STATS Flashcards

1
Q

Equation for positive predictive value:

A

TP / TP + FP

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2
Q

Equation for negative predictive value:

A

TN / TN + FN

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3
Q

Equation for sensitivity:

A

TP / TP + FN

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4
Q

Equation for specificity:

A

TN / TN + FP

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5
Q

Equation for number needed to treat:

A

1 / absolute risk reduction

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6
Q

What is precision?

A

A tests ability to produce the same measurements with repeated tests.

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7
Q

What is sensitivity?

A

SNOUT: high sensitivity, rules something out.
Likelihood of a positive result being a true positive.

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8
Q

Equation for absolute risk reduction:

A

ARR = Experiment risk - control risk

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9
Q

Equation for power and what it’s used for:

A

1 / probability of a type II error

Establishes how large the sample size needs to be.

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10
Q

Type I error:

A

Rejecting a true null hypothesis

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11
Q

Standard error of the mean:

A

Standard deviation / square root of n

How accurate the calculated sample mean is compared to the true population mean

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12
Q

Standard deviation explained:

A

1 SD away from the mean on either side of a normal distribution = 68% of cases.
2 SD = 95%
3 SD = 99%

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13
Q

Main bias in case-control studies:

A

Recall bias

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14
Q

What graph is done to represent if there is publication bias?

A

Funnel plot

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15
Q

Definition of bias:

A

Systematic differences between the data and reality of the population

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16
Q

Incidence =

A

Number of new cases per population in a given time period

17
Q

Prevalence =

A

Total number of cases per population in a given time period

In chronic diseases, prevalence&raquo_space; incidence.
In acute diseases, prevalence ~ = incidence

18
Q

Tests use to determine differences between a) 2 and b) >2 groups in parametric data:

A

T-Test

ANOVA

19
Q

What is the chi-squared test used for?

A

To see if there is a significant difference between 2 groups of categorical data.
Compares the observed data with data that would be expected if the null hypothesis were true.

20
Q

Which graph shows the results of meta-analysis?

A

Forest plot

21
Q

What does the p-value represent?

A

The probability of obtaining a result by chance at least as extreme as the one actually observed.

Small p-value = better, as less likely that the result has come about by chance, and is actually due to the intervention in the study.

22
Q

What does meta-analysis do to the power and the p-value of studies?

A

Increases the power.

Decreases the p-value.

23
Q

Which kind of study is observational and prospective, and what is the usual outcome measure?

A

Cohort study

Relative risk

24
Q

What kind of study is observational and retrospective, and what is the usual outcome measure?

A

Case-control study

Odds ratio = odds in exposed group / odds in unexposed group

24
Calculating odds:
Odds: probability that x happens / probability that x doesn't happen Divide by number of times x doesn't happen, NOT the total number of participants
25