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. Author manuscript; available in PMC: 2009 Apr 23.
Published in final edited form as: Biometrics. 2007 Nov 12;64(3):673–684. doi: 10.1111/j.1541-0420.2007.00930.x

Table 2.

Biases and (RMSEs) for the naive approach that ignores existence of measurement error and our proposed method. The results are based on a simulation study with 500 replications for 1000 cases and 1000 controls, where disease status (D) is binary, environmental variables (X, W) are continuous, and the genetic variant h3 is in the form of diplotype with a multiplicative interaction. The environmental variable is measured with error and the error variance is 0.25. Two cases are considered: (a) genotype known for all subjects and (b) genotype missing for 50% of the subjects.

Naive approach
Proposed method
Parameter True value Bias RMSE Bias RMSE
Complete data β0 −5.000 1.207 1.459 0.230 0.086
βg 0.693 0.080 0.011 −0.001 0.007
βx 1.099 −0.797 0.645 0.001 0.137
βxg 0.693 −0.478 0.235 0.006 0.088
pr(h3) 0.250 0.005 0.000 0.000 0.000
pr(D = 1) 0.046 −0.032 0.001 0.008 0.000
η1 0.000 0.003 0.001
η2 0.100 −0.001 0.000
50% of genetic information is missing β0 −5.000 1.206 1.460 0.228 0.084
βg 0.693 0.082 0.015 −0.002 0.007
βx 1.099 −0.794 0.647 0.013 0.161
βxg 0.693 −0.477 0.243 0.011 0.102
pr(h3) 0.250 0.004 0.000 0.000 0.000
pr(D = 1) 0.046 −0.032 0.001 0.008 0.000
η1 0.000 0.003 0.001
η2 0.100 −0.002 0.000