Table 2.

Performances of the estimation of the mixed cure models with cures partially observed: results from 500 simulated data sets of N  =  2000 subjects each with one binary random variable ($X_1$) and one continuous random variable ($X_2$) under various levels of baseline cure probability (the cure probability when $x_1=x_2=0$) and proportion of the cures that was observed in the study. Time to event was generated based on a Weibull distribution.

Baseline cure probability = 0.3

Prob of observed cure = 0.6

Prob of observed cure = 0.8

Parameters for Models

X 1

X 2

Prob of obs cure

X 1

X 2

Prob of obs cure

% bias1

% Cov2

% bias

% Cov

% bias

% Cov

% bias

% Cov

% bias

% Cov

% bias

% Cov

Prob of Uncure $\alpha$

−0.48

93.4

0.51

96.8

0.13

97.2

−0.41

94.0

0.48

95.2

−0.01

96.2

Latency $\beta$

−0.27

94.6

−0.31

95.2

−0.41

94.2

0.72

93.8

Baseline cure probability = 0.5

Prob of observed cure = 0.6

Prob of observed cure = 0.8

Parameters for Models

X 1

X 2

Prob of obs cure

X 1

X 2

Prob of obs cure

% bias

% Cov

% bias

% Cov

% bias

% Cov

% bias

% Cov

% bias

% Cov

% bias

% Cov

Prob of Uncure $\alpha$

0.17

95.2

0.80

95.0

−0.02

96.0

−0.02

96.2

0.82

95.0

0.02

93.0

Latency $\beta$

−0.60

94.0

−0.32

94.8

−0.58

93.8

−0.24

95.0

Baseline cure probability = 0.7

Prob of observed cure = 0.6

Prob of observed cure = 0.8

Parameters for Models

X 1

X 2

Prob of obs cure

X 1

X 2

Prob of obs cure

% bias

% Cov

% bias

% Cov

% bias

% Cov

% bias

% Cov

% bias

% Cov

% bias

% Cov

Prob of Uncure $\alpha$

0.65

94.6

0.25

95.8

0.33

97.2

0.61

95.2

0.25

95.2

0.14

95.2

Latency $\beta$

0.73

93.8

−0.32

95.6

0.68

93.2

−0.21

95.6

Note. 1. % bias = (estimated parameter-true parameter)/true parameter*100%; 2. % cov = proportion of the true parameter included in the estimated 95% confidence intervals obtained from bootstrapping.