1. Presentation, data and programs at:
Research designs
Hein Stigum
Presentation, data and programs at:
Nov-18
H.S.

2. Designs Aims Designs Disease occurrence Exposure-Disease association
Cross-sectional studies
Cohort studies
Case-control studies
Case-Cohort
Nested Case Control
Traditional Case Control
Aim: find association
Designs: unit of analysis, time for finding exposure and disease
Nov-18
H.S.

3. The 2 by 2 table
Nov-18
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4. True or false? It takes 2 to tango It takes 3 chords to play the blues
It takes 4 numbers to be an epidemiologist
Nov-18
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5. The 2 by 2 table The information is in the contrasts
The lowest number sets the precision
=.13
Add 100 to 100 cell: =.125
Add 10 to 10 cell: =.08
To increase power:
In a cohort study: oversample unexposed
In a case control study: oversample disease
The information is in the contrasts
Nov-18
H.S.

6. 3 examples What design should we use? Gender and Smoking
Do girls smoke more than boys?
Exercise and coronary heart disease (CHD)
Does exercise reduce the risk?
Genes and Diabetes type 1
Does gene-type increase the risk?
What design should we use?
Nov-18
H.S.

7. Cross-section
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8. Time
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9. Cross-sectional example
Pro: fast and inexpensive
Con: reversed causality
Adolescents age 16-18
95% CI
Ex 2: Reversed causality: right after disease, CHD->little exercise, later may have CHD->much exercise OK
Nov-18
H.S.

10. Cohort
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11. Disease frequency depicted
Show:
Prevalence
Incidence proportion, closed pop, no loss to follow up
Incidence rate, takes observation time into account, (could also have loss to follow up)
Nov-18
H.S.

12. Cohort example Pro: reliable Con: costly, time consuming Nov-18 H.S.
95% CI
Gene-Diabetes as cohort:
Gene freq 5% * dis freq 1%=0.05%
Number in exposed, diseased cell= *0.05%=50
Nov-18
H.S.

13. Case Control studies
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14. Cohort vs Case-Control
Cases
Controls
Nov-18
H.S.

15. Case-Control studies Cohort studies Case-Control studies
Measure the exposure experiance of the entire population
Case-Control studies
Measure the exposure experiance of a sample of the source population of cases (=base)
Key assumption
Sample controls independent of exposure (same k)
Prospective or retrospective
Nov-18
H.S.

16. Case-Cohort .
controls
Prospective
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17. . . . . Nested Case-Control case case controls controls risk set
Prospective
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18. Traditional Case-Control.
controls
Retrospective
Nov-18
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19. Traditional Case-Control example
Pro: small, efficient
Con: recall bias
95% CI
recall bias
Nov-18
H.S.

20. Calculations
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21. Data layout OBS, table transposed, b and c different
from earlier tables
Nov-18
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22. Cross-sectional Data Pro: fast and inexpensive Con: reversed causality
Reversed causality: diet and stomach cancer
Pro: fast and inexpensive
Con: reversed causality
Nov-18
H.S.

23. Cohort Data Unbalance in the 2x2 table Exposure is rare
Exposure is rare: oversample
Disease is rare: increase sample, may be costly, do we need all the persons (or person time)
Unbalance in the 2x2 table
Exposure is rare
Disease is rare
Nov-18
H.S.

24. 1) Case Cohort 2) Nested Case Control 3) Traditional Case Control
k=sampling fraction
Nov-18
H.S.