Dr Lauren Kennedy

Lecturer

School of Computer and Mathematical Sciences

Faculty of Sciences, Engineering and Technology


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.

  • Journals

    Year Citation
    2024 Kołczyńska, M., Bürkner, P. C., 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
    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. Statistics in Medicine, 43(5), 953-982.
    DOI
    2023 Gelman, A., Hullman, J., & Kennedy, L. (2023). Causal Quartets: Different Ways to Attain the Same Average Treatment Effect. American Statistician, 6 pages.
    DOI Scopus2
    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
    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 Scopus13 WoS5 Europe PMC8
    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 & Behavior, 2(3-4), 210-217.
    DOI
    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 Scopus19 WoS16
    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 Scopus5 WoS4 Europe PMC1
  • Software

    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.
  • Preprint

    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.
  • Position: Lecturer
  • Phone: 83132314
  • Email: lauren.a.kennedy@adelaide.edu.au
  • Fax: 83133770
  • Campus: North Terrace
  • Building: Ingkarni Wardli, floor Level Six
  • Room: 6.56
  • Org Unit: Mathematical Sciences

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