data.enders {miceadds}

Datasets from Enders' Missing Data Book

Description

Datasets from Enders' missing data book (2010).

Usage

data(data.enders.depression)
data(data.enders.eatingattitudes)
data(data.enders.employee)

Format

• Dataset data.enders.depression:

  'data.frame': 280 obs. of 8 variables:
$ txgroup: int 0 0 0 0 0 0 0 0 0 0 ...
$ dep1 : int 46 49 40 47 33 44 45 53 40 55 ...
$ dep2 : int 44 42 28 47 33 41 43 35 43 45 ...
$ dep3 : int 26 29 31 NA 34 34 34 35 35 36 ...
$ r2 : int 0 0 0 0 0 0 0 0 0 0 ...
$ r3 : int 0 0 0 1 0 0 0 0 0 0 ...
$ pattern: int 3 3 3 2 3 3 3 3 3 3 ...
$ dropout: int 0 0 0 1 0 0 0 0 0 0 ...
  

• Dataset data.enders.eatingattitudes:

  'data.frame': 400 obs. of 14 variables:
$ id : num 1 2 3 4 5 6 7 8 9 10 ...
$ eat1 : num 4 6 3 3 3 4 5 4 4 6 ...
$ eat2 : num 4 5 3 3 2 5 4 3 7 5 ...
$ eat10: num 4 6 2 4 3 4 4 4 6 5 ...
$ eat11: num 4 6 2 3 3 5 4 4 5 5 ...
$ eat12: num 4 6 3 4 3 4 4 4 4 6 ...
$ eat14: num 4 7 2 4 3 4 4 4 6 6 ...
$ eat24: num 3 6 3 3 3 4 4 4 4 5 ...
$ eat3 : num 4 5 3 3 4 4 3 6 4 5 ...
$ eat18: num 5 6 3 5 4 5 3 6 4 6 ...
$ eat21: num 4 5 2 4 4 4 3 5 4 5 ...
$ bmi : num 18.9 26 18.3 18.2 24.4 ...
$ wsb : num 9 13 6 5 10 7 11 8 10 12 ...
$ anx : num 11 19 8 14 7 11 12 12 14 12 ..
  

• Dataset data.enders.employee:

  'data.frame': 480 obs. of 9 variables:
$ id : num 1 2 3 4 5 6 7 8 9 10 ...
$ age : num 40 53 46 37 44 39 33 43 35 37 ...
$ tenure : num 10 14 10 8 9 10 7 9 9 10 ...
$ female : num 1 1 1 1 1 1 1 1 1 1 ...
$ wbeing : num 8 6 NA 7 NA 7 NA 7 7 5 ...
$ jobsat : num 8 5 7 NA 5 NA 5 NA 7 6 ...
$ jobperf : num 6 5 7 5 5 7 7 7 7 6 ...
$ turnover: num 0 0 0 0 0 0 0 0 1 0 ...
$ iq : num 106 93 107 94 107 118 103 106 108 97 ...
  

Source

The datasets were downloaded from https://www.appliedmissingdata.com/.

References

Enders, C. K. (2010). Applied missing data analysis. Guilford Press.