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USMLE Step 1 > Biostatistics > Flashcards

Biostatistics Flashcards

1
Q

Collects data from a group of people to assess frequency of disease (and related risk factors) at a particular point in time

-asks “What is happening?”

A

Cross-sectional study

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2
Q

A cross-sectional study can show risk factor association with disease, but does not establish

A

Causality

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3
Q

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

  • Looks for prior exposure or risk factor
  • Asks “What happened?”
A

Case-control study

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4
Q

Case-control studies measure

A

Odds ratio

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5
Q

Compares a group with a given exposure or risk factor to a group without such exposure.

-Looks to see if exposure affects the likelihood of disease

A

Cohort study

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6
Q

Asks “Who will develop the disease?

A

Prospective cohort

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7
Q

Asks “Who developed the disease? the exposed or unexposed?”

A

Retrospective cohort

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8
Q

What type of study would say “Patients with COPD had higher odds of a history of smoking than those without COPD?”

A

Case-control Study

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9
Q

What type of study would say “Smokers had a higher risk of developing COPD than nonsmokers?”

A

Cohort Study

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10
Q

Compares the frequency with which both monozygotic or both dizygotic twins develop the same disease

-Measures heritability and influence of environmental factors

A

Twin concordance study

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11
Q

Compares siblings raised by biological vs. adoptive parents

-measures heritability and influence of environmental factors

A

Adoption study

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12
Q

Experimental study involving humans. Compares therapeutic benefits of two or more treatments or of treatment and placebo

-Study quality improves with double blinding and randomization

A

Clinical Trial

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13
Q

Refers to the additional blinding of the researchers analyzing the data

A

Triple-blinding

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14
Q

Requires a small number of healthy volunteers and asseses safety, toxicity, pharmokinetics, and pharmodynamics

A

Phase I trial

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15
Q

Requires a small number of patients with the disease of interest and assesses treatment efficacy, optimal dosing, and adverse effects

A

Phase II trial

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16
Q

Requires a large number of patients randomly assigned either to the treatment under investigation or to the best available treatment (or placebo)

-compares new treatment to current standard of care

A

Phase III trial

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17
Q

Requires post marketing surveillance of pateints after treatment is approved

  • detects rare or long-term adverse effects
  • can result in treatment being withdrawn from market
A

Phase IV trials

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18
Q

Sensitivity and specificity are fixed properties of a test, where as PPV and NPV vary depending on

A

Disease prevalence

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19
Q

Proportion of all people with the disease who test positive, or the probability that when the disease is present, the test is positive

A

Sensitivity

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20
Q

Highly sensitive tests are used for screening in diseases with

A

Low prevalence

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21
Q

Desirable for ruling out disease and indicates a low false-negative rate

A

Highly sensitive test

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22
Q

Proportion of all people without the disease who will test negative for the disease

A

Specificity

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23
Q

Desirable for ruling in a disease and indicates a low false-positive rate

A

Highly specific test

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24
Q

How an we remember what sensitive and specific tests are used for?

A
  1. ) Sensitive: SN-N-OUT

2. ) Specific: SP-P-IN

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25
Q

Used for conformation after a positive screening

A

Highly specific test

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26
Q

Proportion of positive test results that are true positives

A

Positive predictive value (PPV)

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27
Q

Proportion of negative results that are true negatives

A

Negative predictive value (NPV)

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28
Q

High prevalence means what for PPV and NPV?

A

High prevalence = High PPV and Low NPV

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29
Q

Looks at new cases

A

Incidence

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30
Q

Looks at all current cases

A

Prevalence

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31
Q

What is the incidence rate?

A

new cases / # people at risk

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32
Q

What is the prevalence?

A

of existing cases / Total # of people

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33
Q

Prevalence is greater than incidence for

A

Chronic diseases

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34
Q

Odds ratios are typically used in

A

Case-control studies

35
Q

Relative risks are typically used in

A

Cohort studies

36
Q

The difference in risk between exposed and unexposed groups, or the proportion of disease occurences that are attributable to the exposure

A

Attributable risk

37
Q

The proportion of risk reduction attributable to the intervention as compared to a control

A

Relative risk reduction (RRR)

38
Q

What is the formula for Relative risk reduction?

A

1-RR

39
Q

The difference in risk attributable to the intervention as compared to a control

A

Absolute Risk Reduction (ARR)

40
Q

Number of patients who need to be treated for 1 patient to benefit

A

Number needed to treat (NNT)

41
Q

Number of patients who need to be exposed to a risk factor for 1 patient to be harmed

A

Number needed to harm (NNH)

42
Q

The higher the precision, the higher the

A

Statistical power (1-β)

43
Q

Random error decreases the

A

Precision

44
Q

Systematic error decreases the

A

Accuracy

45
Q

Error in assigning subjects to a study group resulting in an unrepresentative sample

-most commonly a sampling bias

A

Selection bias

46
Q

What are three types of selection bias?

A

Berkson bias, healthy worker effect, and non response bias

47
Q

When the study population selected from the hospital is less healthy then the general population

A

Berkson bias

48
Q

When the study population is healthier than the general population

A

Healthy worker effect

49
Q

When the participating subjects differ from nonrespondents in meaningful ways

A

Non-response bias

50
Q

Awareness of disorder alters recall by subjects

-common in retrospective studies

A

Recall bias

51
Q

When patients with a disease recall exposure after learning of similar cases

A

Recall bias

52
Q

When information is gathered in a systematically distorted manner

A

Measurement bias

53
Q

When subjects in different groups are not treated the same

A

Procedure bias

54
Q

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

A

Observer-expectancy bias

55
Q

When a factor is related to both the exposure and the outcome but not on the causal pathway

-occurs when multiple factors distort or confuse effect of exposure on outcome

A

Confounding

56
Q

When early detection is confused with increased survival

A

Lead-time bias

57
Q

What are the three measures of central tendency

A
  1. Mean
  2. Median
  3. Mode
58
Q

What are the measures of dispersion?

A
  1. Range
  2. Variance
  3. Standard deviation
  4. Standard Error
  5. Confidence intervals
59
Q

What is most effected by outliers? Least effected?

A
  1. Most = mean

2. Least = mode

60
Q

How much variability exists from the mean in a set of values

A

Standard deviation

61
Q

An estimate of how much variability exists between the sample mean and the true population mean

A

Standard error of the mean

62
Q

What are three types of non-normal distributions?

A
  1. bi-modal
  2. positive skew
  3. negative skew
63
Q

Suggests two different populations

A

bimodal data

64
Q

What are the characteristics of a positive skew?

A

Mean > median > mode

65
Q

What are the characteristics of a negative skew?

A

Mean

66
Q

Says there is no difference association between the disease and the risk factor

A

Null hypothesis

67
Q

Says there is some association between the disease and the risk factor

A

Alternative hypothesis

68
Q

Stating that there is an effect or difference when non actually exists

A

Type I (α ) error (i.e. false positive)

69
Q

Stating that there is not an effect or difference between the null and alternative hypotheses when one exists

A

Type II (β) error (i.e. false negative)

70
Q

There is less than a 5% chance that the data will show something that does not actually exist if

A

P is less than 0.05

71
Q

The probability of making a type II error

A

β

72
Q

The probability of rejecting the null hypothesis when it is false

A

Power (1-β)

73
Q

Ranges of values within which the true mean of the population is expected to fall, with a specific probability

A

Confidence interval

74
Q

What is the z value for

  1. 95% CI
  2. 99% CI
A
  1. z = 1.96

2. z = 2.58

75
Q

There is no significant difference if the 95% confidence interval for a mean difference between 2 variables includes

A

Zero

76
Q

We do not reject the null hypothesis if the 95% CI for OR or RR includes

A

1

77
Q

If the CI’s between two groups do not overlap than

A

Statistically significant difference exists

78
Q

If the CIs between two groups overlap than

A

No significant difference exists

79
Q

Checks differences between means of 2 groups

A

t-test

80
Q

Checks differences between means of 3 or more groups

A

Analysis of Vasiance (ANOVA)

81
Q

Checks differences between 2 or more percentages or proportions of categorical outcomes (not mean values)

A

Chi-squared

82
Q

Is always between +1 and -1. The closer the absolute value is to 1, the stronger the linear correlation between the two variables

A

Pearson correlation coefficient (r)

83
Q

What is the coefficient of determination?

A

r^2

USMLE Step 1 (2 decks)

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