this example demonstrates use of the sas fcs (fully ... fcs imputation example.pdf · this example...

This example demonstrates use of the SAS FCS (Fully Conditional Specification) imputation method in PROC MI. This method

is experimental in SAS v9.3 and as such, is not fully supported and may change prior to becoming production. This method

is equivalent to the sequential regression and chained equations methods of IVEware and Stata. The data used is a subset

of cases and variables from the NHANES 2005-2006 data. You can download the data set by clicking on the data set link on

the ASDA website. The example replicates the Chapter 11 example of the ASDA textbook.

July 15, 2013

******************************************************************************************;

* Example of use of the experimental FCS method of PROC MI

* July 15 2013

* Berglund

* Data used is for Chapter 11 of ASDA ;

******************************************************************************************;

libname d 'f:\brahms\summerclasses\complexanalysis_2013' ;

options ls=130 ps=62 nodate nonumber ;

data c11 ;

set d.impute_subset_nhanes ;

* set to those 18 and older for this imputation and also have positive weight for wtmec2yr ;

if age18p=1 and wtmec2yr > 0 ;

* create combined strata and cluster variable for use in imputation model ;

strata_cluster=sdmvstra*10+sdmvpsu ;

run ;

ods rtf file='f:\brahms\summerclasses\complexanalysis_2013\SAS FCS example.rtf' ;

title ;

proc means n nmiss mean min max ;

run ;

proc mi nimpute=0 ;

run ;

* impute missing data using FCS method with appropriate regression or function ;

proc mi data=c11 out=fcs_imp_c11

seed=2013

min= . . . . . . 14 0 . 4

max= . . . . . . 60 5 . 124

;

class riagendr ridreth1 marcat strata_cluster ;

fcs regression(bmxbmi bpxdi1_1 indfmpir) discrim(marcat) ;

var riagendr ridreth1 wtmec2yr agec agecsq strata_cluster bmxbmi indfmpir marcat bpxdi1_1 ;

run ;

* check imputed variables ;

proc means data=fcs_imp_c11 ;

class _imputation_ ;

var bmxbmi bpxdi1_1 indfmpir ;

run ;

proc freq data=fcs_imp_c11 ;

tables _imputation_*(marcat ) ;

run ;

* analyze 5 imputed data sets using PROC SURVEYREG ;

proc surveyreg data=fcs_imp_c11 ;

strata sdmvstra ; cluster sdmvpsu ; weight wtmec2yr ;

by _imputation_ ;

class marcat riagendr ridreth1 ;

model bpxdi1_1=marcat riagendr ridreth1 agec agecsq bmxbmi indfmpir / solution ;

ods output parameterestimates=fcs_reg_out ;

run ;

proc print data=fcs_reg_out ;

run ;

data fcs_reg_out_1 ;

set fcs_reg_out ;

parameter=compress(parameter) ;

run ;

* use fcs_reg_out_1 with compressed parameter values in PROC MIANALYZE ;

proc mianalyze parms(classvar=full)=fcs_reg_out_1 edf=16 ;

modeleffects intercept marcat1 marcat2 riagendr1 ridreth11 ridreth12 ridreth13 ridreth14 agec agecsq bmxbmi indfmpir ;

run ;

ods rtf close ;

The Means Procedure

Variable Label N

N

Miss Mean Minimum Maximum

SEQN

RIAGENDR

RIDRETH1

INDFMPIR

WTMEC2YR

SDMVPSU

SDMVSTRA

MARCAT

BPXDI1_1

AGE18P

AGEC

AGECSQ

BMXBMI

strata_clust

er

respondent sequence number

gender - adjudicated

1=mex 2=oth hisp 3=white 4=black 5=other

family pir

full sample 2 year mec exam weight

masked variance pseudo-psu

masked variance pseudo-stratum

1=married 2=prev married 3=never married

body mass index (kg/m**2)

5334

5334

5334

5066

5334

5334

5334

5329

4581

5334

5334

5334

5237

5334

0

0

0

268

0

0

0

5

753

0

0

0

97

0

36358.80

1.5198725

2.8710161

2.5923431

40813.74

1.5050619

50.5466817

1.6595984

68.9945427

1.0000000

-0.5079417

406.0373060

28.5119572

506.9718785

31130.00

1.0000000

1.0000000

0

1363.17

1.0000000

44.0000000

1.0000000

4.0000000

1.0000000

-27.5979309

0.1616603

13.3599997

441.0000000

41473.00

2.0000000

5.0000000

5.0000000

156152.18

2.0000000

58.0000000

3.0000000

124.0000000

1.0000000

39.4020691

1552.52

130.2100067

582.0000000

The MI Procedure

Model Information

Data Set WORK.C11

Method MCMC

Multiple Imputation Chain Single Chain

Initial Estimates for MCMC EM Posterior Mode

Start Starting Value

Prior Jeffreys

Number of Imputations 0

Number of Burn-in Iterations 200

Number of Iterations 100

Seed for random number generator 708032001

Missing Data Patterns

Group SEQN RIAGENDR RIDRETH1 INDFMPIR WTMEC2YR SDMVPSU SDMVSTRA MARCAT

1 X X X X X X X X

2 X X X X X X X X

3 X X X X X X X X

4 X X X X X X X X

5 X X X X X X X .

6 X X X X X X X .

7 X X X . X X X X

8 X X X . X X X X

9 X X X . X X X X

10 X X X . X X X X

11 X X X . X X X .


Group BPXDI1_1 AGEC AGECSQ BMXBMI strata_cluster Freq Percent

Group Means

SEQN RIAGENDR RIDRETH1

1 X X X X X 4308 80.76 36350 1.517874 2.873027

2 X X X . X 49 0.92 36511 1.489796 2.918367

3 . X X X X 666 12.49 36351 1.533033 2.990991

4 . X X . X 39 0.73 36644 1.512821 3.179487

5 X X X X X 3 0.06 35644 1.666667 3.000000

6 . X X X X 1 0.02 40762 1.000000 3.000000

7 X X X X X 217 4.07 36516 1.506912 2.447005

8 X X X . X 4 0.07 39099 1.250000 2.500000

9 . X X X X 41 0.77 35850 1.634146 2.536585

10 . X X . X 5 0.09 36233 1.600000 3.600000

11 . X X X X 1 0.02 34036 2.000000 3.000000


Group

Group Means

INDFMPIR WTMEC2YR SDMVPSU SDMVSTRA MARCAT BPXDI1_1 AGEC AGECSQ

1 2.622560 42126 1.528319 50.376509 1.636955 69.092851 -0.978618 385.373120

2 2.117347 32845 1.510204 50.673469 1.693878 69.387755 17.544926 762.681601

The MI Procedure


Group

Group Means

INDFMPIR WTMEC2YR SDMVPSU SDMVSTRA MARCAT BPXDI1_1 AGEC AGECSQ

3 2.454414 37000 1.348348 51.219219 1.753754 . -0.603937 442.466803

4 2.251538 38286 1.487179 49.666667 1.589744 . 9.940531 578.293446

5 2.133333 54858 1.666667 48.000000 . 74.000000 18.402070 539.302851

6 2.220000 111730 1.000000 57.000000 . . 12.402070 153.811340

7 . 30749 1.543779 51.686636 1.764977 67.105991 2.259212 531.622802

8 . 21503 1.500000 47.250000 2.000000 57.000000 17.902069 1046.734100

9 . 31227 1.439024 52.853659 1.878049 . -2.719882 559.895078

10 . 24486 1.200000 48.400000 2.200000 . 20.802069 1035.766089

11 . 38107 2.000000 47.000000 . . 39.402069 1552.523071


Group

Group Means

BMXBMI strata_cluster

1 28.423888 505.293408

2 . 508.244898

3 29.304339 513.540541

4 . 498.153846

5 22.776667 481.666667

6 30.870001 571.000000

7 27.698111 518.410138

8 . 474.000000

9 29.691463 529.975610

10 . 485.200000

11 23.280001 472.000000

The MI Procedure

Model Information

Data Set WORK.C11

Method FCS


Number of Burn-in Iterations 10

Seed for random number generator 2013

FCS Model Specification

Method Imputed Variables

Regression WTMEC2YR AGEC AGECSQ BMXBMI INDFMPIR BPXDI1_1

Discriminant Function RIAGENDR RIDRETH1 strata_cluster MARCAT


Group RIAGENDR RIDRETH1 WTMEC2YR AGEC AGECSQ strata_cluster MARCAT BMXBMI

1 X X X X X X X X

2 X X X X X X X X

3 X X X X X X X X

4 X X X X X X X X

5 X X X X X X X .

6 X X X X X X X .

7 X X X X X X X .

8 X X X X X X X .

9 X X X X X X . X

10 X X X X X X . X

11 X X X X X X . X


Group INDFMPIR BPXDI1_1 Freq Percent

1 X X 4308 80.76

2 X . 666 12.49

3 . X 217 4.07

4 . . 41 0.77

5 X X 49 0.92

6 X . 39 0.73

7 . X 4 0.07

8 . . 5 0.09

9 X X 3 0.06

10 X . 1 0.02

11 . . 1 0.02


Group

Group Means

WTMEC2YR AGEC AGECSQ BMXBMI INDFMPIR BPXDI1_1

1 42126 -0.978618 385.373120 28.423888 2.622560 69.092851

2 37000 -0.603937 442.466803 29.304339 2.454414 .

The MI Procedure


Group

Group Means

WTMEC2YR AGEC AGECSQ BMXBMI INDFMPIR BPXDI1_1

3 30749 2.259212 531.622802 27.698111 . 67.105991

4 31227 -2.719882 559.895078 29.691463 . .

5 32845 17.544926 762.681601 . 2.117347 69.387755

6 38286 9.940531 578.293446 . 2.251538 .

7 21503 17.902069 1046.734100 . . 57.000000

8 24486 20.802069 1035.766089 . . .

9 54858 18.402070 539.302851 22.776667 2.133333 74.000000

10 111730 12.402070 153.811340 30.870001 2.220000 .

11 38107 39.402069 1552.523071 23.280001 . .

Variance Information

Variable

Variance

DF

Relative

Increase

in Variance

Fraction

Missing

Information

Relative

Efficiency Between Within Total

BMXBMI 0.000133 0.008612 0.008772 3652.1 0.018532 0.018357 0.996342

INDFMPIR 0.000008230 0.000474 0.000484 3383.5 0.020827 0.020606 0.995896

BPXDI1_1 0.003624 0.031259 0.035609 253.59 0.139136 0.128618 0.974922

Parameter Estimates

Variable Mean Std Error 95% Confidence Limits DF Minimum Maximum Mu0

t for H0:

Mean=Mu0

Pr > |t

|

BMXBMI 28.501476 0.093658 28.31785 28.68510 3652.1 28.485536 28.516455 0 304.32 <.0001

INDFMPIR 2.580659 0.022002 2.53752 2.62380 3383.5 2.575809 2.583001 0 117.29 <.0001

BPXDI1_1 69.052341 0.188702 68.68072 69.42396 253.59 68.962877 69.126781 0 365.93 <.0001

The MEANS Procedure

Imputation

Number N Obs Variable Label N Mean Std Dev Minimum Maximum

1 5334 BMXBMI

BPXDI1_1

INDFMPIR


family pir

5334

5334

5334

28.4855364

68.9628773

2.5811610

6.7695059

12.8448401

1.5899941

13.3599997

4.0000000

0

130.2100067

124.0000000

5.0000000

2 5334 BMXBMI

BPXDI1_1

INDFMPIR


family pir

5334

5334

5334

28.4996719

69.0803907

2.5825689

6.7737226

12.9352557

1.5892538

13.3599997

4.0000000

0

130.2100067

124.0000000

5.0000000

3 5334 BMXBMI

BPXDI1_1

INDFMPIR


family pir

5334

5334

5334

28.4980382

69.0394673

2.5807545

6.7796662

12.9293061

1.5910268

13.3599997

4.0000000

0

130.2100067

124.0000000

5.0000000

4 5334 BMXBMI

BPXDI1_1

INDFMPIR


family pir

5334

5334

5334

28.5076781

69.1267813

2.5830015

6.7921296

12.9660188

1.5908836

13.3599997

4.0000000

0

130.2100067

124.0000000

5.0000000

5 5334 BMXBMI

BPXDI1_1

INDFMPIR


family pir

5334

5334

5334

28.5164555

69.0521899

2.5758088

6.7734906

12.8875637

1.5907886

13.3599997

4.0000000

0

130.2100067

124.0000000

5.0000000

The FREQ Procedure

Table of _Imputation_ by MARCAT

_Imputation_(Imputation

Number)

MARCAT(1=married 2=prev married

3=never married)

Frequency

Percent

Row Pct

Col Pct 1 2 3 Total

1 3058

11.47

57.33

20.00

1035

3.88

19.40

20.00

1241

4.65

23.27

20.00

5334

20.00

2 3058

11.47

57.33

20.00

1035

3.88

19.40

20.00

1241

4.65

23.27

20.00

5334

20.00

3 3057

11.46

57.31

20.00

1036

3.88

19.42

20.02

1241

4.65

23.27

20.00

5334

20.00

4 3058

11.47

57.33

20.00

1035

3.88

19.40

20.00

1241

4.65

23.27

20.00

5334

20.00

5 3057

11.46

57.31

20.00

1035

3.88

19.40

20.00

1242

4.66

23.28

20.01

5334

20.00

Total 15288

57.32

5176

19.41

6206

23.27

26670

100.00

The SURVEYREG Procedure

Regression Analysis for Dependent Variable BPXDI1_1

Imputation Number=1

Data Summary

Number of Observations 5334

Sum of Weights 217700471

Weighted Mean of BPXDI1_1 70.53294

Weighted Sum of BPXDI1_1 1.53551E10

Design Summary

Number of Strata 15

Number of Clusters 30

Fit Statistics

R-square 0.1405

Root MSE 11.4940

Denominator DF 15

Class Level Information

Class Variable Label Levels Values

MARCAT 1=married 2=prev married 3=never married 3 1 2 3

RIAGENDR gender - adjudicated 2 1 2

RIDRETH1 1=mex 2=oth hisp 3=white 4=black 5=other 5 1 2 3 4 5

Tests of Model Effects

Effect Num DF F Value Pr > F

Model 11 262.30 <.0001

Intercept 1 3175.50 <.0001

MARCAT 2 4.42 0.0309

RIAGENDR 1 90.02 <.0001

RIDRETH1 4 3.74 0.0264

AGEC 1 76.98 <.0001

AGECSQ 1 286.40 <.0001

BMXBMI 1 42.65 <.0001

INDFMPIR 1 1.28 0.2755

Note: The denominator degrees of freedom for the F tests is

15.



Imputation Number=1

Estimated Regression Coefficients

Parameter Estimate

Standard

Error t Value

Pr > |t

|

Intercept 67.0702851 1.49951868 44.73 <.0001

MARCAT 1 0.2522855 0.68287451 0.37 0.7170

MARCAT 2 1.6730076 0.83005894 2.02 0.0621

MARCAT 3 0.0000000 0.00000000 . .

RIAGENDR 1 2.9998082 0.31616607 9.49 <.0001

RIAGENDR 2 0.0000000 0.00000000 . .

RIDRETH1 1 -1.6800212 0.89312861 -1.88 0.0795

RIDRETH1 2 0.5216989 1.52682604 0.34 0.7373

RIDRETH1 3 0.3682412 0.96356299 0.38 0.7077

RIDRETH1 4 1.0884216 0.91298897 1.19 0.2517

RIDRETH1 5 0.0000000 0.00000000 . .

AGEC 0.1177890 0.01342504 8.77 <.0001

AGECSQ -0.0115680 0.00068355 -16.92 <.0001

BMXBMI 0.1866135 0.02857335 6.53 <.0001

INDFMPIR -0.1547323 0.13670372 -1.13 0.2755

Note: The denominator degrees of freedom for the t tests is 15.

Matrix X'WX is singular and a generalized inverse was used to solve the normal equations. Estimates are not

unique.



Imputation Number=2

Data Summary





Design Summary

Number of Strata 15


Fit Statistics

R-square 0.1479

Root MSE 11.4952

Denominator DF 15








Model 11 383.66 <.0001

Intercept 1 2281.29 <.0001

MARCAT 2 1.54 0.2463

RIAGENDR 1 69.67 <.0001

RIDRETH1 4 4.73 0.0114

AGEC 1 75.01 <.0001

AGECSQ 1 313.92 <.0001

BMXBMI 1 31.15 <.0001

INDFMPIR 1 1.04 0.3245


15.



Imputation Number=2


Parameter Estimate

Standard

Error t Value

Pr > |t

|

Intercept 68.1342118 1.66213534 40.99 <.0001

MARCAT 1 0.3108735 0.60707612 0.51 0.6160

MARCAT 2 1.3135833 0.86033199 1.53 0.1476

MARCAT 3 0.0000000 0.00000000 . .

RIAGENDR 1 2.6897616 0.32225651 8.35 <.0001

RIAGENDR 2 0.0000000 0.00000000 . .

RIDRETH1 1 -2.7445784 0.82470760 -3.33 0.0046

RIDRETH1 2 -1.5084345 1.17073871 -1.29 0.2171

RIDRETH1 3 -0.8684088 0.95451076 -0.91 0.3773

RIDRETH1 4 0.3544943 0.82426815 0.43 0.6733

RIDRETH1 5 0.0000000 0.00000000 . .

AGEC 0.1200999 0.01386669 8.66 <.0001

AGECSQ -0.0120150 0.00067814 -17.72 <.0001

BMXBMI 0.2016632 0.03613057 5.58 <.0001

INDFMPIR -0.1212641 0.11904511 -1.02 0.3245



unique.



Imputation Number=3

Data Summary





Design Summary

Number of Strata 15


Fit Statistics

R-square 0.1439

Root MSE 11.4906

Denominator DF 15








Model 11 518.08 <.0001

Intercept 1 2661.13 <.0001

MARCAT 2 3.56 0.0542

RIAGENDR 1 76.46 <.0001

RIDRETH1 4 5.19 0.0079

AGEC 1 93.12 <.0001

AGECSQ 1 331.66 <.0001

BMXBMI 1 44.75 <.0001

INDFMPIR 1 2.13 0.1653


15.



Imputation Number=3


Parameter Estimate

Standard

Error t Value

Pr > |t

|

Intercept 67.0981706 1.65589529 40.52 <.0001

MARCAT 1 0.4217369 0.58182439 0.72 0.4797

MARCAT 2 1.7908206 0.76337193 2.35 0.0331

MARCAT 3 0.0000000 0.00000000 . .

RIAGENDR 1 2.8532415 0.32630560 8.74 <.0001

RIAGENDR 2 0.0000000 0.00000000 . .

RIDRETH1 1 -2.0374045 0.71448659 -2.85 0.0121

RIDRETH1 2 -0.8434731 1.38725761 -0.61 0.5523

RIDRETH1 3 0.3837031 0.94306274 0.41 0.6899

RIDRETH1 4 1.4255478 0.64563753 2.21 0.0432

RIDRETH1 5 0.0000000 0.00000000 . .

AGEC 0.1126007 0.01166867 9.65 <.0001

AGECSQ -0.0117181 0.00064345 -18.21 <.0001

BMXBMI 0.1961471 0.02932021 6.69 <.0001

INDFMPIR -0.1917476 0.13147593 -1.46 0.1653



unique.



Imputation Number=4

Data Summary





Design Summary

Number of Strata 15


Fit Statistics

R-square 0.1474

Root MSE 11.5262

Denominator DF 15








Model 11 201.69 <.0001

Intercept 1 2497.19 <.0001

MARCAT 2 2.82 0.0915

RIAGENDR 1 50.90 <.0001

RIDRETH1 4 3.79 0.0254

AGEC 1 61.42 <.0001

AGECSQ 1 281.56 <.0001

BMXBMI 1 32.19 <.0001

INDFMPIR 1 1.69 0.2134


15.



Imputation Number=4


Parameter Estimate

Standard

Error t Value

Pr > |t

|

Intercept 67.3784718 1.59738045 42.18 <.0001

MARCAT 1 0.3542956 0.52448054 0.68 0.5096

MARCAT 2 1.5324728 0.73799536 2.08 0.0554

MARCAT 3 0.0000000 0.00000000 . .

RIAGENDR 1 2.7434930 0.38454203 7.13 <.0001

RIAGENDR 2 0.0000000 0.00000000 . .

RIDRETH1 1 -1.8516348 0.74948475 -2.47 0.0260

RIDRETH1 2 -0.5337351 1.34276044 -0.40 0.6966

RIDRETH1 3 0.2129756 0.93786598 0.23 0.8234

RIDRETH1 4 1.2000083 0.77380213 1.55 0.1418

RIDRETH1 5 0.0000000 0.00000000 . .

AGEC 0.1155102 0.01473853 7.84 <.0001

AGECSQ -0.0120925 0.00072066 -16.78 <.0001

BMXBMI 0.1974419 0.03480093 5.67 <.0001

INDFMPIR -0.1419877 0.10927231 -1.30 0.2134



unique.



Imputation Number=5

Data Summary





Design Summary

Number of Strata 15


Fit Statistics

R-square 0.1442

Root MSE 11.4369

Denominator DF 15








Model 11 204.70 <.0001

Intercept 1 2320.54 <.0001

MARCAT 2 3.17 0.0710

RIAGENDR 1 72.37 <.0001

RIDRETH1 4 3.33 0.0384

AGEC 1 84.44 <.0001

AGECSQ 1 315.53 <.0001

BMXBMI 1 24.25 0.0002

INDFMPIR 1 0.02 0.8765


15.



Imputation Number=5


Parameter Estimate

Standard

Error t Value

Pr > |t

|

Intercept 67.3277824 1.64788786 40.86 <.0001

MARCAT 1 0.2086344 0.61640150 0.34 0.7397

MARCAT 2 1.5618670 0.86927732 1.80 0.0925

MARCAT 3 0.0000000 0.00000000 . .

RIAGENDR 1 2.6672451 0.31354187 8.51 <.0001

RIAGENDR 2 0.0000000 0.00000000 . .

RIDRETH1 1 -1.3146555 0.73964672 -1.78 0.0958

RIDRETH1 2 0.1243126 1.28368906 0.10 0.9241

RIDRETH1 3 0.4226289 0.81428399 0.52 0.6113

RIDRETH1 4 1.6407827 0.74427952 2.20 0.0435

RIDRETH1 5 0.0000000 0.00000000 . .

AGEC 0.1148625 0.01249975 9.19 <.0001

AGECSQ -0.0119607 0.00067334 -17.76 <.0001

BMXBMI 0.1745127 0.03543502 4.92 0.0002

INDFMPIR -0.0201990 0.12778850 -0.16 0.8765



unique.

Obs _Imputation_ Parameter Estimate StdErr DenDF tValue Probt

1 1 Intercept 67.0702851 1.49951868 15 44.73 <.0001

2 1 MARCAT 1 0.2522855 0.68287451 15 0.37 0.7170

3 1 MARCAT 2 1.6730076 0.83005894 15 2.02 0.0621

4 1 MARCAT 3 0.0000000 0.00000000 15 . .

5 1 RIAGENDR 1 2.9998082 0.31616607 15 9.49 <.0001

6 1 RIAGENDR 2 0.0000000 0.00000000 15 . .

7 1 RIDRETH1 1 -1.6800212 0.89312861 15 -1.88 0.0795

8 1 RIDRETH1 2 0.5216989 1.52682604 15 0.34 0.7373

9 1 RIDRETH1 3 0.3682412 0.96356299 15 0.38 0.7077

10 1 RIDRETH1 4 1.0884216 0.91298897 15 1.19 0.2517

11 1 RIDRETH1 5 0.0000000 0.00000000 15 . .

12 1 AGEC 0.1177890 0.01342504 15 8.77 <.0001

13 1 AGECSQ -0.0115680 0.00068355 15 -16.92 <.0001

14 1 BMXBMI 0.1866135 0.02857335 15 6.53 <.0001

15 1 INDFMPIR -0.1547323 0.13670372 15 -1.13 0.2755

16 2 Intercept 68.1342118 1.66213534 15 40.99 <.0001

17 2 MARCAT 1 0.3108735 0.60707612 15 0.51 0.6160

18 2 MARCAT 2 1.3135833 0.86033199 15 1.53 0.1476

19 2 MARCAT 3 0.0000000 0.00000000 15 . .

20 2 RIAGENDR 1 2.6897616 0.32225651 15 8.35 <.0001

21 2 RIAGENDR 2 0.0000000 0.00000000 15 . .

22 2 RIDRETH1 1 -2.7445784 0.82470760 15 -3.33 0.0046

23 2 RIDRETH1 2 -1.5084345 1.17073871 15 -1.29 0.2171

24 2 RIDRETH1 3 -0.8684088 0.95451076 15 -0.91 0.3773

25 2 RIDRETH1 4 0.3544943 0.82426815 15 0.43 0.6733

26 2 RIDRETH1 5 0.0000000 0.00000000 15 . .

27 2 AGEC 0.1200999 0.01386669 15 8.66 <.0001

28 2 AGECSQ -0.0120150 0.00067814 15 -17.72 <.0001

29 2 BMXBMI 0.2016632 0.03613057 15 5.58 <.0001

30 2 INDFMPIR -0.1212641 0.11904511 15 -1.02 0.3245

31 3 Intercept 67.0981706 1.65589529 15 40.52 <.0001

32 3 MARCAT 1 0.4217369 0.58182439 15 0.72 0.4797

33 3 MARCAT 2 1.7908206 0.76337193 15 2.35 0.0331

34 3 MARCAT 3 0.0000000 0.00000000 15 . .

35 3 RIAGENDR 1 2.8532415 0.32630560 15 8.74 <.0001

36 3 RIAGENDR 2 0.0000000 0.00000000 15 . .

37 3 RIDRETH1 1 -2.0374045 0.71448659 15 -2.85 0.0121

38 3 RIDRETH1 2 -0.8434731 1.38725761 15 -0.61 0.5523

39 3 RIDRETH1 3 0.3837031 0.94306274 15 0.41 0.6899

40 3 RIDRETH1 4 1.4255478 0.64563753 15 2.21 0.0432

41 3 RIDRETH1 5 0.0000000 0.00000000 15 . .

42 3 AGEC 0.1126007 0.01166867 15 9.65 <.0001

43 3 AGECSQ -0.0117181 0.00064345 15 -18.21 <.0001

44 3 BMXBMI 0.1961471 0.02932021 15 6.69 <.0001

45 3 INDFMPIR -0.1917476 0.13147593 15 -1.46 0.1653

46 4 Intercept 67.3784718 1.59738045 15 42.18 <.0001

47 4 MARCAT 1 0.3542956 0.52448054 15 0.68 0.5096

Obs _Imputation_ Parameter Estimate StdErr DenDF tValue Probt

48 4 MARCAT 2 1.5324728 0.73799536 15 2.08 0.0554

49 4 MARCAT 3 0.0000000 0.00000000 15 . .

50 4 RIAGENDR 1 2.7434930 0.38454203 15 7.13 <.0001

51 4 RIAGENDR 2 0.0000000 0.00000000 15 . .

52 4 RIDRETH1 1 -1.8516348 0.74948475 15 -2.47 0.0260

53 4 RIDRETH1 2 -0.5337351 1.34276044 15 -0.40 0.6966

54 4 RIDRETH1 3 0.2129756 0.93786598 15 0.23 0.8234

55 4 RIDRETH1 4 1.2000083 0.77380213 15 1.55 0.1418

56 4 RIDRETH1 5 0.0000000 0.00000000 15 . .

57 4 AGEC 0.1155102 0.01473853 15 7.84 <.0001

58 4 AGECSQ -0.0120925 0.00072066 15 -16.78 <.0001

59 4 BMXBMI 0.1974419 0.03480093 15 5.67 <.0001

60 4 INDFMPIR -0.1419877 0.10927231 15 -1.30 0.2134

61 5 Intercept 67.3277824 1.64788786 15 40.86 <.0001

62 5 MARCAT 1 0.2086344 0.61640150 15 0.34 0.7397

63 5 MARCAT 2 1.5618670 0.86927732 15 1.80 0.0925

64 5 MARCAT 3 0.0000000 0.00000000 15 . .

65 5 RIAGENDR 1 2.6672451 0.31354187 15 8.51 <.0001

66 5 RIAGENDR 2 0.0000000 0.00000000 15 . .

67 5 RIDRETH1 1 -1.3146555 0.73964672 15 -1.78 0.0958

68 5 RIDRETH1 2 0.1243126 1.28368906 15 0.10 0.9241

69 5 RIDRETH1 3 0.4226289 0.81428399 15 0.52 0.6113

70 5 RIDRETH1 4 1.6407827 0.74427952 15 2.20 0.0435

71 5 RIDRETH1 5 0.0000000 0.00000000 15 . .

72 5 AGEC 0.1148625 0.01249975 15 9.19 <.0001

73 5 AGECSQ -0.0119607 0.00067334 15 -17.76 <.0001

74 5 BMXBMI 0.1745127 0.03543502 15 4.92 0.0002

75 5 INDFMPIR -0.0201990 0.12778850 15 -0.16 0.8765

The MIANALYZE Procedure

Model Information

PARMS Data Set WORK.FCS_REG_OUT_1


Variance Information

Parameter

Variance

DF

Relative

Increase

in Variance

Fraction

Missing

Information

Relative

Efficiency Between Within Total

intercept 0.186136 2.604080 2.827442 12.919 0.085774 0.081859 0.983892

marcat1 0.007013 0.365682 0.374098 13.969 0.023014 0.022744 0.995472

marcat2 0.031625 0.662437 0.700388 13.407 0.057289 0.055570 0.989008

riagendr1 0.018824 0.111293 0.133882 10.971 0.202966 0.180306 0.965194

ridreth11 0.280565 0.619423 0.956101 7.2036 0.543534 0.388886 0.927836

ridreth12 0.639032 1.815435 2.582273 8.2369 0.422399 0.326039 0.938784

ridreth13 0.301759 0.854313 1.216423 8.2227 0.423862 0.326864 0.938639

ridreth14 0.238896 0.616507 0.903183 7.8418 0.464999 0.349375 0.934689

agec 0.000008238 0.000176 0.000186 13.428 0.056028 0.054386 0.989240

agecsq 4.8249212E-8 0.000000463 0.000000521 12.242 0.125112 0.116644 0.977203

bmxbmi 0.000118 0.001090 0.001231 12.158 0.130056 0.120891 0.976393

indfmpir 0.004155 0.015683 0.020669 9.3801 0.317924 0.262385 0.950140

Parameter Estimates

Parameter Estimate Std Error 95% Confidence Limits DF Minimum Maximum

intercept 67.401784 1.681500 63.76681 71.03676 12.919 67.070285 68.134212

marcat1 0.309565 0.611635 -1.00254 1.62167 13.969 0.208634 0.421737

marcat2 1.574350 0.836892 -0.22808 3.37678 13.407 1.313583 1.790821

riagendr1 2.790710 0.365899 1.98511 3.59631 10.971 2.667245 2.999808

ridreth11 -1.925659 0.977804 -4.22462 0.37330 7.2036 -2.744578 -1.314655

ridreth12 -0.447926 1.606945 -4.13508 3.23923 8.2369 -1.508435 0.521699

ridreth13 0.103828 1.102916 -2.42756 2.63522 8.2227 -0.868409 0.422629

ridreth14 1.141851 0.950359 -1.05740 3.34110 7.8418 0.354494 1.640783

agec 0.116172 0.013650 0.08678 0.14557 13.428 0.112601 0.120100

agecsq -0.011871 0.000722 -0.01344 -0.01030 12.242 -0.012092 -0.011568

bmxbmi 0.191276 0.035091 0.11493 0.26762 12.158 0.174513 0.201663

indfmpir -0.125986 0.143768 -0.44921 0.19724 9.3801 -0.191748 -0.020199

Parameter Estimates

Parameter Theta0

t for H0:

Parameter=Theta0

Pr > |t

|

intercept 0 40.08 <.0001

marcat1 0 0.51 0.6207

marcat2 0 1.88 0.0818

riagendr1 0 7.63 <.0001

ridreth11 0 -1.97 0.0884

ridreth12 0 -0.28 0.7873

ridreth13 0 0.09 0.9273

ridreth14 0 1.20 0.2646

agec 0 8.51 <.0001

The MIANALYZE Procedure

Parameter Estimates

Parameter Theta0

t for H0:

Parameter=Theta0

Pr > |t

|

agecsq 0 -16.45 <.0001

bmxbmi 0 5.45 0.0001

indfmpir 0 -0.88 0.4027

this example demonstrates use of the sas fcs (fully ... fcs imputation example.pdf · this example...

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