Table 2.
Effect (Log RR) of Depression on Stroke Risk | ||||||||||
---|---|---|---|---|---|---|---|---|---|---|
Direct Effect of Depression | Lifetime Effect of Depression | |||||||||
Depression in Midlife | Depression in Late Life | |||||||||
Theoretical Model Under Which Data Were Generated | Depression in Early Life (“True” Effect (3)) |
“True”
Effect ( 2 ) |
Estimated Effect ( 2 ) | % Bias b |
“True”
Effect ( 1 ) |
Estimated Effect ( 1 ) | % Bias b | “True” Effect ( + + ) | Estimated Effect ( + ) | % Bias b |
Accumulation model | 0.69 | 0.69 | 0.75 | 9 | 0.69 | 0.76 | 10 | 2.07 | 1.51 | −27 |
Early-life critical period model | 1.10 | 0.00 | 0.09 | 0.00 | 0.10 | 1.10 | 0.20 | −82 | ||
Pathway model | 0.00 | 0.00 | 0.00 | 1.10 | 1.10 | 0 | 1.10 | 1.10 | 0 | |
Accumulation model with increasing effect across the life course | 0.41 | 0.69 | 0.73 | 6 | 0.92 | 0.96 | 5 | 2.02 | 1.69 | −16 |
Accumulation model with decreasing effect across the life course | 0.92 | 0.69 | 0.77 | 122 | 0.41 | 0.50 | 22 | 2.02 | 1.27 | −37 |
Abbreviation: RR, risk ratio.
a The true direct effect of depression on stroke was set to 0.69, and there were 10,000 replications with 100,000 people in each sample unless otherwise stated. Estimates were obtained from conventional logistic regression models.
b Percent bias = [(average of 10,000 estimated effect − true effect)/true effect] × 100.