biofam3c: Three-channel biofam data

In seqHMM: Mixture Hidden Markov Models for Social Sequence Data and Other Multivariate, Multichannel Categorical Time Series

Three-channel biofam data

Description

Biofam data from the TraMineR package converted into three channels.

Format

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 weight variables.

Details

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) %in% rownames(div) & bf == 7] <- "children"

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) %in% rownames(wp) & bf == 7] <- "with parents"

list("children" = children, "married" = married, "left" = left,
  "covariates" = biofam[, c(1:9, 26:27)])
})

Source

biofam data constructed from the Swiss Household Panel https://forscenter.ch/projects/swiss-household-panel/

References

Müller, N. S., M. Studer, G. Ritschard (2007). Classification de parcours de vie à l'aide de l'optimal matching. In XIVe Rencontre de l a Société francophone de classification (SFC 2007), Paris, 5 - 7 septembre 2007, pp. 157–160.

seqHMM documentation built on July 9, 2023, 6:35 p.m.