# EBM Tables and Equations Flashcards

1
Q

Prevalence =

A

(total #sick)/(total population)

• how many people are sick
• a single time point
• Prevalence can be used to estimate the likelihood of a diagnosis before any “tests”
2
Q

Cumulative incidence:

A

(new cases)/(total population at risk at study start)

• how many people are getting sick (NEW CASES)
• incidence is a rate, it happens over a time interval
3
Q

Incidence equation in steady state:

A

prevalence / duration

4
Q

Duration equation in steady state:

A

prevalence / incidence

5
Q

Prevalence equation in steady state:

A

(incidence) X (average duration)

6
Q

alpha =

A
• the probability you’ll make a false hit.
• Arbitrarily, p = 0.05
• false hit = type 1 error
• 5% of the time, we’ll make an error
7
Q

beta =

A
• probability you won’t find a difference when one actually exists (false miss)
• false miss = type 2 error
• probability of missing a reality
8
Q

power =

A

1 - beta

• power of study to pick up a study when it actually does exist
• Low power is a common reason for type II errors.
9
Q

2 X 2 tables for hypothesis testing:

(alpha, beta, and power)

A
10
Q

2 X 2 tables for hypothesis testing:

(type 1 and 2 errors)

A
11
Q

2 X 2 tables for hypothesis testing:

(false hits and false misses)

A
12
Q

95% CI equation:

A

95% CI = mean +/- 1.96(SEM)

• SEM = SD/ √n
13
Q

Standard error of the mean (SEM) eqaution:

A

SEM = SD/ √n

• SD = standard deviation
• n = sample size
14
Q

The three types of prevention:

A
1. Primary: before exposure (PREVENT)
2. Secondary: after exposure (SCREEN)
3. Tertiary: after disease process occurs (TREAT)
15
Q

Standard deviation:

+/- 3SD contains –% of observations

A

99.7%

16
Q

Standard deviation:

+/- 1SD contains –% of observations

A

68%

17
Q

Standard deviation:

+/- 2SD contains –% of observations

A

95%

18
Q

The three types of variation:

A
• Overall variation:
• measurement variation + biological variation
• Measurement variation:
• instrument variation + observer variation
• Biological variation:
• intra-individual and inter-individual
19
Q

The dependent variable is on what axis?

A

Y-axis

20
Q

The independent variable is on what axis?

A

X-axis

21
Q

Regression r-value close to 0:

A

no association

22
Q

Regression r-value close to 1:

A

strong association

23
Q

Regression r-squared value tells you:

A
• the amount of variation in Y that is contributed by variation in X.
24
Q

Three ways you can control for outliers:

A
1. using non-parametric test
2. dropping the outlier(s)
3. log transformation
25
Q

Variance =

A

measure of the spread/dispersion of values around the mean.

26
Q

Standard deviation =

A

√v; (v = variance)

• decreases as sample size increases
27
Q

Standard error of the mean (SEM) =

A

SD/ √n

28
Q

Equation for 95% CI:

A

95% CI = mean +/- 1.96(SD/ √n)

• SD = standard deviation
• n = sample size
29
Q

For correlation analyses, the confidence interval cannot contain:

A

0

0 = no correlation

30
Q

For relative risk, hazard ratios, and odds ratios, the confidence interval cannot contain:

A

1

31
Q

Sensitivity equation and table:

A

TP/(TP+FN)

SNOUT

32
Q

Specificity equation and table:

A

TN/(TN+FP)

SPIN

33
Q

Positive predictive value equation and table:

A

TP/(TP+FP)

34
Q

Negative predictive value equation and table:

A

TN(TN+FN)

35
Q

False positive rate =

A

1 - specificity

36
Q

Positive Likelihood Ratio equation:

A

LR+ = Sn / (1-Sp)

37
Q

Negative Likelihood Ratio equation:

A

LR- = (1-Sn) / Sp

38
Q

Odds ratio definition and table:

A
• retrospective
• start with people who have disease, and go backwards to find risk factor
39
Q

The probability of two mutually exclusive events, A or B, occurring =

A

(probability A) + (probability B)

40
Q

Relative risk definition and table:

A
• prospective; follow
• start with the risk factor, follow them over time, see how many people get disease
• everyone starts with no disease
41
Q

Probability:

A
• a proportion in which the frequency of both events are in the denominator:

A/(A+B)

42
Q

The probability of two independent events, A and B, occurring together =

A

(probability A) X (probability B)

43
Q

Absolute risk definition and table:

A
• attributable risk
• a difference of relative risks
• how much of getting the disease is attributable to having the risk factor
44
Q

Number needed to treat (NNT) equation and table:

A
• takes everyone into account
• NNT = 1/ARR
45
Q

Absolute risk reduction equation and table:

A
46
Q

Number Needed to Harm (NNH) equation:

A

1/AR