demokin

DemoKin estimates kinship distribution by type and age

https://github.com/ivanwilli/demokin

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DemoKin estimates kinship distribution by type and age

README.Rmd

---
output: github_document
---



```{r, include = FALSE}
knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>",
  fig.path = "man/figures/README-",
  out.width = "100%"
)
pkgload::load_all()
library(knitr)
```

# DemoKin 

::: {.columns}
::: {.column width="30%"}



:::
::: {.column width="70%"}

This is an R package for the demographic analysis of kinship networks using matrix-based models.  
It implements methods developed initially by [Caswell (2019)](https://www.demographic-research.org/articles/volume/41/24), and continued in successive papers (like [Caswell (2020)](https://www.demographic-research.org/articles/volume/42/38) or [Caswell (2024)](https://www.demographic-research.org/articles/volume/49/41)) for estimating the number and age distribution of relatives under various demographic assumptions.

:::
:::

## Features

- Estimate kin counts and age distributions for various types of relatives
- Support for one-sex and two-sex models
- Time-invariant and time-varying approaches
- Multi-state models incorporating additional variables like parity or education
- Visualization tools for kinship networks

## Installation

You can install the development version of DemoKin from GitHub:

```{r, eval = F}
# install.packages("remotes")
remotes::install_github("IvanWilli/DemoKin")
library(DemoKin)
```

## Usage

Here's a basic example of how to use DemoKin:

```{r, eval = T, warning=FALSE, message=F, dev="svg", fig.width=6, fig.height=4, out.width="70%"}

# Run a one-sex time-invariant kinship model using Swedish data from 2015
kin_results <- kin(
  p = swe_px[,"2015"],        # Survival probabilities
  f = swe_asfr[,"2015"],      # Fertility rates
  time_invariant = TRUE       # Use time-invariant model
)

# Visualize the expected number of living relatives by age
kin_results$kin_summary %>%
  rename_kin() %>%
  ggplot2::ggplot(ggplot2::aes(age_focal, count_living)) +
  ggplot2::geom_line() +
  ggplot2::facet_wrap(~kin_label, scales = "free_y") +
  ggplot2::labs(
    title = "Expected number of living relatives by age",
    x = "Age of focal individual",
    y = "Number of relatives"
  )
```

## Documentation

For detailed documentation, please visit the [DemoKin website](https://ivanwilli.github.io/DemoKin/).

The site includes several vignettes demonstrating different types of kinship models:

### Models stratified by age
- [One-sex time-invariant kinship model](https://ivanwilli.github.io/DemoKin/articles/1_1_OneSex_TimeInvariant_Age.html)
- [One-sex time-varying kinship model](https://ivanwilli.github.io/DemoKin/articles/1_2_OneSex_TimeVarying_Age.html)
- [Two-sex time-invariant kinship model](https://ivanwilli.github.io/DemoKin/articles/1_3_TwoSex_TimeInvariant_Age.html)
- [Two-sex time-varying kinship model](https://ivanwilli.github.io/DemoKin/articles/1_4_TwoSex_TimeVarying_Age.html)

### Models stratified by age and stage
- [One-sex time-invariant multi-state model](https://ivanwilli.github.io/DemoKin/articles/2_1_OneSex_TimeInvariant_AgeStage.html)
- [Two-sex time-varying multi-state model](https://ivanwilli.github.io/DemoKin/articles/2_2_TwoSex_TimeVarying_AgeStage.html)

## Contributors

`DemoKin` has benefited from the work of many people over the years, including:

- **Ivan Williams** (University of Buenos Aires) leads the technical development of `DemoKin` with a particular focus on the implementation of the functions in R.

- **Diego Alburez-Gutierrez** (Max Planck Institute for Demographic Research) coordinates the development of the package.

- **Hal Caswell** (University of Amsterdam) provided crucial MATLAB code for computing matrix kinship models.

- **Xi Song** (University of Pennsylvania) contributed the code to estimate time variant kinship models.

- **Benjamin Schlüter** (University of Toronto) contributed code to implement bereavement analysis by cause of death.

- **Joe Butterick** (University of Southampton) contributed code to implement time-variant, two-sex  multistate kinship models.

- **Jason Hilton** (University of Southampton) contributed code to implement time-variant, two-sex multistate kinship models.

- **Sha Jiang** (Max Planck Institute for Demographic Research) helped create and organise the documention for the package, including developing the package’s website.

- **Amanda Martins** (Max Planck Institute for Demographic Research) developed materials for teaching DemoKin, including a course at the [European Doctoral School of Demography]( https://amandamartinsal.github.io/EDSD_kinship_24-25/).

## Citation

Williams, Iván; Alburez-Gutierrez, Diego; and the DemoKin team. (2021) DemoKin: An R package to implement demographic matrix kinship models. URL: https://github.com/IvanWilli/DemoKin.

## Acknowledgments

We thank Silvia Leek from the Max Planck Institute for Demographic Research for designing the DemoKin logo. The logo includes elements that have been taken or adapted [from this file](https://commons.wikimedia.org/wiki/File:Escudo_de_la_Orden_de_San_Jer%C3%B3nimo.svg), originally by Ansunando, [CC BY-SA 4.0](https://creativecommons.org/licenses/by-sa/4.0) via Wikimedia Commons. Sha Jiang provided useful comments for improving the package.

## Get involved!
  
`DemoKin` is under constant development.
If you're interested in contributing, please get in touch, create an [issue](https://github.com/IvanWilli/DemoKin/issues), or submit a pull request.
We look forward to hearing from you!

## License

This project is licensed under the MIT License - see the LICENSE file for details.

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