Summary method for the mnl function

Summary method for the mnl function

# S3 method for mnl
summary(object, sum_check = "", conf_lev = 0.95, test_var = "", dec = 3, ...)

Arguments

object	Return value from mnl
sum_check	Optional output. "confint" to show coefficient confidence interval estimates. "rrr" to show relative risk ratios (RRRs) and confidence interval estimates.
conf_lev	Confidence level to use for coefficient and RRRs confidence intervals (.95 is the default)
test_var	Variables to evaluate in model comparison (i.e., a competing models Chi-squared test)
dec	Number of decimals to show
...	further arguments passed to or from other methods

Details

See https://radiant-rstats.github.io/docs/model/mnl.html for an example in Radiant

See also

mnl to generate the results

plot.mnl to plot the results

predict.mnl to generate predictions

plot.model.predict to plot prediction output

Examples

result <- mnl(
  ketchup,
  rvar = "choice",
  evar = c("price.heinz28", "price.heinz32", "price.heinz41", "price.hunts32"),
  lev = "heinz28"
)
#> Warning: NaNs produced
summary(result)
#> Multinomial logistic regression (MNL)
#> Data                 : ketchup
#> Response variable    : choice
#> Base level           : heinz28 in choice
#> Explanatory variables: price.heinz28, price.heinz32, price.heinz41, price.hunts32 
#> Null hyp.: there is no effect of x on choice
#> Alt. hyp.: there is an effect of x on choice
#> 
#>                          RRR coefficient std.error z.value p.value    
#>  heinz32 (Intercept)               1.564     0.740   6.452  < .001 ***
#>  heinz32 price.heinz28 1.099       0.094     0.076  14.439  < .001 ***
#>  heinz32 price.heinz32   NaN         NaN     0.135 -17.033  < .001 ***
#>  heinz32 price.heinz41   NaN         NaN     0.118  -3.182   0.001 ** 
#>  heinz32 price.hunts32 0.053      -2.934     0.103   0.516   0.606    
#>  heinz41 (Intercept)               1.560     1.092   4.358  < .001 ***
#>  heinz41 price.heinz28 0.745      -0.295     0.136   5.483  < .001 ***
#>  heinz41 price.heinz32   NaN         NaN     0.232  -1.542   0.123    
#>  heinz41 price.heinz41   NaN         NaN     0.175  -8.857  < .001 ***
#>  heinz41 price.hunts32   NaN         NaN     0.209  -1.688   0.091 .  
#>  hunts32 (Intercept)              -0.643     1.309   0.402   0.688    
#>  hunts32 price.heinz28 1.282       0.248     0.126  10.200  < .001 ***
#>  hunts32 price.heinz32 0.536      -0.623     0.246   2.185   0.029 *  
#>  hunts32 price.heinz41   NaN         NaN     0.188  -0.495   0.620    
#>  hunts32 price.hunts32   NaN         NaN     0.208 -12.789  < .001 ***
#> 
#> Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
#> 
#> Pseudo R-squared: 0.2
#> Log-likelihood: -2511.212, AIC: 5052.423, BIC: 5141.473
#> Chi-squared: 1255.653 df(14), p.value < .001 
#> Nr obs: 2,798 
#>