Germán Rodríguez
Statistics and Population Princeton University

Welcome to my home page! This website collects a number of pages related to my research and teaching. It has seven main sections dealing with courses in statistics and demography, statistical software tutorials for Stata and R, and software for producing dynamic documents with Stata.These can always be reached via the links at the top.

Biographical Notes

I was trained as a Biostatistician at the University of North Carolina at Chapel Hill, and before that obtained a Master's degree in Social Science at the University of Chicago. My undergraduate work in my native Chile was in Psychology, where I discovered my love for statistics while studying psychometrics with Erika Himmel. A job as a statistical assistant to Anibal Faundes in a fertility survey led to a life-long interest in population.

Following completion of my Ph.D. I worked for seven years at the World Fertility Survey (WFS) in London, England, once described as the largest social science project ever undertaken. I then returned home and spent five years in the Statistics Department at the Universidad Católica de Chile. In 1987 I joined the Office of Population Research at Princeton University, where I worked for thirty two years, transitioning to emeritus status in 2019. I have been lucky to interact with wonderful colleagues in all three institutions.

More extensive biographic remarks may be found in a nice write-up by a very kind colleague, who wrote them as part of the PAA "honor a colleague" fund-raiser.


My main research interest is statistical demography, the development and application of statistical modeling techniques to the study of human population, with emphasis on fertility and health.

Lately I have been doing some work on reproducible research using Stata and Markdown, writing a Stata command that allows you to produce dynamic documents that combine a narrative written in Markdown, a lightweight markup language, with Stata code. This tool makes it easy to document your work, include tables and graphs, and even quote inline results as part of the narrative, all without tedious and error-prone cutting and pasting. See the stata/markdown section with tips for getting started, documentation and examples.

As part of my work on multilevel models, I contributed an entry on Multilevel Models in Demograhy to the International Encyclopedia of Social and Behavioral Sciences. Earlier work includes a contribution to the Handbook of Multilevel Analysis edited by Jan de Leeuw and Erik Meijer, see also the multilevel section.

I have also done some work on tempo effects in fertility and mortality, noting connections with accelerated failure time models.

You can see a list of my publications in Google Scholar.


Each fall I taught a course on generalized linear models, which covers regression models for continuous data (multiple regression, analysis of variance and analysis of covariance), for binary data (including logistic regression and probit models), for count data (Poisson, over-dispersed Poisson and negative binomial models) and for time to event or survival data (mostly piece-wise exponential hazard models using the Poisson-trick). I used to include a bit on log-linear models for contingency tables, but the last few years I substituted a week on models for longitudinal and panel data, including fixed and random-effects models.

The course website includes a set of lecture notes, available in pdf format as well as html, and a collection of Stata and R logs that show how to obtain practically every result in the notes using the statistical package Stata or the R language for statistical computing and graphics. Depending on the time of the year, you also see problem sets and exams, with solutions. Sometimes I hear from students in remote corners of the globe who have found these materials useful.

Every other spring term, I also taught two half-semester courses, one on Survival Analysis and one on Multilevel Models. The corresponding sections of the website, Pop 509 and Pop 510, while less extensive than the section on GLMs, have a collection of handouts with emphasis on computation.

In the Spring of 2017 I taught Research Methods in Demography. The demography section of the website has handouts that use Stata and R to do demographic calculations organized under 12 different topics ranging from rates and standardization to stable populations. I also taught this course in 2006, 2008 and 2016.

This website also houses tutorials that provide a quick introduction to Stata and R. Both are reproducible documents, written using markstat in Stata and rmarkdown in R.


In my spare time I developed and maintained the web software used between 2002 and 2015 by the Population Association of America (PAA) to manage its annual meetings, including online submissions and reviews. The system has also been used by the International Union for the Scientific Study of Population (IUSSP), the European Association for Population Studies (EAPS), and the Union for African Population Studies (UAPS). I am particularly proud of the 2005 IUSSP site, which is available in English, French, and Spanish, with all three versions running from the same code base (written in C#), using resource strings for localization.

Updated July 2021