I have a model with the following regression coefficient values:
(Intercept) radius perimeter compactness concavepoints
-2.3003926746 0.0743984303 -0.0111031732 -2.5826629017 5.3127565914
radius.stderr smoothness.stderr compactness.stderr concavity.stderr radius.worst
0.4256225882 16.9805981122 -3.8819567231 0.9488969352 0.1408605366
texture.worst area.worst concavity.worst symmetry.worst fractaldimension.worst
0.0105317616 -0.0009867991 0.3504860653 0.8536208289 4.7503948408
I want to make a data table with the variable names in one column, and the corresponding regression coefficient values in the other column. This is what I have tried so far:
var_names = coef(summary(model_B))[, 0]
coef_vals = coef(summary(model_B))[, 1]
data.table(Variables=c(var_names), RegressionCoefficients = c(coef_values))
But I get the following output with the 'Variables' column all NA:
Variables RegressionCoefficients
<dbl> <dbl>
NA -2.3003926746
NA 0.0743984303
NA -0.0111031732
NA -2.5826629017
NA 5.3127565914
NA 0.4256225882
NA 16.9805981122
NA -3.8819567231
NA 0.9488969352
NA 0.1408605366
Use names to access the names of the coefficients.
var_names=names(coef(model_B))
coef_vals=coef(model_B)
data.table(Variables=var_names, RegressionCoefficients=coef_vals)
Variables RegressionCoefficients
1: (Intercept) 2.984208e-16
2: radius 1.000000e+00
3: perimeter 1.000000e+00