leaves: Synthetic data on fathers' parental leaves in Finland

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

Synthetic data on fathers' parental leaves in Finland

Description

Synthetic data on fathers' parental leaves in Finland

Format

A data.table with 9281 rows and 9 variables

Details

The leaves data is a synthetic version of the Finnish fathers' leave-taking data used in Helske et al. (2024) and Helske (2025). The data consists of variables

• workplace: Workplace ID.

• father: father ID within workplace. More accurately, this is the birth of a child, i.e. same father can have multiple entries in data, but each entry has separate ID.

• year: Year when the child was born.

• leave: Factor of leave-taking of the father.

• Occupation: Factor of skill level of the father's occupation

• reform2013: Factor indicating whether the father was eligible for the leave under the 2013 reform.

• same_occupation: Logical value, TRUE if father had same occupation as the previous father.

• lag_reform2013: Factor indicating whether the previous father was eligible for the reform.

• lag_occupation: Factor indiciting the occupation of previous father.

References

Helske S, Helske J, Chapman SN, Kotimäki S, Salin M, and Tikka S (2024). Heterogeneous workplace peer effects in fathers’ parental leave uptake in Finland. doi: 10.31235/osf.io/p3chf Helske J (2025). Feedback-augmented Non-homogeneous Hidden Markov Models for Longitudinal Causal Inference. ArXiv preprint. doi:10.48550/arXiv.2503.16014

Examples

data("leaves")
head(leaves)
# convert to stslist
leaves_sequences <- data_to_stslist(
  leaves, id = "workplace", time = "father", responses = "leave",
  seqdef_args = list(cpal = c("tomato", "navyblue", "goldenrod"))
)
stacked_sequence_plot(leaves_sequences)

seqHMM documentation built on June 8, 2025, 10:16 a.m.