Description Usage Arguments Details Value Author(s) See Also Examples
The findlast function allows to find the last non-missing value in a set of columns of a data.frame object, and returns these values. You can then retrieve these last values for others sets of columns of the data.frame object.
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| data | a  | 
| from | a  | 
| to | a  | 
This function is useful when working on longitudinal data with attrition problems. It allows to retrieve the last values given by repondants in a specific time-varying variable and then getting the values for other time-varying variables according to the index of last participation of each respondant.
If the to argument is missing, the function returns the ids where the last non-missing value is for each row of the data argument.
If the to argument is given, a data.frame containing the corresponding last values on covariates is returned.
Emmanuel Rousseaux
find.value.last, find.value.fun.
| 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 | # data.frame example
fl.data.example <- data.frame(
  'age00' = c(48,NA,34,63,NA,27),
  'age01' = c(NA,27,35,64,NA, NA),
  'age02' = c(50,28,36,NA,NA, NA),
  'sex00' = c('M',NA,'F','M',NA,'M'),
  'sex01' = c(NA,'F','F',NA,NA, NA),
  'sex02' = c('M',NA,'F',NA,'M', NA),
  'nationality00' = factor(c('v1',NA,'v1','v1',NA,'o')),
  'nationality01' = factor(c(NA,'o','v2','o',NA, NA)),
  'nationality02' = factor(c('o',NA,'v2',NA,'o', NA))
)
# we get the column ids where the last non-missing value is
findlast(
  data = fl.data.example,
  from = c('age00', 'age01', 'age02')
)
# we retrieve the last value for age, and get corresponding values for the variables sex and nationality
findlast(
  data = fl.data.example,
  from = c('age00', 'age01', 'age02'),
  to = list(
    'age' = c('age00', 'age01', 'age02'),
    'sex' = c('sex00', 'sex01', 'sex02'),
    'nationality' = c('nationality00','nationality01','nationality02')
  )
)
# same operation but using column ids instead of column names
findlast(
  data = fl.data.example,
  from = 1:3,
  to = list(
    'age' = 1:3,
    'sex' = 4:6,
    'nationality' = 7:9
  )
)
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