54
For time t, we have
S,(i) = exp{-.5t2exp(∕¾B + ∕¾Age)}, (3.21)
R(t) = exp{-.5texp(∕¾cB + ∕¾cAge)}, (3.22)
where β1 = .5, β2 = .4, βlc = .6 and ∕⅜c = ∙3.
The joint distribution of T and C is specified by the Frank copula as below:
— l)(ɑɑ(ɑ) — 11
•Ж c; ɑ) = logα{l + -----ɪ-----¾ (3.23)
α-l
We tested Kendall’s τ — 0.8, corresponding to a = 0.00000001258 with different
percentages of events, dependent and independent censoring.
In order to generate the observations of event time and informative censoring time,
we used the results by Nelsen (1986):
• Step 1, generate two independent Uniform(0,l) random variables и and v .
. Step 2, let v = logα{l + ,⅛-,1.> tt}.
Then we get the cumulative distribution functions и and v for two variables, which
satisfy the relationship specified by the Frank copula. We get S(f) and R(t) through
и and v. Plug them into Equations 3.21 and 3.22, and then get ⅛ and tc as shown
below:
= /-21og(5(⅛))
τ у exp(Z'iβ')
= -21og(B(t))
c exp(W-βc)