Dr Lauren Kennedy

Dr Lauren Kennedy

Senior Lecturer

School of Mathematical Sciences

College of Science

Eligible to supervise Masters and PhD - email supervisor to discuss availability.

I am a lecturer at the University of Adelaide (Adelaide, Australia), where I work creating survey weights and thinking about non-representative data, multilevel modelling, poststratification, causal inference, Bayesian inference and all manner of other related fields to making inference from the social sciences.

Year Citation
2025 Cooper, A., Simpson, D., Kennedy, L., Forbes, C., & Vehtari, A. (2025). Cross-Validatory Model Selection for Bayesian Autoregressions with Exogenous Regressors. Bayesian Analysis, 20(2), 573-597.
DOI Scopus3 WoS2
2024 Kuh, S., Kennedy, L., Chen, Q., & Gelman, A. (2024). Using leave-one-out cross validation (LOO) in a multilevel regression and poststratification (MRP) workflow: A cautionary tale.. Stat Med, 43(5), 953-982.
DOI Scopus7 WoS6 Europe PMC2
2024 Cooper, A., Vehtari, A., Forbes, C., Simpson, D., & Kennedy, L. (2024). Bayesian cross-validation by parallel Markov chain Monte Carlo. Statistics and Computing, 34(4), 15 pages.
DOI Scopus3 WoS3
2024 Gelman, A., Hullman, J., & Kennedy, L. (2024). Causal quartets: Different ways to attain the same average treatment effect*. The American Statistician, 78(3), 1-8.
DOI Scopus6 WoS5
2024 Kolczynska, M., Bürkner, P., Kennedy, L., & Vehtari, A. (2024). Modeling public opinion over time and space: Trust in state institutions in Europe, 1989-2019. Survey Research Methods, 18(1), 1-19.
DOI Scopus5 WoS4
2022 Kuh, S., Kennedy, L., Chen, Q., & Gelman, A. (2022). Using leave-one-out cross-validation (LOO) in a multilevel regression
and poststratification (MRP) workflow: A cautionary tale.
2021 Gao, Y., Kennedy, L., Simpson, D., & Gelman, A. (2021). Improving Multilevel Regression and Poststratification with Structured Priors. Bayesian Analysis, 16(3), 719-744.
DOI Scopus29
2021 Kennedy, L., & Gelman, A. (2021). Know your population and know your model: Using model-based regression and poststratification to generalize findings beyond the observed sample.. Psychological Methods, 26(5), 547-558.
DOI Scopus21 WoS18 Europe PMC19
2019 Kennedy, L., Simpson, D., & Gelman, A. (2019). The Experiment is just as Important as the Likelihood in Understanding the Prior: a Cautionary Note on Robust Cognitive Modeling. Computational Brain and Behavior, 2(3-4), 210-217.
DOI Scopus9
2018 Langsford, S., Perfors, A., Hendrickson, A. T., Kennedy, L. A., & Navarro, D. J. (2018). Quantifying sentence acceptability measures: Reliability, bias, and variability. Glossa, 3(1), 37-1-37-34.
DOI Scopus30 WoS29
2017 Kennedy, L., Navarro, D., Perfors, A., & Briggs, N. (2017). Not every credible interval is credible: evaluating robustness in the presence of contamination in Bayesian data analysis. Behavior Research Methods, 49(6), 2219-2234.
DOI Scopus7 WoS8 Europe PMC2

Year Citation
- Gabry, J., Alexander, R., Dewi, A., & Kennedy, L. (n.d.). mrpkit: R package to run an efficient MRP workflow. [Computer Software]. https://jazzystats.com/research.html.

Year Citation
2023 Cooper, A., Vehtari, A., Forbes, C., Kennedy, L., & Simpson, D. (2023). Bayesian cross-validation by parallel Markov Chain Monte Carlo.
2023 Cooper, A., Simpson, D., Kennedy, L., Forbes, C., & Vehtari, A. (2023). Cross-validatory model selection for Bayesian autoregressions with
exogenous regressors.
2023 Gelman, A., Hullman, J., & Kennedy, L. (2023). Causal quartets: Different ways to attain the same average treatment
effect.
2023 Kennedy, L., Vehtari, A., & Gelman, A. (2023). Model validation for aggregate inferences in out-of-sample prediction.
2021 Gao, Y., Kennedy, L., & Simpson, D. (2021). Treatment effect estimation with Multilevel Regression and
Poststratification.
2020 Gelman, A., Vehtari, A., Simpson, D., Margossian, C. C., Carpenter, B., Yao, Y., . . . Modrák, M. (2020). Bayesian Workflow.
2020 Kennedy, L., Khanna, K., Simpson, D., Gelman, A., Jia, Y., & Teitler, J. (2020). Using sex and gender in survey adjustment.
2019 Gao, Y., Kennedy, L., Simpson, D., & Gelman, A. (2019). Improving multilevel regression and poststratification with structured
priors.

Date Role Research Topic Program Degree Type Student Load Student Name
2024 Co-Supervisor More than just a result: using cycle threshold values in household epidemic modelling Doctor of Philosophy Doctorate Full Time Mr Dylan John Morris
2024 Co-Supervisor More than just a result: using cycle threshold values in household epidemic modelling Doctor of Philosophy Doctorate Full Time Mr Dylan John Morris

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