logregR2: Logistic regression model statistics

In poliscidata: Datasets and Functions Featured in Pollock and Edwards, an R Companion to Essentials of Political Analysis, Second Edition

Description

Logistic regression model statistics

Usage

logregR2(model, digits = 3)

Arguments

model	An estimated logistic regression model
digits	Number of digits to be displayed after decimal points

Value

Returns list of statistics about model (a "LogRegR2" class object)

Examples

   library(poliscidata)
   obama_state_model <- glm(obama_win12 ~ secularism + gunlaw_rank, data=states, family=binomial)
   summary(obama_state_model)
   logregR2(obama_state_model)
   
   obama_vote_model <- svyglm(obama_vote ~ ft_dem, design=nesD, family="quasibinomial")
   summary(obama_vote_model)
   logregR2(obama_vote_model)

Example output

Call:
glm(formula = obama_win12 ~ secularism + gunlaw_rank, family = binomial, 
    data = states)

Deviance Residuals: 
     Min        1Q    Median        3Q       Max  
-1.50562  -0.20026   0.03132   0.21780   2.42177  

Coefficients:
            Estimate Std. Error z value Pr(>|z|)   
(Intercept)  1.21467    1.80898   0.671  0.50192   
secularism   0.04126    0.01513   2.728  0.00638 **
gunlaw_rank -0.20996    0.06853  -3.064  0.00219 **
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

(Dispersion parameter for binomial family taken to be 1)

    Null deviance: 69.235  on 49  degrees of freedom
Residual deviance: 20.210  on 47  degrees of freedom
AIC: 26.21

Number of Fisher Scoring iterations: 7

Chi2                 49.024 
Df                   2 
Sig.                 <.001 
Cox and Snell Index  0.625 
Nagelkerke Index     0.834 
McFadden's R2        0.708 

Call:
svyglm(formula = ...)

Survey design:
survey::svydesign(id = ~1, data = nes, weights = ~wt)

Coefficients:
             Estimate Std. Error t value Pr(>|t|)    
(Intercept) -4.665066   0.290913  -16.04   <2e-16 ***
ft_dem       0.093648   0.005256   17.82   <2e-16 ***
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

(Dispersion parameter for quasibinomial family taken to be 1.553351)

Number of Fisher Scoring iterations: 6

Chi2                 2698.382 
Df                   1 
Sig.                 <.001 
Cox and Snell Index  0.476 
Nagelkerke Index     0.645 
McFadden's R2        0.483 

poliscidata documentation built on July 8, 2020, 6:23 p.m.