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ABSITE > Statistics > Flashcards

Statistics Flashcards

1
Q

Hypothesis-generating study designs

A
  • observational
  • survey
  • case report/series
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2
Q

Hypothesis testing study designs

A 
Experimental
-randomized
Observational
-cross-sectional
-case-control
-cohort
-other
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3
Q

Meta-analysis

A

Pooled data of observational studies

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4
Q

Cross-sectional

A

Single point in time

Temporal trends

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5
Q

Cohort

A

Onset of observation with the exposure

Estimates incidence/rate of exposures and outcomes

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6
Q

Case-control

A

Compare the frequency of exposure between patients who have/have not experienced outcome of interest
Search for risk factors

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7
Q

Case-report

A

Highlight an unusual procedure or event

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8
Q

Continuous variable

A

Can take on any number of values within a specified range of possibilities
Ex: Age, length of stay

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9
Q

Categorical variables

A

Have discrete values
Ex: binary (sex), ordinal (ordered categorical variables such as cancer stage), nominal (unordered categorical variables such as race)

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10
Q

Time-to-event variables

A

Two variables: continuous variable that measures the time interval from an established start point (ex: date of diagnosis) to failure event (ex: death) and a binary variable which indicates whether the failure event occurred
Ex: long-term survival

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11
Q

Measurement of continuous variables

A

Mean (for normally distributed data)

Median (for skewed data)

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12
Q

Descriptive statistics for continuous variables

A

Unpaired t-test
Paired t-test
ANOVA

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13
Q

Multivariate regression model for continuous variables

A

Linear

Need 10-15 observations per variable

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14
Q

Measurement of categorical variables

A

Proportion

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15
Q

Descriptive statistics for categorical variables

A

Chi-squared test

Mantel-Haenszel odds

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16
Q

Multivariate regression model for categorical variables

A

Logistic

Need at least 10 events and equivalent number of non events per variable

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17
Q

Measurement for time-to-event variables

A

Kaplan-Meier

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18
Q

Descriptive statistics for time-to-event variables

A

Log-rank test

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19
Q

Multivariate regression model for time-to-event variables

A

Cox hazard

20
Q

Unpaired t-test

A

Compare 2 independent groups with continuous outcome variables

21
Q

Paired t-test

A

Compare 2 dependent groups with continuous outcome variables

22
Q

ANOVA

A

Compare more than 2 groups with continuous outcome variables

23
Q

Chi-squared

A

Compare distributions of 2 or more groups with categorical outcome variables (sex, mortality)

24
Q

Fisher exact

A

Compare distributions of 2 or more groups with categorical outcome variables with small sample size

25
Q

Log-rank test

A

Compare 2 groups with time-to-event outcome variables

26
Q

Alpha (type 1) error

A

Observe a difference when one does not exist

False-positive

27
Q

Beta (type 2) error

A

No difference is observed when when one actually exists
False-negative
Insufficient power to detect true differences, directly related to sample size

28
Q

Confidence interval (CI)

A

Difference between groups are provided as estimated ratio or absolute difference
Odds ratio/relative risk ratio: if includes 1, no statistical difference
Absolute difference/relative risk: if includes 0, no statistical difference

29
Q

Wide confidence interval

A

Lack of precision

30
Q

Tight confidence interval

A

Minimal uncertainty

31
Q

PICOT framework to summarize research question

A 
Population in the study
Independent variables (intervention/exposure, covariates)
Comparator group, if applicable
Outcome, end point (dependent variable)
Time frame of outcomes assessment
32
Q

Confounder

A

Measured or unmeasured variable associated with the exposure of interest and associated with the outcome

33
Q

Generalizability

A

Ability to take research findings and apply them to clinical practice
-is this reproducible in a clinical setting? In my patient population?

34
Q

Bradford Hill criteria for causality

A

Strength of association
Consistency: do all or most studies indicate that A causes B?
Specificity
Temporality: if A causes B, then A must precede B. Just because A precedes B, A does not necessarily cause B.
Biological gradient (dose-response): the more a person is exposed to A, the more likely they will get disease B
Plausibility: there should be a reasonable biological mechanism to explain why A causes B
Coherence: should make sense with what we already know about A and B
Experiment
Analogy

35
Q

Wilcoxon test

A

Used to study the relationship between an ordinal variable such as satisfaction scores, in 2 samples (before and after treatment)

36
Q

Kruskal-Wallis test

A

Used for ordinal data from 3 or more groups

37
Q

Relative Risk Reduction formula

A

(Incidence in unexposed - incidence in exposed) / incidence in unexposed

38
Q

Risk ratio

A

Used in cohort studies and RCT
data is collected prospectively
Calculate incidences and incidence rates and compare these as risk ratios

39
Q

Odds ratios

A

Used in case-control studies
Only prevalence rates can be calculated
Also used to summarize data from cohort studies and RCTs

40
Q

True or False: PPV and NPV vary depending on the prevalence of disease

A

True
As disease prevalence increases, more people actually have the disease (increase in TP) and fewer people do not have the disease (decrease in TN)
Increase in TP signifies a higher PPV. Decrease in TN signifies a lower NPV

41
Q

True or False: sensitivity and specificity vary depending on prevalence of a disease

A

False

42
Q

Student’s t-test

A

Test for normally distributed continuous variables

43
Q

Mann-whitney test

A

Used for non-normally distributed continuous variables

44
Q

Absolute Risk Reduction

A

Difference in rates between the control group and the experimental group
Incidence in unexposed - incidence in exposed

45
Q

Relative Risk

A

Computes the possibility of disease when exposed to a certain agent relative to the risk of disease when not exposed to the same agent
Incidence in exposed / incidence in unexposed

46
Q

Odds ratio

A

Measure of association between an exposure and an outcome

Diseased in exposed / healthy in exposed) / (diseased in not exposed / healthy in not exposed

47
Q

Hazard ratio

A

Hazard rate of one exposure variable relative to the hazard rate of another exposure variable

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