# list.coef

Regression models for limited dependent variables are interpreted in several different ways. The estimated coefficients are often transformed before being interpreted, for example. Exponentiating logistic or count regression coefficients is common, as is converting the coefficient into percent change. The list.coef function transforms model coefficients into these additional quantities. It also reports confidence intervals for exponentiated coefficients. Users may specify the # of decimal places to report and the alpha level. For example:

    library(catregs)
    data("Mize19AH")
    m1 <- glm(alcB ~woman*parrole + age + race2 + race3 + race4 + income + ed1 + ed2 + ed3 + ed4,family="binomial",data=Mize19AH)
    list.coef(m1)

    ##        variables      b    SE      z     ll     ul p.val  exp.b ll.exp.b
    ## 1    (Intercept)  2.627 0.544  4.827  1.560  3.694 0.000 13.836    4.761
    ## 2          woman -0.284 0.095 -2.999 -0.470 -0.098 0.004  0.753    0.625
    ## 3        parrole -0.482 0.105 -4.568 -0.688 -0.275 0.000  0.618    0.502
    ## 4            age -0.086 0.019 -4.603 -0.123 -0.049 0.000  0.917    0.884
    ## 5          race2 -0.445 0.078 -5.726 -0.598 -0.293 0.000  0.641    0.550
    ## 6          race3  0.284 0.443  0.641 -0.584  1.152 0.325  1.328    0.557
    ## 7          race4 -0.153 0.197 -0.778 -0.539  0.233 0.295  0.858    0.583
    ## 8         income  0.008 0.001  5.505  0.005  0.011 0.000  1.008    1.005
    ## 9            ed1  0.460 0.153  3.006  0.160  0.760 0.004  1.584    1.173
    ## 10           ed2  0.610 0.143  4.256  0.329  0.891 0.000  1.840    1.390
    ## 11           ed3  0.765 0.154  4.967  0.463  1.067 0.000  2.150    1.589
    ## 12           ed4  0.680 0.177  3.833  0.332  1.028 0.000  1.974    1.394
    ## 13 woman:parrole -0.215 0.138 -1.561 -0.486  0.055 0.118  0.806    0.615
    ##    ul.exp.b  percent   CI
    ## 1    40.205 1283.553 95 %
    ## 2     0.906  -24.723 95 %
    ## 3     0.760  -38.228 95 %
    ## 4     0.952   -8.253 95 %
    ## 5     0.746  -35.933 95 %
    ## 6     3.166   32.842 95 %
    ## 7     1.262  -14.202 95 %
    ## 8     1.011    0.798 95 %
    ## 9     2.137   58.371 95 %
    ## 10    2.437   84.042 95 %
    ## 11    2.908  114.969 95 %
    ## 12    2.795   97.413 95 %
    ## 13    1.057  -19.368 95 %

In the above, b refers to the original model coefficient, S.E. to the estimated model coefficient’s standard error, Z is the z-statistic (b/se(b)), LL.CI is the lower limit of the confidence interval around the model coefficient, UL.CI is the upper limit of the confidence interval around the model coefficient, p-val is the p-value associated with the z-statistic, exp.b is the exponentiated model coefficient, LL.CI.for.exp.b is the lower limit of the confidence interval around the exponentiated model coefficient, UL.CI.for.exp.b is the upper limit of the confidence interval around the exponentiated model coefficient, Percent is the % change interpretation of the coefficient, i.e., 100*(1-(exp(b))), and CI is the amount of confidence in the confidence interval.