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How to find the 95% confidence interval for the glm model in R?
To find the confidence interval for a lm model (linear regression model), we can use confint function and there is no need to pass the confidence level because the default is 95%. This can be also used for a glm model (general linear model). Check out the below examples to see the output of confint for a glm model.
Example1
> set.seed(3214) > x1<-rpois(20,5) > y1<-sample(0:1,20,replace=TRUE) > Model1<-glm(y1~x1,family="binomial") > summary(Model1)
Output
Call: glm(formula = y1 ~ x1, family = "binomial") Deviance Residuals: Min 1Q Median 3Q Max -1.6360 -1.4156 0.7800 0.8567 0.9946 Coefficients: Estimate Std. Error z value Pr(>|z|) (Intercept) 0.34851 1.17554 0.296 0.767 x1 0.09794 0.21421 0.457 0.648 (Dispersion parameter for binomial family taken to be 1) Null deviance: 24.435 on 19 degrees of freedom Residual deviance: 24.221 on 18 degrees of freedom AIC: 28.221 Number of Fisher Scoring iterations: 4 > confint(Model1) Waiting for profiling to be done... 2.5 % 97.5 % (Intercept) -1.9946211 2.8014055 x1 -0.3179604 0.5537196
Example2
> x2<-runif(200,2,5) > y2<-sample(0:1,200,replace=TRUE) > Model2<-glm(y2~x2,family="binomial") > summary(Model2)
Output
Call: glm(formula = y2 ~ x2, family = "binomial") Deviance Residuals: Min 1Q Median 3Q Max -1.162 -1.152 -1.145 1.202 1.211 Coefficients: Estimate Std. Error z value Pr(>|z|) (Intercept) -0.009208 0.631317 -0.015 0.988 x2 -0.013999 0.169522 -0.083 0.934 (Dispersion parameter for binomial family taken to be 1) Null deviance: 277.08 on 199 degrees of freedom Residual deviance: 277.07 on 198 degrees of freedom AIC: 281.07 Number of Fisher Scoring iterations: 3 > confint(Model2) Waiting for profiling to be done... 2.5 % 97.5 % (Intercept) -1.2517839 1.2317974 x2 -0.3473611 0.3192271
Example3
> x3<-runif(5000,2,5) > y3<-sample(0:1,5000,replace=TRUE) > Model3<-glm(y3~x3,family="binomial") > summary(Model3)
Output
Call: glm(formula = y3 ~ x3, family = "binomial") Deviance Residuals: Min 1Q Median 3Q Max -1.177 -1.166 -1.156 1.188 1.199 Coefficients: Estimate Std. Error z value Pr(>|z|) (Intercept) 0.03254 0.11913 0.273 0.785 x3 -0.01674 0.03288 -0.509 0.611 (Dispersion parameter for binomial family taken to be 1) Null deviance: 6930.6 on 4999 degrees of freedom Residual deviance: 6930.3 on 4998 degrees of freedom AIC: 6934.3 Number of Fisher Scoring iterations: 3 > confint(Model3) Waiting for profiling to be done... 2.5 % 97.5 % (Intercept) -0.20096508 0.2660569 x3 -0.08119495 0.0476911
Updated on: 19-Nov-2020
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