My research interests broadly fall into three areas:

Statistical demography: I develop methods to improve estimates and forecasts of demographic and health indicators in situations where the available data are sparse or unreliable. This work involves combining demographic and statistical methods to estimate outcomes in developing countries, minority populations, and in small geographic areas.

Health and mortality inequalities: I research how disparities in health and mortality outcomes are changing over time. Recent and current work involves studying the evolution of the opioid epidemic in the United States and Canada.

Using non-traditional data sources in demographic research: I focus on developing methods to overcome biases and data quality issues to take advantage of new data sources such as web and social media data, and text data.

A list of papers is also on Google Scholar.

Peer-reviewed publications

• Alexander, M., and Alkema, L., ‘A Bayesian Cohort Component Projection Model to Estimate Women of Reproductive Age at the Subnational Level in Data-Sparse Settings’, 2022, DOI: 10.¹²¹⁵⁄_00703370-10216406.
• Maheu-Giroux, M, Sardinha, L, Stockl, H, Meyer, S, Godin, A, Alexander, M., and Garcia-Moreno, C. ‘A framework to model global, regional, and national estimates of intimate partner violence’, BMC Medical Research Methodology, 2022: 22(1), 1-17.
• Susmann, H., Alexander, M., and Alkema, L., Temporal models for demographic and global health outcomes in multiple populations: Introducing a new framework to review and standardize documentation of model assumptions and facilitate model comparison, International Statistical Review, 2022, DOI: 10.1111/insr.12491.
• Alexander, M. and Root, L. ‘Competing effects on the average age of infant death’. Demography, 2022, DOI: 10.1215/ 00703370-9779784.
• Kiang MV, Tsai AC, Alexander MJ, Rehkopf DH, Basu S. ‘Racial/Ethnic Disparities in Opioid-Related Mortality in the USA, 1999–2019: the Extreme Case of Washington DC.’ J Urban Heal. Published online 2021:1-7. DOI: 10.1007/s11524-021-00573-8.
• Wilson, T., Grossman, I., Alexander, M., Rees, P., and Temple, J. ‘Methods for small area population forecasts: state-of-the-art and research needs’, Population Research and Policy Review, 2021, DOI: 10.1007/s11113-021-09671-6.
• Kiang MV, Chen JT, Krieger N, Buckee CO, Alexander M, Baker JT, Buckner RL, Coombs III G, Rich-Edwards JW, Carlson KW, & Onnela J-P. ‘Sociodemographic characteristics of missing data in digital phenotyping’. Scientific Reports. 2021;11(1):15408. DOI: 10.1038/s41598-021-94516-7.
• Alexander, M., Polimis, K., and Zagheni, E., ‘Combining social media and survey data to nowcast migrant stocks in the United States’, Population Research and Policy Review, 2020, DOI: 10.1007/s11113-020-09599-3.
• Alexander, M., Polimis, K., and Zagheni, E., ‘The impact of Hurricane Maria on out-migration from Puerto Rico: Evidence from Facebook data’, Population and Development Review, 2019, DOI: 10.1111/padr.12289.
  
• Hug, L., Alexander, M., You, D., and Alkema, L. ‘National, regional, and global levels and trends in neonatal mortality between 1990 and 2017, with scenario-based projections to 2030: a systematic analysis by the United Nations Inter-agency Group for Child Mortality Estimation’, Lancet Global Health, 2019, 7(6): 710–720.
• Kiang, M.V., Basu S., Chen J., and Alexander, M. `Assessment of Changes in the Geographical Distribution of Opioid-Related Mortality Across the United States by Opioid Type, 1999-2016’. JAMA Network Open. 2019, 2(2):e190040.
• Gemmill, A, Kiang, M.V., and Alexander, M., ‘Trends in pregnancy-associated mortality involving opioids in the United States, 2007–2016’, American Journal of Obstetrics and Gynecology, 2019, 220(1): 115-116.
• Alexander, M., Kiang, M.V., and Barbieri M., ‘Trends in Black and White Opioid Mortality in the United States, 1979–2015’, Epidemiology, 2018, 29(5): 707–715.
• Alexander, M., and Alkema, L., ‘Global Estimation of Neonatal Mortality using a Bayesian Hierarchical Splines Regression Model’, Demographic Research, 2018, 38(15): 335–372.
• Alexander, M., Zagheni, E., and Barbieri, M., ‘A Flexible Bayesian Model for Estimating Subnational Mortality’, Demography, 2017, 54(6): 2025–2041.
• Howlett, M., Gray, M., and Hunter, B., ‘Wages, government payments and other income of Indigenous and non-Indigenous Australians’, Australian Journal of Labour Economics, 2016, 19(2): 53–76.
• Hunter, B., Howlett, M., and Gray, M., ‘The Economic Impact of the Mining Boom on Indigenous and Non-Indigenous Australians’, Asia & the Pacific Policy Studies, 2015, 2(3): 517–530.
• Gray, M., Howlett, M., and Hunter, B., ‘Labour Market Outcomes for Indigenous Australians’, The Economic and Labour Relations Review, 2014, 25(3): 497–517.
• Biddle, N., Howlett, M., Hunter, B., and Paradies, Y., ‘Labour Market and Other Discrimination Facing Indigenous Australians’, Australian Journal of Labour Economics, 2013, 16(1): 91–113.

Book chapters

• Alexander, M. ‘Using social media advertising data to estimate migration trends over time’. In Big Data Applications in Geography and Planning. Edward Elgar Publishing. 2021.

Working papers, projects, and pre-prints

• Chong, M.Y.C., and Alexander, M.. ‘Estimating the timing of stillbirths in countries worldwide using a Bayesian hierarchical penalized splines regression model’.
• Alexander, M. and Root, L. ‘Racial disparities in premature births, fetal deaths and neonatal deaths: a multi-decrement lifetable approach’.
• Alexander, M., ‘Decomposing dimensions of mortality inequality’.
• Chong, M., Alburez-Gutierrez, D., Del Fava, E.,Alexander, M., & Zagheni, E. (2022). ‘Identifying and correcting bias in big crowd-sourced online genealogies.
• Alexander, M., Chong, M.Y.C., and Pejcinovska, M. ‘Estimating causes of maternal death in data-sparse contexts’.
• Alexander, M., Wildeman, C., Roehrkasse, A., and Rudlang-Perman, K. ‘Forecasting child welfare outcomes in the United States’. Shiny app; Paper presented at PAA 2022.
• Alexander, R., and Alexander, M.. ‘The Increased Effect of Elections and Changing Prime Ministers on Topics Discussed in the Australian Federal Parliament between 1901 and 2018’.
• Alexander, M., and Goldstein, J., ‘Deaths without denominators: using a matched dataset to study mortality patterns in the United States’.

Working papers where there is not so much working happening

• Alexander, M., ‘Temporal smoothers for use in demographic estimation and projection’. This paper turned into another paper (Susmann et al., above). I wrote an R package to accompany the paper, which can be found on my GitHub. One day I might translate the models from JAGS to Stan.
• Chung, P.H., and Alexander, M., ‘Kin Dependency Ratios: An Extension and Application of the Goodman Method for Estimating the Availability of Kin’.

Talks

Here are recordings of some talks:

• Using Facebook advertising data to estimate migration
• Overcoming barriers to sharing code
• Estimating subnational populations in data-sparse contexts

Code and other fun projects

• A package to fit Rogers-Castro migration models, rcbayes, is on CRAN.
• I am a contributor to the DemoTools R package.
• I made a children’s book in R called ’D is for Demography’. My toddler prefers ‘The Very Hungry Caterpillar’ or ‘Wombat Stew’.
• This repo on my GitHub has various bits and pieces of code, mostly related to mortality, but some other stuff too.
• Shiny app to explore baby names in Australia, Ontario, and USA