Block 6

Question 1

T/F: Measures of association take into account random error

Answer 1

False

Question 2

Statistical inference

Answer 2

The process of drawing conclusions about a population based on data from a sample of that population.
It allows us to deal with random error.

Question 3

What allows us to deal with random error

Answer 3

Statistical inference.

Question 4

Two methods of statistical inference in analytical epidemiology

Answer 4

1) Interval estimation (confidence intervals)
2) Hypothesis testing

Question 5

Interval estimation

Answer 5

95% confidence intervals can be calculated for measures of association

Question 6

Width of the 95% confidence interval is an indication of ____

Answer 6

the precision of the estimate

Question 7

The [narrower or wider] the confidence interval, the more precise the estimate

Answer 7

Narrower

Question 8

3 steps of hypothesis testing

Answer 8

1) Specify a “null” and an “alternative” hypothesis
2) Compare the results that were expected under the null hypothesis with the actual observed results (this is done with a statistical test)
3) Make a decision (this decision is based on the p-value of the statistical test)

Question 9

Null hypothesis (H0)

Answer 9

No association between exposure and disease

Question 10

Alternative hypothesis (HA)

Answer 10

There is an association between exposure and disease

Question 11

Ecological Study Pros and Cons

Answer 11

Pros: Can be done quickly and inexpensively (often use existing data)
Cons: ‘Ecologic fallacy’ - relationships observed at the population level may not hold true at the individual level

Question 12

Cross sectional study Pros and Cons

Answer 12

Pros: Fast, relatively cheap
Cons: Because presence/absence of exposure and disease are assessed at the same time in subjects, it is often not possible to determine which came first: exposure or disease?.
Identifies on prevalent (existing cases) – we might be measuring the association of the exposure with the duration of disease, and not the risk of disease.

Question 13

Prevalence is a function of ____ and ____

Answer 13

Incidence and duration of disease

Question 14

Prospective cohort study Pros (4) and Cons (5)

Answer 14

Pros:
1) Exposure is known to precede the outcome
2) Allow calculation of incidence (risk)
3) Facilitate study of rare exposures (actively recruit subjects with the exposure)
4) Can look at associations with multiple outcomes in the same study

Cons:
1) May have to follow large numbers of subjects for a long time
2) Can be very expensive and time consuming
3) Not good for rare disease
4) Not good for disease with a long latency
5) Differential loss to follow up can introduce bias

Question 15

Retrospective cohort study Pros (5) and Cons (4)

Answer 15

Pros:
1) Can be done over a short time (don’t have to wait for disease to occur)
2) Generally less expensive than a prospective study
3) Allow calculation of incidence (risk)
4) Facilitate study of rare exposures (actively recruit subjects with the exposure)
5) Can look at association with multiple outcomes in the same study

Cons:
1) Temporal relationship between exposure and outcome is sometimes hard to establish (did exposure happen before outcome?)
2) Not good for rare diseases
3) Differential loss to follow up can introduce bias
4) Requires access to good medical records

Question 16

Case control study pros (4) and cons (4)

Answer 16

Pros:
1) Can be done over a short time (disease has already occurred)
2) Relatively inexpensive
3) Facilitate study of rare diseases (actively recruit subjects with the disease)
4) Can look at associations with multiple exposures in the same study
Cons:
1) Selection of appropriate controls is essential (and often difficult)
2) Temporal relationship between exposure and outcome is sometimes hard to establish (did exposure happen before outcome?)
3) Not good for rare exposures
4) Depends upon accurate assessment of exposures that happened in the past (recall bias)

Question 17

Randomized control trial pros (3) and cons (4)

Answer 17

Pros:
1) Well-controlled studies are essentially free of bias and confounding (random allocation, blind or double-blind)
2) Exposure is known to precede the outcome
3) Allow calculation of incidence (risk)
Cons
1) Expensive and very narrow in scope
2) Not always ethical to randomly allocate individuals to treatment
3) Not good for diseases with a long latency
4) Different loss to follow up can introduce bias

Question 18

Two potential source of error in analytical studies

Answer 18

1) Random error
2) Systematic error

Question 19

Random error (3)

Answer 19

1) Random error is the divergence, due to sampling variation, of the measure of association in the sample from the true measure of association in the population
2) Does not bias a study. A study with a lot of random error may be wrong but we don’t call it biased
3) Statistical inference deals with random error

Question 20

Systematic error (4)

Answer 20

1) Error that is inherent to the study method being used, which would result in a predictable and repeatable error if the study were repeated using the same method
2) Not caused by chance
3) Biases a study
4) No formal method to deal with systematic error

Question 21

T/F: there is no formal method to deal with systematic error

Answer 21

True

Question 22

T/F: systematic error does not bias a study

Answer 22

False, systematic error does bias a study

Question 23

Validity

Answer 23

Refers to the absence of systematic error in a study result

Question 24

A valid measure of association

Answer 24

A valid measure of association will have the same value as the true measure in the source population, except for error due to random variation

Question 25

Bias

Answer 25

The extent to which a measure of association from a study differs from the true measure of association in the source population, due to systematic error. Systematic error causes bias. Bias affect validity.

Question 26

T/F: Bias affects validity

Answer 26

True

Question 27

Study population

Answer 27

Subjects in the study
Selected from a source population
The ‘n’ of the study is the number of subjects in the study population

Question 28

Source population

Answer 28

Population from which the subjects were drawn

Question 29

Target population

Answer 29

Population to which we may want to generalize our results

Question 30

Internal validity

Answer 30

Ability to make correct inferences about the association of interest in the source population (based on the observations in the study population)

Question 31

External validity

Answer 31

Ability to make correct inferences about the association of interest in populations beyond the source population

Question 32

Which is more important? Internal validity or external validity

Answer 32

Internal validity

Question 33

Three major types of bias

Answer 33

1) Selection bias
2) Misclassification bias (=information bias)
3) Confounding bias

Question 34

Selection bias

Answer 34

Due to factors that affect the selection of study subjects, their participation in the study and/or their completion of the study.
It occurs when the measure of association for the individuals who were selected for, participated in, and completed the study is different from the true measure of association we would have obtained had we done the study on the entire source population

Question 35

Misclassification (information) bias

Answer 35

Due to factors that affect the accuracy of information on the exposure and outcome
Results in incorrect classification of exposure or outcome status:
-Subjects with no disease are classified as diseased (and vice versa)
-Subjects with no exposure are classified as exposed (and vice versa)

Question 36

Confounding

Answer 36

A distortion of the underlying relationship between an exposure and an outcome by a third factor
-The third factor influences both the exposure and the outcome, distorting the measure of association
-The distortion can be large and lead to overestimation or underestimation of an association; it can even change the apparent direction of an association

Question 37

Reducing confounding variables BEFORE the study starts

Answer 37

• Match the study (esp in case-control studies): select cases and controls so that the confounding factor is equally represented in both groups
• Restriction: do not enroll any animals that have the confounding factor
• Randomization: will reduce confounding

Question 38

Reducing confounding variables AFTER the study has been completed (if you realize there is a confounding variable)

Answer 38

-Deal with the confounding factor in the analysis by stratifying
-Stratify: partition the results based on the confounding factor
(ie: if sex is the confounder, split the data into males and females and do the analysis on each group)
(ie: if practice type is the confounder, split the data into small animal and food animal and do the analysis on each group)