burn_eval_1: BURN_EVAL_1 data

In aplore3: Datasets from Hosmer, Lemeshow and Sturdivant, "Applied Logistic Regression" (3rd Ed., 2013)

Description

burn_eval_1 dataset.

Usage

burn_eval_1

Format

A data.frame with 500 rows and 9 variables: the covariate are the same as those from burn1000.

Source

Hosmer, D.W., Lemeshow, S. and Sturdivant, R.X. (2013) Applied Logistic Regression, 3rd ed., New York: Wiley

Examples

head(burn_eval_1, n = 10)
summary(burn_eval_1)

Example output

   id facility death  age gender  race tbsa inh_inj flame
1   1       15 Alive 26.0   Male White 10.0      No    No
2   2       48 Alive 48.8   Male White  3.0      No   Yes
3   3       62 Alive 15.8   Male White  4.0      No    No
4   4       32 Alive 38.2   Male White  8.0      No   Yes
5   5       28 Alive  0.5   Male White  1.0      No    No
6   6       28 Alive 37.1   Male White  1.0      No    No
7   7       55 Alive 24.3   Male White  8.0      No   Yes
8   8       15 Alive 17.1   Male White 10.0      No   Yes
9   9       20 Alive 37.5   Male White  0.9      No    No
10 10       15 Alive 15.0   Male White 10.3      No   Yes
       id           facility       death          age           gender   
 Min.   :  1.0   Min.   : 1.00   Alive:428   Min.   : 0.10   Female:156  
 1st Qu.:125.8   1st Qu.:15.00   Dead : 72   1st Qu.:14.15   Male  :344  
 Median :250.5   Median :32.00               Median :35.45               
 Mean   :250.5   Mean   :32.67               Mean   :34.96               
 3rd Qu.:375.2   3rd Qu.:48.00               3rd Qu.:51.92               
 Max.   :500.0   Max.   :83.00               Max.   :89.00               
        race          tbsa         inh_inj   flame    
 Non-White:197   Min.   :  0.100   No :434   No :230  
 White    :303   1st Qu.:  2.225   Yes: 66   Yes:270  
                 Median :  6.000                      
                 Mean   : 13.762                      
                 3rd Qu.: 13.625                      
                 Max.   :100.000                      

aplore3 documentation built on May 2, 2019, 8:24 a.m.