An example of a study problem

1. An example of a study problem Bias or truth?

2. How it all started 1968/69 Invited: 1622 women aged 38, 46, 50, 54 and 60 years Examined: 1462 women (90.1%)

3. Psychiatric follow-up 1992/93: Those born 1908, 1914, 1918 and 1922, i.e. the four oldest age cohorts aged 70, 74, 78 and 84, Interview 526 of the survivors agreed (89.6%) CT scan: 277 women agreed

4. Samples • 120 ml blood serum stored at –20°C in 2.5 ml covered polystyrene cups enclosed together in small batches, in firmly tied plastic bags for 28 years. • Thawed once for other analyses at 25 y. and restored for two years at ‑80°C.

5. CT scan and Lacunar Infarcts (LI) • Endpoint: • Lacunar infarcts • White matter lesions

6. Logistic regression

7. Predictors – independent variables • Homocysteine was analysed in tertiles using cut points previously calculated for the whole sample.

8. Predictors – independent variables • Covariates included age, basic cardiovascular risk factors and influential factors for tHcy. • The basic CVD risk factors were systolic blood pressure, diastolic blood pressure, serum cholesterol, serum triglycerides, BMI and smoking.

9. Predictors – independent variables • Factors considered to be influential for tHcy were serum B-12, serum creatinine, coffee consumption and dietary folate.

10. Odds ratio for LI according to tHcy

11. Study design • Type of study? • Possible biases?

12. True or false • The data must be representative • if we want to • generalize the results • A homogenous sample • makes generalization easier

13. Estimate of OR OR = 1 0 ∞

14. ( | ) Estimation, precision Sample Estimate with confidence interval 0 ∞ 95% confidence interval: 95% of repeated intervals will contain the true value

15. Precision Bias True value Estimate Precision and validity • Measures of populations • precision - random error - statistics • validity - systematic error - epidemiology

16. True or false • It takes 2 to tango • It takes 3 chords to play the blues • It takes 4 numbers to be an epidemiologist

17. 2 x 2 table

18. Odds ratio for the study population;hypothesis – no effect No effect, OR=1

19. Odds ratio for the sample- observed effect OR> 1

20. Odds ratio for the sample OR> 1

21. 2 x 2 table

22. Odds ratio for the sample OR> 1 D too large? Those without disease and low tHcy more likely to be included?

23. Odds ratio for the sample OR> 1 a too large? Those with disease and high tHcy more likely to be included?

24. Conclusion 1 • If those ill and exposed are more likely to be examined, the effect estimate will be overestimated • Likewise, if those unaffected and unexposed are more likely to be examined.

25. Odds ratio for the sample OR> 1 a too small? Those without disease and high tHcy less likely to be included?

26. Conclusion 2 • If those ill and exposed are less likely to be examined, the effect estimate will be attenuated

27. Generalization • Do the results apply outside the sample? • Statistical generalization • Representative sample • Biological generalization • Information from outside the study • Homogenous sample