Hi,
I'm trying to run a proc SURVEYlogistic for a complex data, but the output looks weird. anyone has an idea what do those numbers mean? Especially the one highlighted with red.
The SURVEYLOGISTIC Procedure
Model Information | ||
Data Set | WORK.N15 |
|
Response Variable | Antibiotic |
|
Number of Response Levels | 2 |
|
Stratum Variable | VARSTR | VARIANCE ESTIMATION STRATUM - 2015 |
Number of Strata | 165 |
|
Cluster Variable | VARPSU | VARIANCE ESTIMATION PSU - 2015 |
Number of Clusters | 349 |
|
Weight Variable | PERWT | FINAL PERSON WEIGHT, 2015 |
Model | Binary Logit |
|
Optimization Technique | Fisher's Scoring |
|
Variance Adjustment | Degrees of Freedom (DF) |
|
Variance Estimation | |
Method | Taylor Series |
Missing Levels | Included (MISSING) |
Variance Adjustment | Degrees of Freedom (DF) |
Number of Observations Read | 23363 |
Number of Observations Used | 23028 |
Sum of Weights Read | 2.5812E8 |
Sum of Weights Used | 2.5812E8 |
Response Profile | |||
Ordered | Antibiotic | Total | Total |
1 | No | 21546 | 239733598 |
2 | Yes | 1482 | 18390178 |
Model Fit Statistics | ||
Criterion | Intercept Only | Intercept and |
AIC | 132597682 | 131164140 |
SC | 132597690 | 131164156 |
-2 Log L | 132597680 | 131164136 |
Testing Global Null Hypothesis: BETA=0 | |||
Test | Chi-Square | DF | Pr > ChiSq |
Likelihood Ratio | 1433543.99 | 1 | <.0001 |
Score | 757520.937 | 1 | <.0001 |
Wald | 71303.0062 | 1 | <.0001 |
Analysis of Maximum Likelihood Estimates | |||||
Parameter | DF | Estimate | Standard | Wald | Pr > ChiSq |
Intercept | 1 | -30.8434 | 0.0911 | 114655.453 | <.0001 |
PPI | 1 | 14.1581 | 0.0530 | 71303.0062 | <.0001 |
Odds Ratio Estimates | |||
Effect | Point Estimate | 95% Wald | |
PPI | >999.999 | >999.999 | >999.999 |
Association of Predicted Probabilities and Observed | |||
Percent Concordant | 4.0 | Somers' D | 0.040 |
Percent Discordant | 0.0 | Gamma | 1.000 |
Percent Tied | 96.0 | Tau-a | 0.005 |
Pairs | 31931172 | c | 0.520 |
Are there any messages in the LOG regarding convergence?
Typically with coefficient estimates that large and correspondingly small standard errors, there are convergence issues. It seems like as well that your weights are extremely large. Have you tried normalizing them?
Here is the Log description. No, I haven't normalized the weight.
NOTE: PROC SURVEYLOGISTIC is modeling the probability that Antibiotic='Yes'.
NOTE: Convergence criterion (GCONV=1E-8) satisfied.
NOTE: Only one cluster in a stratum. The estimate of variance will omit this stratum.
NOTE: Only one cluster in a stratum. The estimate of variance will omit this stratum.
NOTE: PROCEDURE SURVEYLOGISTIC used (Total process time):
real time 0.20 seconds
cpu time 0.14 seconds
Given the large disparity between the sample size and the sum of the weights, you might try normalizing the weights and see if the results make more sense.
Do you have any article or thread about data normalization? I haven't done this procedure before. I'm sorry if this is a basic question.
I will try to do that and see what will happen.
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