Three-channel biofam data
Biofam data from the TraMineR package converted into three channels.
A list including three sequence data sets for 2000 individuals with 16 state variables, and a separate data frame with 1 id variable, 8 covariates, and 2 weights variables.
This data is constructed from the biofam data in
the TraMineR package. Here the original state sequences are converted into three separate
data sets: children, married, and left. These include the corresponding
life states from age 15 to 30: childless or (having) children;
single, married, or divorced; and (living) with parents or
left home.
Note that the divorced state does not give information on parenthood or residence,
so a guess is made based on preceeding states.
The fourth data frame covariates is a collection of
additional variables from the original data:
idhous
|
id |
sex
|
sex |
birthyr
|
birth year |
nat_1_02
|
first nationality |
plingu02
|
language of questionnaire |
p02r01
|
religion |
p02r04
|
religious participation |
cspfaj
|
father's social status |
cspmoj
|
mother's social status |
wp00tbgp
|
weights inflating to the Swiss population |
wp00tbgs
|
weights respecting sample size |
The data is loaded by calling data(biofam3c). It was built using following code:
data("biofam" , package = "TraMineR")
biofam3c <- with(biofam, {
## Building one channel per type of event left, children or married
bf <- as.matrix(biofam[, 10:25])
children <- bf == 4 | bf == 5 | bf == 6
married <- bf == 2 | bf == 3 | bf == 6
left <- bf == 1 | bf == 3 | bf == 5 | bf == 6 | bf == 7
children[children == TRUE] <- "children"
children[children == FALSE] <- "childless"
# Divorced parents
div <- bf[(rowSums(bf == 7) > 0 & rowSums(bf == 5) > 0) |
(rowSums(bf == 7) > 0 & rowSums(bf == 6) > 0),]
children[rownames(bf)
married[married == TRUE] <- "married"
married[married == FALSE] <- "single"
married[bf == 7] <- "divorced"
left[left == TRUE] <- "left home"
left[left == FALSE] <- "with parents"
# Divorced living with parents (before divorce)
wp <- bf[(rowSums(bf == 7) > 0 & rowSums(bf == 2) > 0 &
rowSums(bf == 3) == 0 & rowSums(bf == 5) == 0 &
rowSums(bf == 6) == 0) |
(rowSums(bf == 7) > 0 & rowSums(bf == 4) > 0 &
rowSums(bf == 3) == 0 & rowSums(bf == 5) == 0 &
rowSums(bf == 6) == 0), ]
left[rownames(bf)
list("children" = children, "married" = married, "left" = left,
"covariates" = biofam[, c(1:9, 26:27)])
})biofam data constructed from the Swiss Household Panel
https://forscenter.ch/projects/swiss-household-panel/
Müller, N. S., M. Studer, G. Ritschard (2007). Classification de parcours de vie à l'aide de l'optimal matching. In XIVe Rencontre de la Société francophone de classification (SFC 2007), Paris, 5 - 7 septembre 2007, pp. 157–160.
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