Table 1.

Results from standard Cox model applied to simulated data

	Figure 1		Figure 2
	HR	95% CI	HR	95% CI
Higher educated, cohort 1	0.55	[0.53, 0.57]	0.55	[0.53, 0.57]
(Higher educated, cohort 1) * age groups	1.03	[1.03, 1.04]	1.03	[1.03, 1.04]
Higher educated, cohort 2			0.59	[0.57, 0.62]
(Higher educated, cohort 2) * age groups			1.02	[1.01, 1.02]
Higher educated, cohort 3			0.71	[0.68, 0.73]
(Higher educated, cohort 3) * age groups			0.98	[0.98, 0.99]
Higher educated, cohort 4			0.82	[0.78, 0.85]
(Higher educated, cohort 4) * age groups			0.95	[0.95, 0.96]

Notes:

^1.HR: Hazard Ratio; CI: Confidence Interval

^2.100,000 cases are randomly drawn from 1 million cases in each simulated data. They are split into long format by 12 five-year age groups: 30–34, 35–39, 40–44, 45–49, 50–54, 55–59, 60–64, 65–69, 70–74, 75–79, 80–84, and 85–90. These age groups are coded from 1 to 12.

^3.Time metric in continuous Cox model is attained age (age of death or being censored). Therefore, the main effects of age groups are not controlled in the model. Inclusion does not alter the results.

^4.Advantageous over other parametric models, Cox model does not need to make any parametric assumption of the underlying hazard function. Piecewise exponential model (piecewise constant hazard) and discrete time non-parametric baseline model (estimated with pgmhaz command) are also used to test the robustness of results. These two models provide almost identical results to those from Cox model. But these models do not adjust for gamma distribution of frailty.