1. Let S(t) be the Kaplan-Meier estimator of the survival function and o3(t) = E sit,

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Chapter1: Combinatorial Analysis
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1. Let S(t) be the Kaplan-Meier estimator of the survival function and
o(t) =
sit, <e n(n, - d,)
d,
%3D
(a) Show that the approximate variance of aresin
is
Š(to)
(b) Hence, the 100(1-a)% confidence interval for S(to), based on this transformation,
is given as
1/27
$(to)
max 0, arcsin ($(to)2) – 0.521-0/20s(to)
1-$(to)
sin? {
< S(to) <
sin min
arcsin ($(to)2) +0.521-0/20s(to).
1- $(to)/
Transcribed Image Text:1. Let S(t) be the Kaplan-Meier estimator of the survival function and o(t) = sit, <e n(n, - d,) d, %3D (a) Show that the approximate variance of aresin is Š(to) (b) Hence, the 100(1-a)% confidence interval for S(to), based on this transformation, is given as 1/27 $(to) max 0, arcsin ($(to)2) – 0.521-0/20s(to) 1-$(to) sin? { < S(to) < sin min arcsin ($(to)2) +0.521-0/20s(to). 1- $(to)/
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