Binary logistic regression — blr

Binary logistic regression.

Usage

blr_regress(object, ...)

# S3 method for class 'glm'
blr_regress(object, odd_conf_limit = FALSE, ...)

Arguments

object: An object of class "formula" (or one that can be coerced to that class): a symbolic description of the model to be fitted or class glm.
...: Other inputs.
odd_conf_limit: If TRUE, odds ratio confidence limts will be displayed.

Examples

# using formula
blr_regress(object = honcomp ~ female + read + science, data = hsb2)
#>                              Model Overview                              
#> ------------------------------------------------------------------------
#> Data Set    Resp Var    Obs.    Df. Model    Df. Residual    Convergence 
#> ------------------------------------------------------------------------
#>   data      honcomp     200        199           196            TRUE     
#> ------------------------------------------------------------------------
#> 
#>                     Response Summary                     
#> --------------------------------------------------------
#> Outcome        Frequency        Outcome        Frequency 
#> --------------------------------------------------------
#>    0              147              1              53     
#> --------------------------------------------------------
#> 
#>                   Maximum Likelihood Estimates                    
#> -----------------------------------------------------------------
#>  Parameter     DF    Estimate    Std. Error    z value    Pr(>|z|) 
#> -----------------------------------------------------------------
#> (Intercept)    1     -12.7772       1.9755    -6.4677      0.0000 
#>   female1      1      1.4825        0.4474     3.3139       9e-04 
#>    read        1      0.1035        0.0258     4.0186       1e-04 
#>   science      1      0.0948        0.0305     3.1129      0.0019 
#> -----------------------------------------------------------------
#> 
#>  Association of Predicted Probabilities and Observed Responses  
#> ---------------------------------------------------------------
#> % Concordant          0.8561          Somers' D        0.7147   
#> % Discordant          0.1425          Gamma            0.7136   
#> % Tied                0.0014          Tau-a            0.2794   
#> Pairs                  7791           c                0.8568   
#> ---------------------------------------------------------------
#> 

# using a model built with glm
model <- glm(honcomp ~ female + read + science, data = hsb2,
             family = binomial(link = 'logit'))

blr_regress(model)
#>                              Model Overview                              
#> ------------------------------------------------------------------------
#> Data Set    Resp Var    Obs.    Df. Model    Df. Residual    Convergence 
#> ------------------------------------------------------------------------
#>   data      honcomp     200        199           196            TRUE     
#> ------------------------------------------------------------------------
#> 
#>                     Response Summary                     
#> --------------------------------------------------------
#> Outcome        Frequency        Outcome        Frequency 
#> --------------------------------------------------------
#>    0              147              1              53     
#> --------------------------------------------------------
#> 
#>                   Maximum Likelihood Estimates                    
#> -----------------------------------------------------------------
#>  Parameter     DF    Estimate    Std. Error    z value    Pr(>|z|) 
#> -----------------------------------------------------------------
#> (Intercept)    1     -12.7772       1.9755    -6.4677      0.0000 
#>   female1      1      1.4825        0.4474     3.3139       9e-04 
#>    read        1      0.1035        0.0258     4.0186       1e-04 
#>   science      1      0.0948        0.0305     3.1129      0.0019 
#> -----------------------------------------------------------------
#> 
#>  Association of Predicted Probabilities and Observed Responses  
#> ---------------------------------------------------------------
#> % Concordant          0.8561          Somers' D        0.7147   
#> % Discordant          0.1425          Gamma            0.7136   
#> % Tied                0.0014          Tau-a            0.2794   
#> Pairs                  7791           c                0.8568   
#> ---------------------------------------------------------------
#> 

# odds ratio estimates
blr_regress(model, odd_conf_limit = TRUE)
#>                              Model Overview                              
#> ------------------------------------------------------------------------
#> Data Set    Resp Var    Obs.    Df. Model    Df. Residual    Convergence 
#> ------------------------------------------------------------------------
#>   data      honcomp     200        199           196            TRUE     
#> ------------------------------------------------------------------------
#> 
#>                     Response Summary                     
#> --------------------------------------------------------
#> Outcome        Frequency        Outcome        Frequency 
#> --------------------------------------------------------
#>    0              147              1              53     
#> --------------------------------------------------------
#> 
#>                   Maximum Likelihood Estimates                    
#> -----------------------------------------------------------------
#>  Parameter     DF    Estimate    Std. Error    z value    Pr(>|z|) 
#> -----------------------------------------------------------------
#> (Intercept)    1     -12.7772       1.9755    -6.4677      0.0000 
#>   female1      1      1.4825        0.4474     3.3139       9e-04 
#>    read        1      0.1035        0.0258     4.0186       1e-04 
#>   science      1      0.0948        0.0305     3.1129      0.0019 
#> -----------------------------------------------------------------
#> 
#>                   Odds Ratio Estimates                    
#> ---------------------------------------------------------
#>  Effects          Estimate          95% Wald Conf. Limit 
#> ---------------------------------------------------------
#>  female1           4.4039          1.8955         11.0521 
#>    read            1.1091          1.0569          1.1699 
#>  science           1.0994          1.0377          1.1702 
#> ---------------------------------------------------------
#> 
#>  Association of Predicted Probabilities and Observed Responses  
#> ---------------------------------------------------------------
#> % Concordant          0.8561          Somers' D        0.7147   
#> % Discordant          0.1425          Gamma            0.7136   
#> % Tied                0.0014          Tau-a            0.2794   
#> Pairs                  7791           c                0.8568   
#> ---------------------------------------------------------------
#>