. Author manuscript; available in PMC: 2019 Mar 14.

Published in final edited form as: Comput Stat. 2018 May 15;33(4):1589–603. doi: 10.1007/s00180-018-0813-z

Table 4.

Average computing times on all quantile levels from 200 Monte-Carlo simulations in Model (7) under all settings (Seconds)

	S1–1		S1–2
	N = 500	N = 1000	N = 500	N = 1000
FI (M = 10)	0.826	1.313	0.789	1.357
FI (M = 20)	0.903	2.883	1.775	2.972
MI (m = 10)	8.353	21.929	18.079	22.355
	S2–1		S2–2
	N = 500	N = 1000	N = 500	N = 1000
FI (M = 10)	0.519	1.365	1.237	2.354
FI (M = 20)	0.986	1.972	1.550	3.533
FIIPW (M = 10)	0.509	1.404	1.316	2.345
FIIPW (M = 20)	0.995	2.020	1.635	3.535
IPW	0.062	0.112	0.049	0.079
MI (m = 10)	9.469	14.622	23.649	38.588
MIIPW (m = 10)	9.744	15.301	25.685	40.350

Here FI, FIIPW, IPW, MI, MIIPW are the imputation approaches. N stands for sample size and M stands for the number of x we simulate from the estimate function f (x|z_i). m stands for the repeated imputation-estimation times in MI and MIIPW