Summary method for logistic regression results

Creates a summary object that produces detailed output when printed, including omnibus test, model summary, Hosmer-Lemeshow test, classification table, and coefficient table.

Usage

# S3 method for class 'logistic_regression'
summary(
  object,
  omnibus_test = TRUE,
  model_summary = TRUE,
  hosmer_lemeshow = TRUE,
  classification = TRUE,
  coefficients = TRUE,
  digits = 3,
  ...
)

Arguments

object

A logistic_regression result object.

omnibus_test

Logical. Show omnibus test of model coefficients? (Default: TRUE)

model_summary

Logical. Show model summary (pseudo R-squared)? (Default: TRUE)

hosmer_lemeshow

Logical. Show Hosmer-Lemeshow test? (Default: TRUE)

classification

Logical. Show classification table? (Default: TRUE)

coefficients

Logical. Show coefficients table? (Default: TRUE)

digits

Number of decimal places for formatting (Default: 3).

...

Additional arguments (not used).

Value

A summary.logistic_regression object.

See also

logistic_regression for the main analysis function.

Examples

survey_data$high_satisfaction <- ifelse(survey_data$life_satisfaction >= 4, 1, 0)
result <- logistic_regression(survey_data, high_satisfaction ~ age + income)
summary(result)
#> 
#> Logistic Regression Results
#> ---------------------------
#> - Formula: high_satisfaction ~ age + income
#> - Method: ENTER
#> - N: 2115
#> 
#>   Dependent Variable Encoding
#>   ------------------------------
#>   Original Value  Internal Value
#>   ------------------------------
#>   0                            0
#>   1                            1
#>   ------------------------------
#> 
#>   Omnibus Tests of Model Coefficients
#>   ---------------------------------
#>          Chi-square  df   Sig.     
#>   ---------------------------------
#>   Model     357.432   2  <.001  ***
#>   ---------------------------------
#> 
#>   Model Summary
#>   -------------------------------
#>   -2 Log Likelihood      2520.010
#>   Cox & Snell R Square      0.155
#>   Nagelkerke R Square       0.209
#>   McFadden R Square         0.124
#>   -------------------------------
#> 
#>   Hosmer and Lemeshow Test
#>   ------------------------
#>      Chi-square  df   Sig.
#>   ------------------------
#>         150.764   8  <.001
#>   ------------------------
#> 
#>   Classification Table (cutoff = 0.50; rows: observed, columns: predicted)
#>   ---------------------------------------
#>   Observed              0    1  % Correct
#>   ---------------------------------------
#>   0                   508  380       57.2
#>   1                   289  938       76.4
#>   Overall Percentage                 68.4
#>   ---------------------------------------
#> 
#>   Variables in the Equation
#>   ------------------------------------------------------------------------------------------
#>   Term              B      S.E.     Wald  df   Sig.  Exp(B)  95% CI Lower  95% CI Upper     
#>   ------------------------------------------------------------------------------------------
#>   (Intercept)  -2.252     0.212  112.868   1  <.001   0.105                              ***
#>   age           0.001     0.003    0.174   1   .677   1.001         0.996         1.007     
#>   income        0.001  4.26e-05  268.118   1  <.001  1.0007        1.0006        1.0008  ***
#>   ------------------------------------------------------------------------------------------
#> 
#> Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05
summary(result, classification = FALSE)
#> 
#> Logistic Regression Results
#> ---------------------------
#> - Formula: high_satisfaction ~ age + income
#> - Method: ENTER
#> - N: 2115
#> 
#>   Dependent Variable Encoding
#>   ------------------------------
#>   Original Value  Internal Value
#>   ------------------------------
#>   0                            0
#>   1                            1
#>   ------------------------------
#> 
#>   Omnibus Tests of Model Coefficients
#>   ---------------------------------
#>          Chi-square  df   Sig.     
#>   ---------------------------------
#>   Model     357.432   2  <.001  ***
#>   ---------------------------------
#> 
#>   Model Summary
#>   -------------------------------
#>   -2 Log Likelihood      2520.010
#>   Cox & Snell R Square      0.155
#>   Nagelkerke R Square       0.209
#>   McFadden R Square         0.124
#>   -------------------------------
#> 
#>   Hosmer and Lemeshow Test
#>   ------------------------
#>      Chi-square  df   Sig.
#>   ------------------------
#>         150.764   8  <.001
#>   ------------------------
#> 
#>   Variables in the Equation
#>   ------------------------------------------------------------------------------------------
#>   Term              B      S.E.     Wald  df   Sig.  Exp(B)  95% CI Lower  95% CI Upper     
#>   ------------------------------------------------------------------------------------------
#>   (Intercept)  -2.252     0.212  112.868   1  <.001   0.105                              ***
#>   age           0.001     0.003    0.174   1   .677   1.001         0.996         1.007     
#>   income        0.001  4.26e-05  268.118   1  <.001  1.0007        1.0006        1.0008  ***
#>   ------------------------------------------------------------------------------------------
#> 
#> Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05