I did run a logistic regression model fit in R for some dataset. I can see the Coefficients per predictor via summary(model_fit), but now I need to store them in a data frame. Below are my values how I see them via summary.
Coefficients:
Estimate Std. Error z value Pr(>|z|)
(Intercept) -4.387e+00 2.734e+00 -1.605 0.1086
GDP_PER_CAP -6.888e-05 3.870e-05 -1.780 0.0751 .
CO2_PER_CAP 1.816e-01 7.255e-02 2.503 0.0123 *
PERC_ACCESS_ELECTRICITY -5.973e-03 1.291e-02 -0.463 0.6437
ATMS_PER_1E5 -5.749e-03 8.181e-03 -0.703 0.4822
PERC_INTERNET_USERS -2.146e-02 2.106e-02 -1.019 0.3083
SCIENTIFIC_ARTICLES_PER_YR 3.319e-05 1.650e-05 2.011 0.0443 *
PERC_FEMALE_SECONDARY_EDU 1.559e-01 6.428e-02 2.426 0.0153 *
PERC_FEMALE_LABOR_FORCE -1.265e-02 1.470e-02 -0.860 0.3896
PERC_FEMALE_PARLIAMENT -4.802e-02 2.087e-02 -2.301 0.0214 *
dataframe <- dataframe0 %>%
mutate(EQUAL_PAY = relevel(factor(EQUAL_PAY), "YES"))
set.seed(1)
trn_index = createDataPartition(y = dataframe$EQUAL_PAY, p = 0.80, list = FALSE)
trn_equalpay = dataframe[trn_index, ]
tst_equalpay = dataframe[-trn_index, ]
equalpay_lgr = train(EQUAL_PAY ~ .-EQUAL_WORK -COUNTRY, method = "glm",
family = binomial(link = "logit"), data = trn_equalpay,
trControl = trainControl(method = 'cv', number = 10))
???? coefficients <- summary(equalpay_lgr)