From: A nonparametric multiple imputation approach for missing categorical data
 | Pr(Y=1)=0.297 | Pr(Y=2)=0.250 | ||||||
---|---|---|---|---|---|---|---|---|
Method | Est | SD | SE | CR | Est | SD | SE | CR |
FO | 0.298 | 0.023 | 0.023 | 0.952 | 0.249 | 0.021 | 0.022 | 0.974 |
CC | 0.328 | 0.032 | 0.033 | 0.862 | 0.323 | 0.033 | 0.033 | 0.406 |
 | Working models for Y: | Five covariates with logit link | ||||||
 |  | (misspecified scenario 5) | ||||||
 | Working models for δ: | Five covariates with logit link | ||||||
 |  | (misspecified scenario 5) | ||||||
CE | 0.295 | 0.068 | 0.058 | 0.956 | 0.218 | 0.049 | 0.051 | 0.926 |
PMI | 0.316 | 0.038 | 0.038 | 0.912 | 0.294 | 0.038 | 0.038 | 0.800 |
NNMI MLR (5,0.4,0.4;0.2) | 0.310 | 0.039 | 0.040 | 0.940 | 0.275 | 0.036 | 0.039 | 0.930 |
NNMI MLR (5,0.1,0.7;0.2) | 0.314 | 0.041 | 0.041 | 0.934 | 0.274 | 0.037 | 0.038 | 0.924 |
NNMI MLR (5,0.7,0.1;0.2) | 0.309 | 0.040 | 0.040 | 0.924 | 0.276 | 0.038 | 0.038 | 0.914 |
NNMI CLR (5,0.4,0.4;0.2) | 0.308 | 0.040 | 0.040 | 0.936 | 0.279 | 0.037 | 0.038 | 0.924 |
NNMI CLR (5,0.1,0.7;0.2) | 0.305 | 0.039 | 0.040 | 0.930 | 0.279 | 0.037 | 0.039 | 0.914 |
NNMI CLR (5,0.7,0.1;0.2) | 0.310 | 0.040 | 0.040 | 0.920 | 0.276 | 0.037 | 0.038 | 0.924 |