

A

odds ratio

22
Q

Cross sectional study

A

aka prevalence study. A snapshot in time, measures exposure and outcome simultaneously. Good for measuring prevalence. Inexpensive and easy to do.

Note: can show association, but NOT causality

23
Q

Attributable risk percentage (ARP)

A

The excess risk in the exposed population that can be attributed to the risk factor.

ARP = (RR-1)/RR

24
Q

Relative Risk

A

The risk of developing disease in the exposed group divided by risk of developing disease in non-exposed group. Used in cohort studies.

RR = [a/(a+b)] / [c/(c+d)]

25
Q

Odds Ratio

A

Odds that the group with the disease had exposure, divided by odds that group without disease had exposure. Used in case-control studies.

OR = (a/c) / (b/d)

26
Q

Crossover study

A

Subjects randomly assigned to a sequence of treatments given consecutively, with washout in between.

Each subject serves as his/her own control.

27
Q

Relative risk reduction (RRR)

A

Percent reduction in absolute risk between treatment and control.

RRR = [control absolute risk - tx absolute risk] / control absolute risk

RRR = 1-RR

28
Q

Incidence and deaths of cancers in women

A

Breast: 1st and 2nd
Lung: 2nd and 1st
Colon: 3rd and 3rd

29
Q

Some common confounders

A

Gender, smoking, socioeconomic status

30
Q

Confidence interval

A

Range of values in which a specified probability of means of repeated samples is expected to fall.

CI = mean +/- Z(SEM)
For 95%, Z = 1.96
For 99%, Z = 2.58

Remember that SEM = Std dev / sqrt(n)

31
Q

Confidence interval for mean difference between 2 variables includes 0:

A

Null hypothesis is not rejected - no significant difference

32
Q

Confidence interval for mean difference between 2 variables includes 1:

A

Significant difference - null hypothesis is rejected

33
Q

Confidence intervals between two groups overlap/don’t overlap

A

If they overlap, there is no significant difference

If they don’t overlap there is a significant difference

34
Q

95% CI, p=?

A

p=0.05

35
Q

Standard error of the mean and standard deviation

A

Std dev: how much variability exists from mean in a set.

SEM: estimation of how much variability exists between sample mean and true population mean. SEM = std dev / sqrt(n)

36
Q

Mean, mode, median in a positive skewed distribution

A

Asymmetry with longer tail on right

mean > median > mode

37
Q

Mean, mode, median in a negative skewed distribution

A

Asymmetry with longer tail on left

Mean < median < mode

38
Q

What does RR = 1 mean? Greater than 1? Less than 1?

A

RR=1 Null value - no association
>1 exposure is associated with increased disease occurence
<1 exposure associated with decreased disease occurence

39
Q

If 95% CI contains 1.0:

If it does not contain 1.0:

A

Contains 1 = p>0.05

If it does not contain 1, p < 0.05

40
Q

Most effective preventative intervention almost all the time

A

STOP SMOKING

41
Q

In a gaussian curve, percentage that falls within 1, 2, and 3 standard deviations from mean.

A

1: 68% (16 on each side)
2: 95% (2.5 on each side)
3: 99.7% (0.15 on each side)

42
Q

Null Hypothesis

A

No association with disease and risk factor

43
Q

Hypothesis testing: correct result

A

Stating there is a difference when there really is one

Stating that there is not a difference when one doesn’t exist

44
Q

Type 1 error (a)

A

False positive error. Study says there is a difference when there is none. alpha is the probability of making this error.

45
Q

Type 2 (b) error

A

False negative error. Saying there is no difference when there really is one. Related to power (power = 1-b)

46
Q

Power

A

(1-b). Probability of rejecting the null hypothesis when it is false.

47
Q

Things that increase power, decrease b

A

Increased sample size, expected effect size, and precision

48
Q

t-test

A

Check differences between two groups

49
Q

ANOVA

A

Analysis of variance. Check difference between means of 3 or more groups.

50
Q

Chi-square

A

Check difference between 2 or more percentages of categoracal outcomes, not means.

eg compare percentage of people of different ethnic groups with hypertension

51
Q

Primary, secondary, and tertiary disease prevention

A

Primary: prevent occurrence (vaccination)
Secondary: screen early for disease
Tertiary: treatment

52
Q

Correlation coefficient (r)

A

Measure of strength and direction of linear relationship between two variables. Between -1 and 1, closer to 1 = stronger correlation

Ofter reported as r^2, coefficient of determination

Behavioral Science (2 decks)

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