Hello,
I have a survey data with probable dementia (yes/no) and two independent factors.
I used this logistic model and try to estimate the relative risk using log-binomial model. I am wondering how can I convert the beta estimate into relative risk (RR). I used the estimate statement to calculate the relative risk, but I am not sure about it. Does it give the relative risk. Help!!!
proc surveylogistic data=work.final;
class Immigrant (ref='0') Race (ref='1');
model prob_dementia(event='1') = Immigrant Race/link=cloglog;
weight Weight;
estimate "immigrant vs non-immigrant" Immigrant 1 -1/exp;
run;
Here is the output calculated using estimate option.
SAS Output
Analysis of Maximum Likelihood Estimates | |||||
Parameter |
| Estimate | Standard | t Value | Pr > |t| |
Intercept |
| -1.6232 | 0.0664 | -24.46 | <.0001 |
Immigrant | 1 | 0.0629 | 0.0738 | 0.85 | 0.3943 |
Race | 2 | 0.1642 | 0.0751 | 2.19 | 0.0289 |
Race | 4 | -0.2129 | 0.1208 | -1.76 | 0.0780 |
NOTE: The degrees of freedom for the t tests |
Association of Predicted Probabilities and Observed | |||
Percent Concordant | 26.0 | Somers' D | 0.031 |
Percent Discordant | 23.0 | Gamma | 0.063 |
Percent Tied | 51.0 | Tau-a | 0.009 |
Pairs | 4106232 | c | 0.515 |
Estimate | ||||||
Label | Estimate | Standard Error | DF | t Value | Pr > |t| | Exponentiated |
immigrant vs non-immigrant | 0.06287 | 0.07380 | 5226 | 0.85 | 0.3943 | 1.0649 |
The CLOGLOG link does not result in a log binomial model. See this note for estimating a relative risk based on a logistic model. You can use an ordinary logistic model (fit in PROC LOGISTIC or SURVEYLOGISTIC), and then use the NLMeans macro as shown there.
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