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Table 1 Simulation results (10-30% censored; Scenario 1)

From: A multiple imputation method based on weighted quantile regression models for longitudinal censored biomarker data with missing values at early visits

α α 0 α 1 α 2
Method Bias 100xRE Bias 100xRE Bias 100xRE
10% censored  
OMNI 0.0015 -0.0004 -0.0009
CC-DL/2 -0.0353 40.885 0.2295 32.190 0.0163 49.142
MI 1 0.0151 19.644 -0.1900 15.025 -0.0531 29.805
MI 2 0.0289 54.944 0.0044 39.458 -0.0055 67.701
MI-CQR 0.0588 61.407 -0.0237 49.594 -0.0133 80.753
MI-wCQR 1 0.0548 64.175 -0.0142 53.410 -0.0109 82.931
MI-wCQR 2 0.0554 64.336 -0.0143 53.619 -0.0110 83.657
MI-wCQR 3 0.0562 63.070 -0.0119 53.832 -0.0112 82.383
15% censored  
OMNI 0.0015 -0.0004 -0.0009
CC-DL/2 0.0155 34.977 0.1073 20.623 0.0005 43.807
MI 1 0.2081 12.694 -0.2884 11.962 -0.0673 20.976
MI 2 0.0318 51.749 0.0043 33.300 -0.0061 65.404
MI-CQR 0.0612 60.611 -0.0265 48.581 -0.0131 80.495
MI-wCQR 1 0.0541 62.868 -0.0195 52.850 -0.0097 81.684
MI-wCQR 2 0.0521 61.869 -0.0194 51.751 -0.0060 80.580
MI-wCQR 3 0.0566 61.969 -0.0155 51.419 -0.0104 81.064
20% censored  
OMNI 0.0015 -0.0004 -0.0009
CC-DL/2 0.0769 25.633 -0.0500 14.061 -0.0084 35.731
MI 1 0.2753 11.360 -0.3920 10.965 -0.0793 15.871
MI 2 0.0339 47.699 0.0041 28.147 -0.0067 61.568
MI-CQR 0.0636 59.024 -0.0273 44.248 -0.0129 75.347
MI-wCQR 1 0.0542 62.054 -0.0215 49.542 -0.0087 79.569
MI-wCQR 2 0.0485 62.323 -0.0233 48.830 -0.0066 78.507
MI-wCQR 3 0.0618 60.503 -0.0178 45.908 -0.0112 75.721
30% censored  
OMNI 0.0015 -0.0004 -0.0009
CC-DL/2 0.2094 12.909 -0.4255 7.810 0.0062 23.053
MI 1 0.4420 8.714 -0.6175 10.370 -0.0973 10.664
MI 2 0.0383 42.703 0.0019 21.804 -0.0076 54.866
MI-CQR 0.0621 58.587 -0.0198 39.975 -0.0111 75.797
MI-wCQR 1 0.0466 61.367 -0.0177 44.947 -0.0042 77.979
MI-wCQR 2 0.0327 62.075 -0.0262 43.389 0.0018 79.091
MI-wCQR 3 0.0302 61.427 -0.0072 40.062 0.0015 75.897
  1. OMNI: Omniscient; CC-DL/2: CC with censored values imputed by DL/2; MI-MCMC 1: MI-MCMC imputing only missing values; MI-MCMC 2: MI-MCMC imputing both censored and missing values; MI-CQR: MI-unweighted CQR; MI-wCQR 1: MI-weighted CQR using original probability of missing; MI-wCQR 2: MI-weighted CQR using estimated probability from censored values imputed by DL/2; MI-wCQR 3MI-weighted CQR using estimated probability from uncensored values only; RE: Relative Efficiency