Table 2.

Simulation Results Based on Complete Data Generated Using Young et al.'s (18) Algorithm, in Which Every Sixth Measurement of Both the Confounder and the Exposure Are Observed and the Remaining 5 Measurements Are Missing

φ, Sample Size (n), and Statistic	Analytical Approach
	Complete Data	Available- Casea	LOCF	Multiple Imputationb
0 100
Bias	0.013	0.090	0.046	0.002
SD	0.305	0.637	0.528	0.225
rMSE	0.305	0.643	0.530	0.225
500
Bias	−0.005	0.050	0.062	0.003
SD	0.139	0.238	0.231	0.131
rMSE	0.139	0.243	0.239	0.131
−log(3)
100
Bias	−0.037	−0.043	0.885	0.898
SD	0.354	0.699	0.639	0.265
rMSE	0.356	0.700	1.092	0.936
500
Bias	−0.023	0.017	0.852	0.912
SD	0.170	0.287	0.280	0.163
rMSE	0.172	0.288	0.897	0.926
log(2)
100
Bias	0.043	0.161	−0.422	−0.574
SD	0.284	0.666	0.509	0.208
rMSE	0.287	0.685	0.662	0.611
500
Bias	0.039	0.097	−0.437	−0.575
SD	0.123	0.250	0.173	0.140
rMSE	0.129	0.268	0.470	0.592

Abbreviations: LOCF, last observation carried forward; rMSE, root mean squared error; SD, standard deviation.

^a Some estimates were excluded when calculating the performance statistics (bias, SD, and rMSE) because of an excessively high (≥10) odds ratio; for each (φ, n) pair, the following numbers of estimates were excluded: (0, 100): 0; (0, 500): 0; (−log(3), 100): 13; (−log(3), 500): 0; (log(2), 100): 1; (log(2), 100): 0.

^b Some estimates were excluded when calculating the performance statistics (bias, SD, and rMSE) because of an excessively high (≥10) odds ratio; for each (φ, n) pair, the following numbers of estimates were excluded: (0, 100): 8; (0, 500): 2; (−log(3), 100): 6; (−log(3), 500): 5; (log(2), 100): 6; (log(2), 100): 1.