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. Author manuscript; available in PMC: 2014 Jan 15.
Published in final edited form as: Biometrika. 2013 May 14;100(3):741–755. doi: 10.1093/biomet/ast012

Table 1.

Simulation results for gamma frailty.

CR σ2 σ̂2 SD β NPMLE J-S1 J-S2
Bias(%) SD SE CP(%) Bias(%) SD Bias(%) SD
λ0(t): Weibull type
15% 2 1.98 .30 β̂1 −0.5 .068 .08 97 0.3 .078 0.0 .104
β̂2 0.5 .061 .07 97 −0.4 .069 0.1 .090
40% 2 1.96 .31 β̂1 −1.6 .085 .09 95 1.2 .090 −1.0 .109
β̂2 1.5 .076 .08 94 −0.9 .081 1.3 .096
15% 1 0.98 .17 β̂1 −0.5 .069 .07 95 0.3 .075 −0.4 .082
β̂2 0.4 .060 .06 94 −0.3 .064 0.3 .071
40% 1 0.97 .19 β̂1 −2.2 .082 .10 97 0.4 .089 −1.1 .093
β̂2 2.3 .071 .08 96 −0.3 .076 1.1 .081
15% 0.5 0.48 .12 β̂1 −0.9 .062 .08 97 −0.1 .069 −0.5 .069
β̂2 1.1 .055 .07 97 0.1 .061 0.7 .062
40% 0.5 0.47 .14 β̂1 −2.4 .077 .09 96 −0.2 .083 −1.7 .082
β̂2 2.9 .070 .08 96 0.2 .075 1.9 .074
λ0 (t): reciprocal type
15% 2 2.00 .30 β̂1 −0.3 .154 .17 96 0.6 .161 0.3 .234
β̂2 1.4 .138 .14 95 0.5 .143 0.8 .208
40% 2 2.00 .32 β̂1 −2.5 .173 .18 95 1.0 .179 0.3 .219
β̂2 4.0 .154 .16 94 0.8 .157 1.0 .201
15% 1 0.99 .17 β̂1 −1.5 .143 .15 96 −0.5 .144 −0.9 .166
β̂2 1.4 .125 .13 96 0.8 .128 0.5 .148
40% 1 0.98 .22 β̂1 −4.2 .163 .18 96 −0.8 .160 −1.6 .172
β̂2 5.2 .146 .16 96 1.0 .145 1.0 .152
15% 0.5 0.48 .11 β̂1 −1.0 .136 .13 94 0.6 .136 0.2 .139
β̂2 1.1 .124 .12 93 −1.0 .122 0.2 .122
40% 0.5 0.47 .12 β̂1 −5.1 .156 .17 95 0.8 .157 −0.3 .156
β̂2 5.2 .140 .15 94 −0.9 .139 1.0 .138

CR, censoring rate; σ2, true variance of frailty; σ̂2, estimate for σ2; SD, sample standard deviation; SE, mean of estimated standard errors; CP, empirical coverage probability of 95% Wald-type confidence interval; NPMLE, proposed nonparametric maximum likelihood estimator; J-S1, smoothed EM-like estimator; J-S2, induced smoothing estimator.