Print summaries from logistf
logistfPrint.RdPrint nice summaries from objects returned by logistf.
Value
A data frame with a row for each predictor and the following columns
- coef
log odds ratio
- exp(coef)
odds ratio
- lower
lower confidence bound of odds ratio for specified level
- upper
upper confidence bound of odds ratio for specified level
- p
p-value
Details
There is a lot of raw output from logistf, and it is not
easy to extract the coefficient table. This function provides
a convenient wrapper to return summaries from logistf.
Examples
library(logistf)
data(sex2)
fit <- logistf(case ~ age + oc + vic + vicl + vis + dia, data = sex2,
alpha = 0.1)
summary(fit)
#> logistf(formula = case ~ age + oc + vic + vicl + vis + dia, data = sex2,
#> alpha = 0.1)
#>
#> Model fitted by Penalized ML
#> Coefficients:
#> coef se(coef) lower 0.9 upper 0.9 Chisq
#> (Intercept) 0.12025405 0.4763429 -0.6673577 0.9177303 0.06286298
#> age -1.10598131 0.4149021 -1.8277045 -0.4328451 7.50773092
#> oc -0.06881673 0.4344026 -0.7986318 0.6507581 0.02467044
#> vic 2.26887464 0.5384872 1.4248338 3.2325326 22.93139022
#> vicl -2.11140817 0.5320395 -3.0613215 -1.2704704 19.10407252
#> vis -0.78831694 0.4089620 -1.4743338 -0.1137542 3.69740975
#> dia 3.09601166 1.5052197 1.0835108 6.8752016 7.89693139
#> p method
#> (Intercept) 8.020268e-01 2
#> age 6.143472e-03 2
#> oc 8.751911e-01 2
#> vic 1.678877e-06 2
#> vicl 1.237805e-05 2
#> vis 5.449701e-02 2
#> dia 4.951873e-03 2
#>
#> Method: 1-Wald, 2-Profile penalized log-likelihood, 3-None
#>
#> Likelihood ratio test=49.09064 on 6 df, p=7.15089e-09, n=239
#> Wald test = 31.96835 on 6 df, p = 1.654713e-05
## Streamlined summary
logistfPrint(fit)
#> coef exp(coef) lower 0.9 upper 0.9 p
#> (Intercept) 0.120 1.128 0.513 2.504 0.802
#> age -1.106 0.331 0.161 0.649 0.006
#> oc -0.069 0.933 0.450 1.917 0.875
#> vic 2.269 9.669 4.157 25.344 0.000
#> vicl -2.111 0.121 0.047 0.281 0.000
#> vis -0.788 0.455 0.229 0.892 0.054
#> dia 3.096 22.110 2.955 967.970 0.005