Dr Kristen Hunter

Dr Kristen Hunter

  • Ph.D in Statistics, Harvard University (2022)
  • B.A. in Statistics, Harvard University (2012)
School of Mathematics & Statistics

Lecturer in Statistics and Data Science.

I am an applied and methodological statistician with particular expertise in causal inference.  I am actively seeking collaborative projects related to environmental policy and climate change.

Personal website: https://web.maths.unsw.edu.au/~khunter/

School of Mathematics and Statistics UNSW Sydney NSW 2052 The Red Centre Room 2074
  • Journal articles | 2022
    Hunter KB; Glickman ME; Campos LF, 2022, 'Inferring medication adherence from time-varying health measures', Statistics in Medicine, 41, pp. 2205 - 2226, http://dx.doi.org/10.1002/sim.9351
    Journal articles | 2021
    Campos LF; Glickman ME; Hunter KB, 2021, 'Measuring effects of medication adherence on time-varying health outcomes using Bayesian dynamic linear models', BIOSTATISTICS, 22, pp. 662 - 683, http://dx.doi.org/10.1093/biostatistics/kxz059
  • Preprints | 2022
    Pashley NE; Hunter KB; McKeough K; Rubin DB; Dasgupta T, 2022, Causal inference from treatment-control studies having an additional factor with unknown assignment mechanism, , http://arxiv.org/abs/2202.03533v1
    Preprints | 2021
    Hunter K; Miratrix L; Porter K, 2021, Power Under Multiplicity Project (PUMP): Estimating Power, Minimum Detectable Effect Size, and Sample Size When Adjusting for Multiple Outcomes in Multi-level Experiments, , http://arxiv.org/abs/2112.15273v3
    Preprints | 2021
    Hunter KB; Glickman ME; Campos LF, 2021, Inferring medication adherence from time-varying health measures, , http://arxiv.org/abs/2104.11651v1
    Preprints | 2021
    Hunter KB; Koenig K; Bind M-A, 2021, Conceptualizing experimental controls using the potential outcomes framework, , http://arxiv.org/abs/2104.10302v1


I conduct applied and methodological research in causal inference, which is the design and analysis of experiments and observational studies.  My methodological work includes power analyses, simulation studies, applied Bayesian analysis, and the use of negative and positive controls in experimental design.  My previous areas of application include education, healthcare, basic science, and genetics.


Research goals

My future research agenda is to apply statistics, in particular causal inference techniques, to pressing problems in environmental and climate change science.  I am actively looking for collaborators and projects where I can provide statistical expertise to help solve environmental challenges.  I do not have much experience in the area of environmental research, but I am willing to learn and hoping to contribute.