Lectures 1-4

Question 1

Definition of EBM:

Answer 1

• medicine combining the best current research evidence with clinical expertise and patient values.

Question 2

The five outcomes of disease:

Answer 2

1. death
2. disease
3. discomfort
4. disability
5. dissatisfaction

Question 3

Prevalence =

Answer 3

(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”

Question 4

Cumulative incidence:

Answer 4

(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

Question 5

Incidence density =

Answer 5

• the incidence rate in a dynamic, changing population in which people are under study and at risk for varying periods of time.
• “person-years” or “person-days”

Question 6

Incidence equation in steady state:

Answer 6

prevalence / duration

Question 7

Duration equation in steady state:

Answer 7

prevalence / incidence

Question 8

Prevalence equation in steady state:

Answer 8

(incidence) X (average duration)

Question 9

Apparent incidence depends on:

Answer 9

• intensity of effort to identify cases, not just the true underlying incidence.

Question 10

Epidemic:

Answer 10

• an increase in incidence of a disease in a community or region.
• Outbreak is sometimes used to mean a small epidemic in a limited location.
• An epidemic curve is a plot of the distribution of cases over time.

Question 11

Pandemic:

Answer 11

• an epidemic that crosses many international boundaries.

Question 12

Endemic:

Answer 12

• the constant presence of a disease or infectious agent within a given geographic area or population group.

Question 13

Random samples:

Answer 13

• Every person has an equal probability of being sampled

Question 14

Probability sample:

Answer 14

• Every person has a known (but not necessarily equal) probability of being selected.
• Can weight the sample towards some low-frequency groups of interest.

Question 15

“grab” samples:

Answer 15

• convenient
• susceptible to bias

Question 16

alpha =

Answer 16

• 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

Question 17

beta =

Answer 17

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

Question 18

power =

Answer 18

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.

Question 19

Low power is a common reason for what types of errors?

Answer 19

type 2

Question 20

Power can be reduced by:

Answer 20

BLAMSE

1. beta too lax (~0.2)
2. low prevalence of outcome in population
3. alpha too stringent (~ 0.01)
4. multiple comparison adjustments
5. sample size (small)
6. effect size (small)

Question 21

A confidence interval is:

Answer 21

• the range of values you get for repeated/multiple samples
• 95% CI means that 95% of values fall within 2SD

Question 22

2 X 2 tables for hypothesis testing:

(alpha, beta, and power)

Answer 22

Question 23

2 X 2 tables for hypothesis testing:

(type 1 and 2 errors)

Answer 23

Question 24

2 X 2 tables for hypothesis testing:

(false hits and false misses)

Answer 24

Question 25

95% CI equation:

Answer 25

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

• SEM = SD/ √n

Question 26

Standard error of the mean (SEM) eqaution:

Answer 26

SEM = SD/ √n

• SD = standard deviation
• n = sample size

Question 27

In order to be signficant, confidence intervals cannot:

Answer 27

1. cannot overlap / touch
2. cannot include 0 when doing correlations
3. cannot include 1 when relative risk, hazards ratio, odds ratio

Question 28

When to use T-test:

Answer 28

• use when comparing means of 2 groups
• PARAMETRIC

Question 29

Mann-Whitney test:

Answer 29

• non-parametric test similar to t-test
• does not rely on mean or variation

Question 30

Risk can be offset by:

Answer 30

1. Intervention
2. Treatment
3. Prevention
4. Education

Question 31

A risk factor is:

Answer 31

• anything which increases the likelihood that a disease will occur
• can be genetic or environmental

Question 32

The three types of prevention:

Answer 32

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

Question 33

Primary prevention:

Answer 33

• before exposure
• prevent disease occurrence
  
  • e.g. vaccinations

Question 34

Secondary prevention:

Answer 34

• after exposure
• screening early for disease
  
  • e.g. pap smears

Question 35

Tertiary prevention:

Answer 35

• after disease process
• treat
  
  • e.g. chemotherapy

Question 36

When to use ANOVA:

Answer 36

• when comparing means of 3 or more groups

Question 37

Pathogenic triangle:

Answer 37

• host — environment — agent (all are connected in an exposure)

Question 38

Latency:

Answer 38

• Time between exposure and event

Question 39

Null Hypothesis (Ho):

Answer 39

• states that there is no difference

Question 40

Type I error:

Answer 40

• FALSE POSITIVE
  
  • saying there is a difference when there is not.
  • rejecting the null hypothesis when it should be accepted

Question 41

Type II error:

Answer 41

• FALSE NEGATIVE
  
  • saying there is no difference in treatment effects when there is.
  • failing to reject (accepting) the null hypothesis when it should be rejected

Question 42

How to increase the power of a study:

Answer 42

• increase the number of subjects