I have survey data and I want to do a bivariate logistic regression of age categories (18-29, 30-39, 40-49, 50+) on PrEP usage (yes, no). Here is my code below
proc surveylogistic data=dataname;
class AgeCat;
model takePrEP= AgeCat;
run;
I want to report the p-value, odds ratios, and confidence intervals for the AgeCat variable. Here is my output for this code. My questions are: what p-value would I report? Am I missing something in my code?
Model Convergence Status
Convergence criterion (GCONV=1E-8) satisfied.
Model Fit Statistics
Criterion
Intercept Only
Intercept and Covariates
AIC
147.059
150.391
SC
150.252
163.163
-2 Log L
145.059
142.391
Testing Global Null Hypothesis: BETA=0
Test
F Value
Num DF
Den DF
Pr > F
Likelihood Ratio
0.89
3
177
0.4479
Score
0.85
3
177
0.4666
Wald
0.86
3
177
0.4646
Type 3 Analysis of Effects
Effect
F Value
Num DF
Den DF
Pr > F
AgeCat
0.86
3
177
0.4646
Analysis of Maximum Likelihood Estimates
Parameter
Estimate
Standard Error
t Value
Pr > |t|
NOTE: The degrees of freedom for the t tests is 179.
Intercept
1.6129
0.2857
5.65
<.0001
AgeCat
1
0.5619
0.3722
1.51
0.1329
AgeCat
2
-0.0442
0.3787
-0.12
0.9071
AgeCat
3
-0.4089
0.5506
-0.74
0.4587
Odds Ratio Estimates
Effect
Point Estimate
95% Confidence Limits
NOTE: The degrees of freedom in computing the confidence limits is 179.
AgeCat 1 vs 4
1.956
0.359
10.664
AgeCat 2 vs 4
1.067
0.193
5.882
AgeCat 3 vs 4
0.741
0.096
5.694
Association of Predicted Probabilities and Observed Responses
Percent Concordant
41.0
Somers' D
0.182
Percent Discordant
22.7
Gamma
0.287
Percent Tied
36.3
Tau-a
0.044
Pairs
3875
c
0.591
... View more