Members' published software

Jeronimo O. Muniz (Universidade Federal de Minas Gerais, UFMG) has published two Stata software packages for demographic estimation:

mslt - The mslt command calculates the functions of a multistate life table and plots a graph of conditional and unconditional life expectancies by time. The command provides linear and exponential solutions to estimate the number of individuals, transitions, probabilities, person-years, and years of life in a given cohort and state of occupancy. The input data are time-specific transition rates (or survivorship proportions) between nonabsorbing and at most one absorbing state. In addition to the mean age at transfer between states, mslt calculates the following summary measures: the mean age, the probability of dying, the average duration, and the proportion of life spent in a specific state.

• Muniz, J. O. (2020). Multistate life tables using Stata. The Stata Journal, 20(3), 721-745. https://doi.org/10.1177/1536867X20953577

ilt - One way to estimate mortality in countries with incomplete data is to utilize intercensal methods, which do not require model life tables and provide accurate results even in the presence of age distortions and death underregistration. In this article, I revisit three of these techniques (census based, death distribution, and an iterative procedure) and introduce ilt, a command to calculate singledecrement life tables and the net flow of migrants by age. The required inputs are two age-specific population distributions and the average number of deaths between them. The empirical example draws on data from Vietnam, but the methods are extendable to any context and period.

• Muniz, J. O. (2023). Iterative intercensal single-decrement life tables using Stata. The Stata Journal, 23(3), 813-834. https://doi.org/10.1177/1536867X231196441

Frans Willekens (Netherlands Interdisciplinary Demographic Institute, NIDI) published 2 packages on the R Archive Network (CRAN). 
 

VirtualPop - The package uses a demographic model, microsimulation techniques and data on mortality and fertility to generate a virtual population of several generations. Death rates are from the Human Mortality Database and parity-specific fertility rates from the Human Fertility Database. The virtual population is fully consistent with the empirical rates used. The package comes with 4 papers (vignettes). Two describe the simulation method, which is rooted in survival and life history analysis. One paper discusses the validity of the simulation by comparing family structures and kinship networks in the virtual population with empirical data. Simulations are compared with data from the U.S. Current Population Survey are used. The fourth paper is a tutorial. The vignettes are R markdown documents, which integrate text, R code and results. The publication of descriptions of method and analysis with data and computer code makes research fully reproducible.  

Families has several easy-to-use functions to explore family structures and kinship networks in the virtual population. The functions are described in the user’s manual and the vignette included in the package. The vignette also describes kin structures in the virtual population and addresses two relatively new subjects in demography: the demography of grandparenthood and the double burden for young children and ageing parents. Virtual populations that mimic real populations offer unique opportunities to resolve issues of limited data and to study complex networks in real populations.

The two packages made the top 40 R packages published in a month in all disciplines in the natural, life and social sciences (VirtualPop in June and Families in July).