Good evening everyone,
I am still relatively new to SAS and I wanted to make sure I am correctly implementing and interpreting my code.
I am looking at the age (in months) that patients (<=2yo) with cleft palates undergo cleft palate repair and seeing how race, gender, location, income level, and hospital type affects the timing of that repair.
This is my code to determine the estimate age of repair by each of those variables (while controlling for one-another).
proc surveyreg data=kid.KID_complete;
class race female hosp_region zipinc hosp_locteach;
weight discwt;
where age<=2 and cleftpalateonly=1 and cleftpalaterepair=1;
model agemonth = race female hosp_region zipinc hosp_locteach/ solution;
domain race female hosp_region zipinc hosp_locteach;
Format race racef.;
Format female femalef.;
Format hosp_region regionf.;
Format zipinc zipincf.;
Format hosp_locteach hosp_locteachf.;
ods output
DataSummary=output
DomainSummary=domain
ParameterEstimates = MyParmEst;
run;
In the results, for each domain analysis, I get something like this (this is just for the domain race = white children)
The SURVEYREG Procedure | ||||
I:Race=White | ||||
Domain Regression Analysis for Variable AGEMONTH | ||||
Domain Summary | ||||
Number of Observations | 2459 | |||
Number of Observations in Domain | 1480 | |||
Number of Observations Not in Domain | 979 | |||
Sum of Weights in Domain | 2639.9 | |||
Weighted Mean of AGEMONTH | 12.56934 | |||
Weighted Sum of AGEMONTH | 33182.4 | |||
Fit Statistics | ||||
R-Square | 0.0295 | |||
Root MSE | 5.0756 | |||
Denominator DF | 2458 | |||
Tests of Model Effects | ||||
Effect | Num DF | F Value | Pr > F | |
Model | 9 | 3.24 | 0.0006 | |
Intercept | 1 | 787.25 | <.0001 | |
RACE | 0 | . | . | |
female | 1 | 0.99 | 0.3207 | |
HOSP_REGION | 3 | 4.73 | 0.0027 | |
zipinc | 3 | 3.29 | 0.0197 | |
HOSP_LOCTEACH | 2 | 0.19 | 0.8286 | |
Note: The denominator degrees of freedom for the F tests is 2458. | ||||
Estimated Regression Coefficients | ||||
Parameter | Estimate | Standard Error | t Value | Pr > |t| |
Intercept | 11.718497 | 0.369853 | 31.68 | <.0001 |
RACE Asian | 0 | 0 | . | . |
RACE Black | 0 | 0 | . | . |
RACE Hispanic | 0 | 0 | . | . |
RACE Native American | 0 | 0 | . | . |
RACE Other | 0 | 0 | . | . |
RACE White | 0 | 0 | . | . |
female Female | 0.3051803 | 0.30724 | 0.99 | 0.3207 |
female Male | 0 | 0 | . | . |
HOSP_REGION Midwest | 1.1362171 | 0.460781 | 2.47 | 0.0137 |
HOSP_REGION Northeast | -0.2683534 | 0.365375 | -0.73 | 0.4627 |
HOSP_REGION South | -0.5941962 | 0.42009 | -1.41 | 0.1574 |
HOSP_REGION West | 0 | 0 | . | . |
zipinc 25-50th | 1.2050844 | 0.404636 | 2.98 | 0.0029 |
zipinc 51-75th | 0.386581 | 0.373655 | 1.03 | 0.301 |
zipinc <25th | 0.7636029 | 0.409625 | 1.86 | 0.0624 |
zipinc >75th | 0 | 0 | . | . |
HOSP_LOCTEACH Rural | -0.2140308 | 1.106108 | -0.19 | 0.8466 |
HOSP_LOCTEACH Urban non-teaching | 0.4966877 | 0.852428 | 0.58 | 0.5602 |
HOSP_LOCTEACH Urban teaching | 0 | 0 | . | . |
Would I correct in interpreting this as:
In white children, when controlling for age, gender, location, income, and hospital type, the average age of repair is 11.7months (p<0.0001)?
Those results are unreadable. Could you please edit your message above and paste the results using the {i} icon in the editor.
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