   
Model Parameter Estimates

Reg of h on $\widehat{h}$


setting

true # z

used # z

n

β

ρ

Intercept

Slope

R
^{2}

1

5

5

100

1.10

71.50^{a}(estimated)

0.06

1.06

0.82

   
1.14

1.00 (fixed)

0.28

1.48

0.79

   
1.08

20.00 (fixed)

0.08

1.15

0.84

2

5

5

200

0.99

90.03 (estimated)

0.01

1.04

0.87

   
1.05

1.00 (fixed)

0.01

1.13

0.84

   
0.96

20.00 (fixed)

0.00

1.07

0.87

3

5

5

300

0.98

111.76 (estimated)

0.01

1.04

0.90

   
1.03

1.00 (fixed)

0.02

1.10

0.87

   
0.97

20.00 (fixed)

0.01

1.06

0.90

 This table shows the simulation results of estimated regression coefficients β and the nonparametric function h(·) in model logit(π) = xβ+ h(z) for binary outcomes based on 300 runs. True β = 1. In the table, ^{a}is the average of the estimated $\widehat{\rho}$ from 300 simulations.