LISTSERV at the University of Georgia
Menubar Imagemap
Home Browse Manage Request Manuals Register
Previous (more recent) messageNext (less recent) messagePrevious (more recent) in topicNext (less recent) in topicPrevious (more recent) by same authorNext (less recent) by same authorPrevious page (December 2008, week 4)Back to main SAS-L pageJoin or leave SAS-L (or change settings)ReplyPost a new messageSearchProportional fontNon-proportional font
Date:         Mon, 22 Dec 2008 10:07:38 -0500
Reply-To:     "Simon, Lorna" <Lorna.Simon@UMASSMED.EDU>
Sender:       "SAS(r) Discussion" <SAS-L@LISTSERV.UGA.EDU>
From:         "Simon, Lorna" <Lorna.Simon@UMASSMED.EDU>
Subject:      Help with proc mixed
Content-Type: text/plain; charset=us-ascii

I am trying to use the mixed procedure to model total costs, where total cost is collected at each one-month follow-up. The greatest number of follow-ups is 24; 75% of the sample has at least 12 months of follow-up. My data look like this: Print of concatenated dataset 09:51 Monday, December 22, 2008 1

No_health_ substance_ scattered_ time_ Obs clientid fu totalcost male insurance abuse white housing homeless age

1 1010 0 2026 1 0 0 1 . 60 51 2 1010 1 0 1 0 0 1 . 60 51 3 1010 1 0 1 0 0 1 . 60 51 4 1010 1 0 1 0 0 1 . 60 51 5 1010 1 0 1 0 0 1 . 60 51 6 1010 1 0 1 0 0 1 . 60 51 7 1010 1 0 1 0 0 1 . 60 51 8 1010 1 0 1 0 0 1 . 60 51 9 1010 1 0 1 0 0 1 . 60 51 10 1010 1 0 1 0 0 1 . 60 51 11 1010 1 0 1 0 0 1 . 60 51 12 1010 1 0 1 0 0 1 . 60 51 13 1010 1 0 1 0 0 1 . 60 51 14 1010 1 0 1 0 0 1 . 60 51 15 1010 1 0 1 0 0 1 . 60 51 16 1010 1 0 1 0 0 1 . 60 51 17 1010 1 0 1 0 0 1 . 60 51 18 1010 1 0 1 0 0 1 . 60 51 19 1010 1 0 1 0 0 1 . 60 51 20 1010 1 0 1 0 0 1 . 60 51 21 1010 1 0 1 0 0 1 . 60 51 22 1010 1 0 1 0 0 1 . 60 51 23 1010 1 0 1 0 0 1 . 60 51 24 1013 0 0 1 0 0 0 0 36 . 25 1013 1 0 1 0 0 0 0 36 . 26 1013 1 . 1 0 0 0 0 36 . 27 1013 1 0 1 0 0 0 0 36 . 28 1013 1 0 1 0 0 0 0 36 . 29 1013 1 0 1 0 0 0 0 36 . 30 1013 1 0 1 0 0 0 0 36 . 31 1013 1 0 1 0 0 0 0 36 . 32 1013 1 0 1 0 0 0 0 36 . 33 1013 1 0 1 0 0 0 0 36 . 34 1013 1 0 1 0 0 0 0 36 . 35 1013 1 0 1 0 0 0 0 36 . 36 1013 1 0 1 0 0 0 0 36 .

The variable fu denotes a follow-up visit, where 1=follow-up, 0=initial visit.

When I run the proc mixed it looks like it's only using the initial visits, as it only reads in 159 observations. Here is my output from proc mixed: Class Level Information

Class Levels Values

clientid 159 1017 1018 1021 1036 1039 1045 1065 1070 1073 1076 1077 1079 1080 1085 1093 1094 1095 1096 1099 1106 1107 1108 1109 1110 1111 1112 1114 1115 1116 1117 1118 1119 1120 1121 1123 1124 1125 2004 2006 2012 2013 2014 2015 2017 2018 2019 2023 2224 3001 3006 3007 3008 3011 3012 3014 3015 3016 3151 3152 3154 3156 3157 3301 3302 3305 3307 3309 3310 3311 3312 3313 4001 4003 4004 4027 5001 5003 5004 5005 5006 5010 5011 5012 5301 5303 5304 5306 5308 5309 5310 5311 5314 5315 5602 5604 5605 5607 5611 5612 6007 6012 6013 6014 6015 6017 716251-s 71834-G 7216838-B 7223713-V 746734-G 8001 8002 8003 8004 8005 8008 8010 8011 8013 8014 8015 8016 8017 8018 8019 9002 9013 9014 9015 9016 9017 9020 9021 9023 9024 9026 9028 9029 9030 B001 B002 B003 B004 B005 B006 B007 B008 B009 B010 B012 B013 B014 B016 B017 BH00 BH03 Z002 Z005 Z017

09:51 Monday, December 22, 2008 54

The Mixed Procedure

Dimensions

Covariance Parameters 1 Columns in X 9 Columns in Z 0 Subjects 159 Max Obs Per Subject 1

Number of Observations

Number of Observations Read 1826 Number of Observations Used 159 Number of Observations Not Used 1667

Iteration History

Iteration Evaluations -2 Res Log Like Criterion

0 1 3502.37548392 1 1 3502.37548392 0.00000000

Convergence criteria met.

Estimated R Matrix for clientid 1017

Row Col1

1 5.9692E8

09:51 Monday, December 22, 2008 55

The Mixed Procedure

Covariance Parameter Estimates

Cov Parm Subject Estimate

UN(1,1) clientid 5.9692E8

Fit Statistics

-2 Res Log Likelihood 3502.4 AIC (smaller is better) 3504.4 AICC (smaller is better) 3504.4 BIC (smaller is better) 3507.4

Null Model Likelihood Ratio Test

DF Chi-Square Pr > ChiSq

0 0.00 1.0000

Solution for Fixed Effects

Standard Effect Estimate Error DF t Value Pr > |t|

Intercept 20087 10923 150 1.84 0.0679 male -6492.44 4914.47 150 -1.32 0.1885 No_health_insurance -12402 11161 150 -1.11 0.2683 substance_abuse 4894.27 4539.70 150 1.08 0.2827 white 1528.88 4936.32 150 0.31 0.7572 ethnicity 1183.47 8998.36 150 0.13 0.8955 scattered_housing 5924.68 4005.03 150 1.48 0.1412 time_homeless 86.0865 25.7034 150 3.35 0.0010 age -195.33 195.19 150 -1.00 0.3186

Here is my syntax for the mixed procedure: proc mixed; class clientid; model totalcost=male no_health_insurance substance_abuse white ethnicity scattered_housing time_homeless age/s; repeated/type=un subject=clientid r; title; run;

Any help would be appreciated. I followed the example from sas help, so I don't know why it isn't using all the observations.


Back to: Top of message | Previous page | Main SAS-L page