SAS output for exemplar 6 from detailed questions 

This file was produced using the SAS html output with the minimal style. You can
also view the program that created this output.

Some comments have been added to the output in blue and preceeded by ****

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Imputation summary IVEWARE macro
Data checks after IVEWARE data
Postimputation procedures for IVEWARE results
Imputation output PROC MI
Data checks after PROCMI data
Postimputation procedures for PROC MI results

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******THE IVEWARE IMPUTE macro produces a lot of output in a listing file.
BY default it shows lists of variables and code like this that 
summarises observed and imputed data for each variable


Optionally the prediction equations can be viewed at each iteration.

Variable YEYRST02                                                                                                                    
                  Observed           Imputed          Combined                                                                       
  Number              3846               482              4328                                                                       
 Minimum                 0                 0                 0                                                                       
 Maximum                 7                 7                 7                                                                       
    Mean          0.140666          0.192946          0.146488                                                                       
 Std Dev          0.771889          0.983287          0.798243                                                                       
                                                                                                                                     
Variable YFYSHP02                                                                                                                    
                  Observed           Imputed          Combined                                                                       
  Number              3527               801              4328                                                                       
 Minimum                 0                 0                 0                                                                       
 Maximum                 7                 7                 7                                                                       
    Mean          0.246669          0.284644          0.253697                                                                       
 Std Dev           1.04675           1.21403           1.07962                                                                       
                                                                                                                                     
Variable YFYBOP02                                                                                                                    
                  Observed           Imputed          Combined                                                                       
  Number              3521               807              4328                                                                       
 Minimum                 0                 0                 0                                                                       
 Maximum                 7                 7                 7                                                                       
    Mean          0.712014          0.843866          0.736599                                                                       
 Std Dev           1.65557           1.61811           1.64926 

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**** This SAS table was produced by a macro to compare observed and imputed values for most variables there are more in the higher categories for the imputed data. Nothing looks completely wrong as it did for some of the other attempts link to details.

		N	value
			0	1	2	3	4	5	6	7
			PctN	PctN	PctN	PctN	PctN	PctN	PctN	PctN
var	mis	40480	96	2	1	1	0	0	0	0
YAYARS02	0
	1	2800	98	1	0	0	0	0	0	0
YAYBOP02	0	40350	75	7	6	3	2	2	2	3
	1	2930	80	8	5	3	1	1	0	3
YAYBUS02	0	40330	77	8	6	4	1	1	1	2
	1	2950	83	7	4	2	1	1	0	2
YAYCBK02	0	40540	99	1	0	0	0	0	0	0
	1	2740	97	0	0	0	0	0	0	2
YAYGRF02	0	40470	72	8	6	3	2	2	3	4
	1	2810	81	8	5	2	1	1	0	2
YAYHBK02	0	40540	98	1	0	0	0	0	0	0
	1	2740	97	0	0	0	0	.	0	2
YAYHIT02	0	40150	47	11	11	7	4	3	6	10
	1	3130	26	31	20	10	4	3	2	3
YAYHOM02	0	40270	70	13	7	4	1	1	2	2
	1	3010	83	9	5	2	1	0	0	1
YAYJRD02	0	40580	98	1	0	0	0	0	0	0
	1	2700	96	1	0	0	0	0	0	2
YAYROB02	0	40470	98	1	0	0	0	0	0	0
	1	2810	95	0	1	0	0	0	0	3
YAYSCL02	0	40510	89	6	3	1	0	1	0	0
	1	2770	95	1	1	0	0	0	0	2
YAYSHP02	0	40480	73	12	6	3	1	1	2	2
	1	2800	82	8	5	2	1	1	0	2
YAYSKV02	0	40450	83	7	4	2	1	1	1	1
	1	2830	89	4	3	1	1	0	0	2
YAYVND02	0	40540	86	6	3	2	1	1	1	1
	1	2740	92	2	1	1	0	0	0	2
YAYWEP02	0	40480	89	4	2	1	1	0	1	2
	1	2800	92	2	2	1	0	0	0	2
YBYARS02	0	41410	86	5	3	2	1	0	1	1
	1	1870	95	2	1	0	1	0	0	1
YBYBOP02	0	41410	60	10	9	7	3	3	4	5
	1	1870	51	23	14	5	3	2	1	2
YBYBUS02	0	41440	74	9	6	3	1	2	2	2
	1	1840	79	10	5	2	1	1	0	1
YBYCBK02	0	41490	98	1	0	0	0	0	0	0
	1	1790	97	1	0	0	0	0	0	1
YBYGRF02	0	41300	66	7	7	4	3	2	3	8
	1	1980	64	14	9	5	3	2	1	3
YBYHBK02	0	41500	97	2	0	0	0	0	0	0
	1	1780	97	1	0	0	0	0	0	1
YBYHIT02	0	41230	54	14	12	6	3	3	3	4
	1	2050	42	27	16	8	4	1	1	1
YBYHOM02	0	41360	81	7	5	2	1	1	1	1
	1	1920	92	4	2	1	0	0	0	0
YBYJRD02	0	41500	96	2	1	0	0	0	0	0
	1	1780	97	1	1	0	0	0	0	1
YBYPET02	0	41490	94	2	1	1	0	0	0	1
	1	1790	97	1	1	0	0	0	0	1
YBYROB02	0	41490	98	1	0	0	0	0	0	0
	1	1790	99	0	0	0	0	0	.	1
YBYSCL02	0	41480	91	4	2	1	1	0	0	1
	1	1800	97	1	1	1	0	0	0	0
YBYSHP02	0	41530	74	10	6	3	1	1	2	3
	1	1750	82	8	5	2	1	0	0	1
YBYSKV02	0	41330	76	9	5	3	1	2	1	2
	1	1950	81	8	6	2	1	1	1	1
YBYVND02	0	41460	84	6	4	2	1	1	1	1
	1	1820	93	3	2	1	1	0	0	0
YBYWEP02	0	41380	84	5	3	2	1	1	1	3
	1	1900	88	4	3	2	1	0	0	1
YCYARS02	0	42240	86	4	3	2	1	1	1	1
	1	1040	91	3	2	1	0	0	0	1
YCYBOP02	0	42230	56	8	9	7	4	3	5	8
	1	1050	34	31	17	8	4	2	2	2
YCYBUS02	0	42320	69	10	8	4	2	2	2	4
	1	960	67	18	9	3	1	1	.	1
YCYCBK02	0	42120	96	2	1	0	0	0	0	0
	1	1160	98	1	0	0	.	0	.	1
YCYDRG02	0	42390	96	1	1	0	0	0	0	1
	1	890	98	0	0	0	0	0	.	0
YCYGRF02	0	42400	57	6	6	5	4	3	5	13
	1	880	29	28	17	10	5	5	1	5
YCYHBK02	0	42300	97	2	1	0	0	0	0	0
	1	980	98	1	0	0	.	0	.	0
YCYHIT02	0	42210	54	12	10	6	4	2	4	7
	1	1070	31	29	17	9	5	3	1	4
YCYHOM02	0	42360	82	6	4	2	1	1	1	2
	1	920	95	3	2	1	.	.	.	0
YCYJRD02	0	42270	92	3	2	1	1	0	1	1
	1	1010	92	4	1	1	0	0	0	1
YCYPET02	0	42160	94	2	1	1	0	0	0	1
	1	1120	97	1	0	1	0	0	0	0
YCYRAB02	0	42450	98	1	0	0	0	0	0	0
	1	830	99	.	0	0	.	.	.	0
YCYROB02	0	42320	98	1	0	0	0	0	0	0
	1	960	98	.	.	0	.	0	.	2
YCYSCL02	0	42400	89	4	3	1	1	1	1	1
	1	880	96	2	2	0	.	0	0	0
YCYSHP02	0	42300	73	7	5	3	2	2	3	5
	1	980	68	14	9	4	2	1	0	2
YCYSKV02	0	42270	61	10	8	4	3	3	3	8
	1	1010	31	21	18	11	7	5	2	7
YCYVND02	0	42330	78	7	5	3	2	1	2	2
	1	950	85	7	3	2	1	1	1	0
YCYWEP02	0	42330	77	6	4	2	2	1	2	5
	1	950	75	11	8	2	1	1	1	1
YDYARS02	0	41180	90	3	2	2	1	0	1	1
	1	2100	96	1	1	1	0	0	0	0
YDYBOP02	0	41290	62	6	9	6	4	2	5	6
	1	1990	39	27	17	7	3	2	1	4
YDYBUS02	0	41350	69	9	8	5	2	2	2	4
	1	1930	68	14	9	4	2	1	1	3
YDYCBK02	0	41300	96	2	1	1	0	0	0	0
	1	1980	96	1	1	0	0	0	0	1
YDYDRG02	0	41270	93	2	1	1	0	0	1	2
	1	2010	93	2	2	1	0	0	0	2
YDYGRF02	0	41200	64	5	6	5	3	2	5	11
	1	2080	42	23	15	8	3	2	1	5
YDYHBK02	0	41360	96	2	1	0	0	0	0	0
	1	1920	97	1	1	1	0	0	0	0
YDYHIT02	0	41270	68	9	8	5	3	2	2	4
	1	2010	56	19	10	6	3	2	1	3
YDYHOM02	0	41290	83	5	4	2	1	1	2	1
	1	1990	91	4	2	1	0	1	0	1
YDYJRD02	0	41320	92	2	2	1	1	0	1	1
	1	1960	88	4	3	2	1	0	0	2
YDYPET02	0	41300	95	2	1	0	0	0	0	1
	1	1980	98	1	1	0	0	0	0	1
YDYRAB02	0	41270	98	1	1	0	0	0	0	1
	1	2010	98	0	1	0	0	0	0	1
YDYROB02	0	41300	98	1	0	0	0	0	0	0
	1	1980	96	1	1	0	0	0	0	1
YDYSCL02	0	41320	93	2	2	1	0	0	1	1
	1	1960	95	2	1	0	0	0	0	1
YDYSHP02	0	41280	77	5	5	3	2	1	3	5
	1	2000	73	12	7	3	1	1	0	3
YDYSKV02	0	41100	57	8	9	6	3	3	4	10
	1	2180	28	24	18	9	6	4	3	8
YDYVND02	0	41250	81	5	5	3	1	1	2	2
	1	2030	84	6	3	2	1	0	0	2
YDYWEP02	0	41200	80	5	3	3	1	1	2	5
	1	2080	81	8	5	2	1	1	1	2
YEYARS02	0	38500	95	2	1	1	0	0	0	1
	1	4780	95	1	1	0	0	0	0	1
YEYBOP02	0	38500	69	6	7	5	3	2	3	5
	1	4780	57	19	11	5	3	1	1	3
YEYBUS02	0	38550	68	8	8	5	2	1	3	5
	1	4730	49	25	15	6	2	1	1	2
YEYCBK02	0	38550	98	1	1	0	0	0	0	0
	1	4730	95	1	0	0	0	0	0	3
YEYDRG02	0	38570	93	1	1	1	1	0	1	2
	1	4710	92	2	1	1	0	0	0	2
YEYGRF02	0	38520	79	4	4	4	2	1	3	4
	1	4760	72	11	7	4	2	1	1	4
YEYHBK02	0	38460	98	1	1	0	0	0	0	0
	1	4820	96	1	0	0	0	0	0	2
YEYHIT02	0	38400	81	6	4	3	2	1	2	1
	1	4880	79	8	5	2	2	1	1	3
YEYJRD02	0	38570	93	3	1	1	1	0	1	1
	1	4710	91	2	2	1	1	0	0	3
YEYPET02	0	38540	97	1	0	0	0	0	0	1
	1	4740	97	1	0	0	0	0	0	1
YEYRAB02	0	38190	98	1	0	0	0	0	0	0
	1	5090	97	0	0	0	0	0	0	1
YEYROB02	0	38570	99	0	0	0	0	0	0	0
	1	4710	97	0	0	0	0	0	0	2
YEYRST02	0	38460	95	2	1	1	0	0	0	1
	1	4820	94	2	1	1	0	0	0	2
YEYSHP02	0	38560	87	3	3	2	1	1	2	2
	1	4720	86	6	3	2	1	0	0	2
YEYSKV02	0	37940	54	7	8	6	3	3	5	13
	1	5340	25	24	17	11	6	4	3	11
YEYVND02	0	38520	89	3	3	2	1	0	1	1
	1	4760	91	3	2	1	1	1	0	2
YEYWEP02	0	38540	86	3	2	2	1	1	1	4
	1	4740	82	7	4	2	1	1	0	3
YFYARS02	0	35230	97	1	1	0	0	0	0	0
	1	8050	95	1	1	0	0	0	0	2
YFYBFT02	0	34970	99	0	0	0	0	.	0	0
	1	8310	86	1	0	0	0	0	0	12
YFYBOP02	0	35210	77	7	6	3	2	1	2	3
	1	8070	63	14	9	4	2	1	1	5
YFYCBK02	0	35270	98	1	0	0	0	0	0	0
	1	8010	92	1	1	1	0	0	0	5
YFYDRG02	0	35210	93	1	1	1	0	1	1	2
	1	8070	85	4	3	1	1	1	0	5
YFYFRD02	0	34830	99	0	.	0	0	.	0	0
	1	8450	59	0	0	0	0	0	0	41
YFYHBK02	0	35170	99	1	0	0	0	0	0	0
	1	8110	94	1	1	0	0	0	0	4
YFYHIT02	0	35100	85	6	4	2	1	1	1	1
	1	8180	82	6	4	2	1	1	0	4
YFYJRD02	0	35290	97	2	1	0	0	0	0	0
	1	7990	94	1	1	0	0	0	0	3
YFYPET02	0	35280	99	1	0	0	0	0	0	0
	1	8000	98	1	0	0	0	0	0	1
YFYRAB02	0	35290	98	0	0	0	0	0	0	0
	1	7990	94	1	1	0	0	0	0	3
YFYROB02	0	35070	99	0	0	0	0	0	0	0
	1	8210	93	1	1	0	0	0	0	4
YFYRST02	0	35240	97	1	0	0	0	0	0	0
	1	8040	94	1	1	1	0	0	0	3
YFYRST22	0	35240	91	4	2	1	0	0	1	1
	1	8040	84	5	3	2	1	1	0	4
YFYSHP02	0	35270	92	2	2	1	0	0	1	1
	1	8010	91	2	1	1	0	0	0	3
YFYSKV02	0	27270	51	5	10	8	4	5	7	11
	1	16010	18	19	16	11	8	6	5	17
YFYVND02	0	35240	90	3	2	2	0	1	1	1
	1	8040	88	4	2	1	1	1	0	3
YFYWEP02	0	35240	91	2	2	1	0	0	1	2
	1	8040	86	4	3	2	1	1	0	3

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The MIANALYZE Procedure BOYS ONLY

Model Information
Data Set	WORK.OUTCOV
Number of Imputations	10

***** The first table gives the breakdown of variation in estimates within and between estimates and the amount of missing information. The missing information can be less than the % of data that are missing if some is recovered from correlations with other variables. Only DVAR5 and DVAR6 have much missing information.

Multiple Imputation Variance Information
Parameter	Variance			DF	Relative Increase in Variance	Fraction Missing Information
	Between	Within	Total
dprev1	0.000003434	0.000074479	0.000078256	3862.4	0.050720	0.048764
dprev2	0.000001459	0.000077191	0.000078796	21708	0.020785	0.020452
dprev3	0.000000837	0.000067496	0.000068417	49686	0.013642	0.013498
dprev4	0.000000800	0.000076162	0.000077042	68983	0.011554	0.011451
dprev5	0.000005092	0.000084057	0.000089658	2305.9	0.066637	0.063286
dprev6	0.000082448	0.000082283	0.000173	32.739	1.102199	0.550928
dvol1	0.005869	0.110718	0.117174	2964.5	0.058312	0.055736
dvol2	0.000457	0.124148	0.124651	552243	0.004053	0.004041
dvol3	0.000909	0.215530	0.216530	422212	0.004638	0.004622
dvol4	0.001071	0.222785	0.223964	325085	0.005289	0.005268
dvol5	0.006861	0.143345	0.150892	3597.7	0.052649	0.050543
dvol6	0.510691	0.137307	0.699067	13.937	4.091257	0.826778
dvar1	0.000049428	0.003754	0.003809	44160	0.014483	0.014321
dvar2	0.000026676	0.004628	0.004658	226755	0.006340	0.006309
dvar3	0.000032336	0.005827	0.005863	244490	0.006104	0.006075
dvar4	0.000062525	0.005726	0.005795	63885	0.012012	0.011900
dvar5	0.000250	0.003866	0.004140	2046.3	0.071028	0.067229
dvar6	0.004516	0.003031	0.007999	23.335	1.638737	0.649811

***** The Next table gives the estimates and standard errors for each variable along with the maximum and minimum value that you get from any of the 10 imoutations. The confidence intervals allow for the variation between imputations.

Multiple Imputation Parameter Estimates
Parameter	Estimate	Std Error	95% Confidence Limits		DF	Minimum	Maximum	Theta0	t for H0: Parameter=Theta0	Pr > |t|
dprev1	0.795021	0.008846	0.77768	0.81236	3862.4	0.792599	0.798995	0	89.87	<.0001
dprev2	0.784788	0.008877	0.76739	0.80219	21708	0.782092	0.786204	0	88.41	<.0001
dprev3	0.819872	0.008271	0.80366	0.83608	49686	0.817725	0.820923	0	99.12	<.0001
dprev4	0.788716	0.008777	0.77151	0.80592	68983	0.787117	0.789858	0	89.86	<.0001
dprev5	0.757058	0.009469	0.73849	0.77563	2305.9	0.754226	0.761535	0	79.95	<.0001
dprev6	0.764367	0.013152	0.73760	0.79113	32.739	0.747830	0.773413	0	58.12	<.0001
dvol1	10.809456	0.342307	10.13827	11.48064	2964.5	10.718136	10.943810	0	31.58	<.0001
dvol2	11.513705	0.353060	10.82172	12.20569	552243	11.481042	11.561444	0	32.61	<.0001
dvol3	16.227867	0.465328	15.31584	17.13989	422212	16.189127	16.279580	0	34.87	<.0001
dvol4	15.274555	0.473248	14.34700	16.20211	325085	15.216537	15.323892	0	32.28	<.0001
dvol5	11.390087	0.388448	10.62849	12.15169	3597.7	11.280950	11.592965	0	29.32	<.0001
dvol6	10.837506	0.836102	9.04349	12.63152	13.937	9.361352	12.095934	0	12.96	<.0001
dvar1	2.983189	0.061713	2.86223	3.10415	44160	2.969849	2.992691	0	48.34	<.0001
dvar2	3.272088	0.068247	3.13833	3.40585	226755	3.267245	3.283234	0	47.94	<.0001
dvar3	3.860895	0.076567	3.71083	4.01097	244490	3.852444	3.869804	0	50.42	<.0001
dvar4	3.583097	0.076122	3.43390	3.73230	63885	3.570580	3.597990	0	47.07	<.0001
dvar5	2.685747	0.064346	2.55956	2.81194	2046.3	2.663317	2.718136	0	41.74	<.0001
dvar6	2.274006	0.089438	2.08914	2.45888	23.335	2.133851	2.361352	0	25.43	<.0001

*********** Now results from logistic regression estimates only shown

Multiple Imputation Parameter Estimates
Parameter	Estimate	Std Error	95% Confidence Limits		DF	Minimum	Maximum	Theta0	t for H0: Parameter=Theta0	Pr > |t|
GENDERFemale	-0.191119	0.039837	-0.26978	-0.11246	164.48	-0.220764	-0.163021	0	-4.80	<.0001
SZINDEPManual_high_depr	0.272795	0.039570	0.19506	0.35053	514.29	0.251888	0.295251	0	6.89	<.0001
sectorBehavioural	1.582194	0.665119	0.24032	2.92407	42.413	0.986843	2.436056	0	2.38	0.0219
sectorIndependent	-0.534746	0.237318	-1.00676	-0.06273	83.04	-0.767530	-0.381391	0	-2.25	0.0269
sectorSpecial	-1.140705	0.373077	-1.88592	-0.39549	64.392	-1.534438	-0.839111	0	-3.06	0.0032

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*********** PROC MI produces lots of output only a few extracts given here.
First a summary of settings.
Additional default outputs are missing data patterns and the variance covariance matrix of the
variables, not shown here as too big. variables

Model Information
Data Set	WORK.TEMP2
Method	MCMC
Multiple Imputation Chain	Single Chain
Initial Estimates for MCMC	EM Posterior Mode
Start	Starting Value
Prior	Jeffreys
Number of Imputations	10
Number of Burn-in Iterations	200
Number of Iterations	100
Seed for random number generator	24374

**** Convergence plots for any variable or covariances of variables can be selected from the imputation step. One is shown here for the covariance of two questions. It looks cleareer in SAS. No problems appeared with any variables.

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**** Now a table of observed and imputed data after rounding results
This is from PROC MI results.

		N	value
			0	1	2	3	4	5	6	7
			PctN	PctN	PctN	PctN	PctN	PctN	PctN	PctN
var	mis	40480	96	2	1	1	0	0	0	0
YAYARS02	0
	1	2800	76	23	1	.	.	.	.	.
YAYBOP02	0	40350	75	7	6	3	2	2	2	3
	1	2930	44	22	18	9	5	2	1	0
YAYBUS02	0	40330	77	8	6	4	1	1	1	2
	1	2950	45	25	17	8	3	1	0	.
YAYCBK02	0	40540	99	1	0	0	0	0	0	0
	1	2740	96	4	.	.	.	.	.	.
YAYGRF02	0	40470	72	8	6	3	2	2	3	4
	1	2810	45	22	16	10	5	2	0	0
YAYHBK02	0	40540	98	1	0	0	0	0	0	0
	1	2740	82	17	1	.	.	.	.	.
YAYHIT02	0	40150	47	11	11	7	4	3	6	10
	1	3130	30	15	16	13	11	6	4	4
YAYHOM02	0	40270	70	13	7	4	1	1	2	2
	1	3010	46	27	16	8	2	1	0	0
YAYJRD02	0	40580	98	1	0	0	0	0	0	0
	1	2700	79	19	2	0	.	.	.	.
YAYROB02	0	40470	98	1	0	0	0	0	0	0
	1	2810	86	14	0	.	.	.	.	.
YAYSCL02	0	40510	89	6	3	1	0	1	0	0
	1	2770	63	29	7	0	0	.	.	.
YAYSHP02	0	40480	73	12	6	3	1	1	2	2
	1	2800	44	24	16	9	3	2	1	0
YAYSKV02	0	40450	83	7	4	2	1	1	1	1
	1	2830	51	27	16	4	2	0	0	.
YAYVND02	0	40540	86	6	3	2	1	1	1	1
	1	2740	55	28	13	3	1	0	0	.
YAYWEP02	0	40480	89	4	2	1	1	0	1	2
	1	2800	54	28	14	4	1	0	0	0
YBYARS02	0	41410	86	5	3	2	1	0	1	1
	1	1870	53	29	12	4	2	0	0	0
YBYBOP02	0	41410	60	10	9	7	3	3	4	5
	1	1870	35	20	16	13	6	4	3	2
YBYBUS02	0	41440	74	9	6	3	1	2	2	2
	1	1840	41	23	17	10	5	3	1	0
YBYCBK02	0	41490	98	1	0	0	0	0	0	0
	1	1790	86	13	1	0	.	.	.	.
YBYGRF02	0	41300	66	7	7	4	3	2	3	8
	1	1980	34	19	16	11	9	5	3	3
YBYHBK02	0	41500	97	2	0	0	0	0	0	0
	1	1780	82	16	2	0	.	.	.	.
YBYHIT02	0	41230	54	14	12	6	3	3	3	4
	1	2050	33	20	18	14	7	5	2	2
YBYHOM02	0	41360	81	7	5	2	1	1	1	1
	1	1920	52	29	14	3	1	0	0	.
YBYJRD02	0	41500	96	2	1	0	0	0	0	0
	1	1780	66	25	6	3	1	0	0	.
YBYPET02	0	41490	94	2	1	1	0	0	0	1
	1	1790	63	29	5	2	1	0	.	.
YBYROB02	0	41490	98	1	0	0	0	0	0	0
	1	1790	87	13	0	.	.	.	.	.
YBYSCL02	0	41480	91	4	2	1	1	0	0	1
	1	1800	64	30	6	1	.	.	.	.
YBYSHP02	0	41530	74	10	6	3	1	1	2	3
	1	1750	43	21	17	10	5	3	1	0
YBYSKV02	0	41330	76	9	5	3	1	2	1	2
	1	1950	42	24	17	9	5	2	0	0
YBYVND02	0	41460	84	6	4	2	1	1	1	1
	1	1820	50	28	12	5	2	1	1	0
YBYWEP02	0	41380	84	5	3	2	1	1	1	3
	1	1900	45	25	16	7	4	2	0	1
YCYARS02	0	42240	86	4	3	2	1	1	1	1
	1	1040	50	24	15	7	2	1	0	.
YCYBOP02	0	42230	56	8	9	7	4	3	5	8
	1	1050	28	17	16	12	12	7	4	6
YCYBUS02	0	42320	69	10	8	4	2	2	2	4
	1	960	31	23	18	12	6	5	2	2
YCYCBK02	0	42120	96	2	1	0	0	0	0	0
	1	1160	68	23	5	4	0	.	.	.
YCYDRG02	0	42390	96	1	1	0	0	0	0	1
	1	890	61	27	8	2	1	0	.	.
YCYGRF02	0	42400	57	6	6	5	4	3	5	13
	1	880	23	13	14	11	11	8	8	12
YCYHBK02	0	42300	97	2	1	0	0	0	0	0
	1	980	63	28	6	2	0	.	.	.
YCYHIT02	0	42210	54	12	10	6	4	2	4	7
	1	1070	26	17	17	13	10	7	4	5
YCYHOM02	0	42360	82	6	4	2	1	1	1	2
	1	920	53	27	12	6	2	0	0	.
YCYJRD02	0	42270	92	3	2	1	1	0	1	1
	1	1010	48	27	12	5	3	3	1	0
YCYPET02	0	42160	94	2	1	1	0	0	0	1
	1	1120	63	29	6	1	0	0	.	.
YCYRAB02	0	42450	98	1	0	0	0	0	0	0
	1	830	76	21	2	1	.	.	.	.
YCYROB02	0	42320	98	1	0	0	0	0	0	0
	1	960	80	19	1	.	.	.	.	.
YCYSCL02	0	42400	89	4	3	1	1	1	1	1
	1	880	52	34	12	2	1	0	.	.
YCYSHP02	0	42300	73	7	5	3	2	2	3	5
	1	980	34	17	16	11	9	5	4	5
YCYSKV02	0	42270	61	10	8	4	3	3	3	8
	1	1010	17	10	15	12	13	9	8	16
YCYVND02	0	42330	78	7	5	3	2	1	2	2
	1	950	38	24	15	10	7	3	2	2
YCYWEP02	0	42330	77	6	4	2	2	1	2	5
	1	950	38	19	16	12	7	3	2	3
YDYARS02	0	41180	90	3	2	2	1	0	1	1
	1	2100	54	30	12	4	1	0	0	.
YDYBOP02	0	41290	62	6	9	6	4	2	5	6
	1	1990	29	16	15	15	10	7	4	3
YDYBUS02	0	41350	69	9	8	5	2	2	2	4
	1	1930	35	20	17	12	7	5	2	1
YDYCBK02	0	41300	96	2	1	1	0	0	0	0
	1	1980	58	30	8	3	1	0	.	.
YDYDRG02	0	41270	93	2	1	1	0	0	1	2
	1	2010	53	25	10	3	3	3	1	1
YDYGRF02	0	41200	64	5	6	5	3	2	5	11
	1	2080	28	14	15	12	10	7	6	8
YDYHBK02	0	41360	96	2	1	0	0	0	0	0
	1	1920	67	25	6	2	0	0	.	.
YDYHIT02	0	41270	68	9	8	5	3	2	2	4
	1	2010	29	20	18	13	10	5	3	2
YDYHOM02	0	41290	83	5	4	2	1	1	2	1
	1	1990	50	27	14	6	1	1	0	.
YDYJRD02	0	41320	92	2	2	1	1	0	1	1
	1	1960	45	27	13	5	4	3	2	1
YDYPET02	0	41300	95	2	1	0	0	0	0	1
	1	1980	64	28	6	1	0	0	.	.
YDYRAB02	0	41270	98	1	1	0	0	0	0	1
	1	2010	70	26	3	1	0	.	.	.
YDYROB02	0	41300	98	1	0	0	0	0	0	0
	1	1980	71	26	3	0	0	.	.	.
YDYSCL02	0	41320	93	2	2	1	0	0	1	1
	1	1960	60	30	8	2	0	0	.	.
YDYSHP02	0	41280	77	5	5	3	2	1	3	5
	1	2000	32	19	18	11	9	5	3	3
YDYSKV02	0	41100	57	8	9	6	3	3	4	10
	1	2180	21	12	11	13	10	10	9	13
YDYVND02	0	41250	81	5	5	3	1	1	2	2
	1	2030	39	24	18	9	5	3	1	1
YDYWEP02	0	41200	80	5	3	3	1	1	2	5
	1	2080	38	19	17	12	7	4	2	1
YEYARS02	0	38500	95	2	1	1	0	0	0	1
	1	4780	61	30	6	1	0	0	0	0
YEYBOP02	0	38500	69	6	7	5	3	2	3	5
	1	4780	32	17	18	14	8	6	3	2
YEYBUS02	0	38550	68	8	8	5	2	1	3	5
	1	4730	37	18	17	12	8	4	2	1
YEYCBK02	0	38550	98	1	1	0	0	0	0	0
	1	4730	72	24	3	1	.	.	.	.
YEYDRG02	0	38570	93	1	1	1	1	0	1	2
	1	4710	53	27	11	5	3	1	1	1
YEYGRF02	0	38520	79	4	4	4	2	1	3	4
	1	4760	34	18	18	13	8	5	2	1
YEYHBK02	0	38460	98	1	1	0	0	0	0	0
	1	4820	81	18	1	.	.	.	.	0
YEYHIT02	0	38400	81	6	4	3	2	1	2	1
	1	4880	37	26	19	10	5	2	1	0
YEYJRD02	0	38570	93	3	1	1	1	0	1	1
	1	4710	51	29	13	5	2	1	0	0
YEYPET02	0	38540	97	1	0	0	0	0	0	1
	1	4740	70	25	3	1	0	0	.	0
YEYRAB02	0	38190	98	1	0	0	0	0	0	0
	1	5090	77	21	2	0	0	.	.	0
YEYROB02	0	38570	99	0	0	0	0	0	0	0
	1	4710	86	14	0	.	.	.	.	.
YEYRST02	0	38460	95	2	1	1	0	0	0	1
	1	4820	62	29	7	2	1	0	0	.
YEYSHP02	0	38560	87	3	3	2	1	1	2	2
	1	4720	44	24	17	9	4	1	1	0
YEYSKV02	0	37940	54	7	8	6	3	3	5	13
	1	5340	19	11	12	12	12	11	9	15
YEYVND02	0	38520	89	3	3	2	1	0	1	1
	1	4760	47	29	15	6	2	1	0	0
YEYWEP02	0	38540	86	3	2	2	1	1	1	4
	1	4740	41	22	17	10	6	2	1	1
YFYARS02	0	35230	97	1	1	0	0	0	0	0
	1	8050	75	23	1	0	.	.	.	.
YFYBFT02	0	34970	99	0	0	0	0	.	0	0
	1	8310	92	8	.	.	.	.	.	.
YFYBOP02	0	35210	77	7	6	3	2	1	2	3
	1	8070	38	23	20	12	5	2	1	0
YFYCBK02	0	35270	98	1	0	0	0	0	0	0
	1	8010	84	16	1	.	.	.	.	.
YFYDRG02	0	35210	93	1	1	1	0	1	1	2
	1	8070	53	26	12	5	3	1	0	0
YFYFRD02	0	34830	99	0	.	0	0	.	0	0
	1	8450	89	11	0	.	.	.	.	.
YFYHBK02	0	35170	99	1	0	0	0	0	0	0
	1	8110	86	13	1	0	.	.	.	.
YFYHIT02	0	35100	85	6	4	2	1	1	1	1
	1	8180	47	29	16	6	2	0	0	.
YFYJRD02	0	35290	97	2	1	0	0	0	0	0
	1	7990	71	25	3	0	0	.	.	.
YFYPET02	0	35280	99	1	0	0	0	0	0	0
	1	8000	83	16	1	0	.	.	.	.
YFYRAB02	0	35290	98	0	0	0	0	0	0	0
	1	7990	77	22	1	0	.	.	.	.
YFYROB02	0	35070	99	0	0	0	0	0	0	0
	1	8210	84	16	0	0	.	.	.	.
YFYRST02	0	35240	97	1	0	0	0	0	0	0
	1	8040	69	26	4	1	0	.	.	.
YFYRST22	0	35240	91	4	2	1	0	0	1	1
	1	8040	51	31	12	4	1	0	0	.
YFYSHP02	0	35270	92	2	2	1	0	0	1	1
	1	8010	56	28	12	3	1	0	0	.
YFYSKV02	0	27270	51	5	10	8	4	5	7	11
	1	16010	15	9	11	12	12	11	9	19
YFYVND02	0	35240	90	3	2	2	0	1	1	1
	1	8040	49	30	15	5	1	0	0	.
YFYWEP02	0	35240	91	2	2	1	0	0	1	2
	1	8040	48	27	16	6	2	1	0	.

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*****Finally post imputation output from PROC MI, first prevalence for boys,
only the estimated means are shown here.

Multiple Imputation Parameter Estimates
Parameter	Estimate	Std Error	95% Confidence Limits		DF	Minimum	Maximum	Theta0	t for H0: Parameter=Theta0	Pr > |t|
dprev1	0.808093	0.008489	0.79145	0.82473	36808	0.806584	0.809785	0	95.19	<.0001
dprev2	0.789072	0.008752	0.77192	0.80623	246854	0.788294	0.790581	0	90.16	<.0001
dprev3	0.820942	0.008226	0.80482	0.83706	234615	0.819845	0.822131	0	99.80	<.0001
dprev4	0.795885	0.008701	0.77883	0.81294	26692	0.794239	0.797439	0	91.47	<.0001
dprev5	0.767307	0.009112	0.74945	0.78517	33953	0.765432	0.769090	0	84.21	<.0001
dprev6	0.774806	0.009313	0.75654	0.79307	1416.8	0.770919	0.778692	0	83.20	<.0001
dvol1	11.091815	0.314571	10.47526	11.70837	93910	11.036123	11.138546	0	35.26	<.0001
dvol2	11.874257	0.353222	11.18195	12.56656	260474	11.836305	11.909465	0	33.62	<.0001
dvol3	16.628715	0.469360	15.70879	17.54864	4.69E6	16.600366	16.645176	0	35.43	<.0001
dvol4	15.991084	0.478408	15.05341	16.92875	135229	15.932785	16.072702	0	33.43	<.0001
dvol5	12.367078	0.360487	11.66053	13.07362	290054	12.335162	12.403749	0	34.31	<.0001
dvol6	9.303429	0.291787	8.73009	9.87677	479.44	9.176955	9.470965	0	31.88	<.0001
dvar1	3.272382	0.065545	3.14387	3.40089	3694.4	3.251943	3.289895	0	49.93	<.0001
dvar2	3.472108	0.071603	3.33177	3.61245	61736	3.461820	3.484225	0	48.49	<.0001
dvar3	4.003704	0.079714	3.84747	4.15994	378295	3.995885	4.011431	0	50.23	<.0001
dvar4	3.889438	0.082572	3.72760	4.05128	66775	3.873342	3.899406	0	47.10	<.0001
dvar5	3.386603	0.077990	3.23372	3.53949	6887.3	3.358025	3.405121	0	43.42	<.0001
dvar6	3.058253	0.076122	2.90861	3.20790	402.46	3.011431	3.089620	0	40.18	<.0001

*****Now post imputation output logistic regression,
only the estimated means are shown here.

Multiple Imputation Parameter Estimates
Parameter	Estimate	Std Error	95% Confidence Limits		DF	Minimum	Maximum	Theta0	t for H0: Parameter=Theta0	Pr > |t|
GENDER1	0.202041	0.036349	0.13075	0.27333	1953.5	0.188424	0.211715	0	5.56	<.0001
SZINDEPManual_high_depr	0.291250	0.039160	0.21441	0.36809	1120.5	0.277200	0.307355	0	7.44	<.0001
sectorBehavioural	1.878687	0.665353	0.56438	3.19300	155.31	1.515617	2.442913	0	2.82	0.0054
sectorIndependent	-0.653223	0.244573	-1.13483	-0.17162	258.58	-0.835988	-0.478719	0	-2.67	0.0080
sectorSpecial	-1.209145	0.368714	-1.93914	-0.47915	120.48	-1.642677	-1.024473	0	-3.28	0.0014