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BCACP > Stats/Primary Literature > Flashcards

Stats/Primary Literature Flashcards

1
Q

How can you overcome random error?

A

Increase sample size

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2
Q

What type of trial is impacted the most by selection bias?

A

Case-control study

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3
Q

How can selection bias be reduced in observational studies?

A

Propensity score matching

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4
Q

What are disadvantages of case report/case series?

A

-Difficult to generalize results
-Report may not truly be characteristic of the disease
-Does not determine causality or association between exposure + outcome

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4
Q

Case Report/Case Series

A

Describes experience of a single patient or small group of patients with an unusual or rare disease or symptoms

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5
Q

Cross-Sectional Study/Survey

A

Identify the prevalence or characteristics of a condition in a group of individuals and evaluate associations

Snapshot of a population at one point in time

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6
Q

What are disadvantages of cross-sectional study/survey?

A

-Low response rates
-Responding population may be biased
-Does not usually target acute, rapidly fatal, or rare diseases
-Cannot establish temporal or causal relationships

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7
Q

Case-Control Study

A

Provides an efficient means to determine the association (or exposure) between the risk factor and the outcome of interest

Retrospective

Cannot determine the actual risk of the outcome (RR) but can determine an estimate risk (OR)

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8
Q

What are disadvantages of case-control study?

A

-Can have poor data quality
-Matching is often flawed
-Indirect measurement of risk
-Susceptible to bias or confounding
-Temporal relationship is not always known

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9
Q

Cohort Study

A

Healthy subjects are followed over time to try to correlate exposure (or risk factors) and disease occurrence

Identifies the relationship between exposure and outcome

Strongest design to establish cause-and-effect relationship for risk

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10
Q

What are disadvantages of cohort study?

A

-Only risks evaluated at baseline can be used
-Cannot investigate a rare disease
-Take a long time to complete

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11
Q

What does prevalence measure?

A

Occurrence of new and existing cases of a disease (or event) at a specified point or period in time

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12
Q

What does incidence measure?

A

Occurrence of new cases of a disease (or event) during a time interval

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13
Q

When is an OR or RR considered not statistically significant?

A

When 95% CI includes 1.0

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14
Q

Randomized Controlled Trial

A

Subjects are randomly assigned to intervention or control group

Gold standard for study interventions and determining causal relationships

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15
Q

When would a crossover RCT be appropriate?

A

When chronic or highly variable diseases (ex: migraines) are being evaluated

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16
Q

What are disadvantages of RCT?

A

-Time-consuming and expensive
-Adherence to study protocol can be poor
-Incomplete follow-up from subjects
-Guidelines may have changed since the initiation of trial
-Subjects may differ from the population of interest

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17
Q

Superiority Trial

A

Designed to detect a difference between experimental treatments

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18
Q

Equivalence Trial

A

Designed to confirm the absence of a meaningful difference between treatments; neither better nor worse (both directions)

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19
Q

Non-Inferiority Trial

A

Designed to investigate weather a treatment is not clinically worse (not less effective) than an existing treatment

Usually requires larger sample sizes

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20
Q

Intention-to-Treat

A

Includes everyone in the trial who was initially randomized regardless of treatment adherence or dropping out

Similar to routine clinical practice

21
Q

Per-Protocol

A

Only evaluates those who completed the trial and adhered to the protocol

22
Q

Cost-Minimization Analysis (CMA)

A

-Differences in cost among comparable therapies are evaluated
-Only useful to compare therapies that have similar outcomes (no outcomes measured)
-Primary focus is $$$

23
Q

Cost-Effectiveness Analysis (CEA)

A

-Outcome: clinical units or cost per unit health outcome (ex: years of life saves, number of symptom-free days, blood glucose)
-Useful to measure the cost impact when health outcomes are improved

24
Q

Cost-Utility Analysis (CUA)

A

-Assigns utility weights to outcomes so that the impact can be measured in relation to the cost ex: quality-adjusted life-years)
-Compares outcomes related to mortality when mortality may not be the most important outcome

25
Q

Cost-Benefit Analysis (CBA)

A

-Monetary value is placed on both therapy costs and beneficial health outcomes
-Allow analysis of both the cost of treatment and the costs saves with beneficial outcome

26
Q

What should not be reported with ordinal data?

A

Mean + SD

27
Q

What type of data would it be appropriate to use mean?

A

Continuous and normally distributed (parametric)

28
Q

What type of data would it be appropriate to use SD?

A

Continuous and normally distributed (parametric)

29
Q

What type of data would it be appropriate to use median?

A

Ordinal and continuous (including non-parametric)

30
Q

What type of data would it be appropriate to use mode?

A

Nominal, ordinal, and continuous

31
Q

What is the relationship between mean and median in normally distributed data?

A

They will be roughly the same

32
Q

What does a 95% CI mean?

A

There is a 95% change that the range includes the true population value

33
Q

When is a CI for continuous variables not statistically significant?

A

When it contains 0

34
Q

What is the null hypothesis?

A

No difference between groups being compared

35
Q

What is the alternative hypothesis?

A

There is a difference between groups being compared

36
Q

What is a Type I Error?

A

Concluding there is a difference when there is truly no difference (falsely rejecting the null hypothesis)

37
Q

What is a Type II Error?

A

Concluding there is no difference when one truly does exist (falsely accepting the null hypothesis)

38
Q

Test used for: non-parametric, nominal data w/ 2 independent groups

A

Chi-squared OR Fischer exact test

39
Q

Test used for: non-parametric, nominal data w/ 3+ independent groups

A

Chi-squared OR Fischer exact test

40
Q

Test used for: non-parametric, nominal data w/ 2 dependent groups

A

McNemar test

41
Q

Test used for: non-parametric, nominal data w/ 3+ dependent groups

A

Cochran Q test OR Mantel-Haenszel test

42
Q

Test used for: non-parametric, ordinal data w/ 2 independent groups

A

Mann-Whitney U test OR Wilcoxon rank sum test

43
Q

Test used for: non-parametric, ordinal data w/ 3+ independent groups

A

Kruskal-Wallis test

44
Q

Test used for: non-parametric, ordinal data w/ 2 dependent groups

A

Wilcoxan signed-rank test

45
Q

Test used for: non-parametric, ordinal data w/ 3+ dependent groups

A

Friedman ANOVA

46
Q

Test used for: parametric, continuous data w/ 2 independent groups

A

Student t-test

47
Q

Test used for: parametric, continuous data w/ 3+ independent groups

A

ANOVA

48
Q

Test used for: parametric, continuous data w/ 2 dependent groups

A

Paired t-test

49
Q

Test used for: parametric, continuous data w/ 3+ dependent groups

A

ANOVA

BCACP (20 decks)

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