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Associate Professor Matthew Schofield

(PhD Otago)


Office: Science III, room 237
Tel +64 3 479 7779
Email matthew.schofield@otago.ac.nz

About

I am an Associate Professor in the Department of Mathematics and Statistics at the University of Otago. Before moving to Otago, I held positions at the University of Kentucky and Columbia University.

For more information please visit my personal webpage

Research Interests

My research involves the use of statistical modelling in various scientific disciplines with a focus on the use of Bayesian approaches. Recent application areas include ecology, environmental sciences, biomechanics, biological sciences and genetics.

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Publications

Schofield, M. R., Barker, R. J., Link, W. A., & Pavanato, H. (2023). Estimating population size: The importance of model and estimator choice. Biometrics. Advance online publication. doi: 10.1111/biom.13828

Pohl, A. J., Schofield, M. R., & Ferber, R. (2022). A generalised smoothing approach for continuous, planar, inverse kinematics problems. Journal of Biomechanics. Advance online publication. doi: 10.1016/j.jbiomech.2022.111158

Schofield, M. R., Maze, M. J., Crump, J. A., Rubach, M. P., Galloway, R., & Sharples, K. J. (2021). On the robustness of latent class models for diagnostic testing with no gold standard. Statistics in Medicine, 40, 4751-4763. doi: 10.1002/sim.8999

Holmes, J. B., Schofield, M. R., & Barker, R. J. (2022). Pólya‐gamma data augmentation and latent variable models for multivariate binomial data. Journal of the Royal Statistical Society: Series C, 71, 194-218. doi: 10.1111/rssc.12528

Efford, M. G., & Schofield, M. R. (2020). A spatial open-population capture-recapture model. Biometrics, 76, 394-402. doi: 10.1111/biom.13150

Schofield, M. R., Barker, R. J., Link, W. A., & Pavanato, H. (2023). Estimating population size: The importance of model and estimator choice. Biometrics. Advance online publication. doi: 10.1111/biom.13828

Journal - Research Article

Pohl, A. J., Schofield, M. R., & Ferber, R. (2022). A generalised smoothing approach for continuous, planar, inverse kinematics problems. Journal of Biomechanics. Advance online publication. doi: 10.1016/j.jbiomech.2022.111158

Journal - Research Other

Schofield, M. R., Maze, M. J., Crump, J. A., Rubach, M. P., Galloway, R., & Sharples, K. J. (2021). On the robustness of latent class models for diagnostic testing with no gold standard. Statistics in Medicine, 40, 4751-4763. doi: 10.1002/sim.8999

Journal - Research Article

Holmes, J. B., Schofield, M. R., & Barker, R. J. (2022). Pólya‐gamma data augmentation and latent variable models for multivariate binomial data. Journal of the Royal Statistical Society: Series C, 71, 194-218. doi: 10.1111/rssc.12528

Journal - Research Article

Efford, M. G., & Schofield, M. R. (2020). A spatial open-population capture-recapture model. Biometrics, 76, 394-402. doi: 10.1111/biom.13150

Journal - Research Article

Pohl, A. J., Schofield, M. R., & Ferber, R. (2021). Comparing the performance of Bayesian and least-squares approaches for inverse kinematics problems. Journal of Biomechanics, 126, 110597. doi: 10.1016/j.jbiomech.2021.110597

Journal - Research Article

Wang, T., Schofield, M., Bebbington, M., & Kiyosugi, K. (2020). Bayesian modelling of marked point processes with incomplete records: Volcanic eruptions. Journal of the Royal Statistical Society: Series C, 69(1), 109-130. doi: 10.1111/rssc.12380

Journal - Research Article

Davies, T. M., Schofield, M. R., Cornwall, J., & Sheard, P. W. (2019). Modelling multilevel spatial behaviour in binary-mark muscle fibre configurations. Annals of Applied Statistics, 13(3), 1329-1347. doi: 10.1214/18-AOAS1214

Journal - Research Article

Barker, R. J., Schofield, M. R., Link, W. A., & Sauer, J. R. (2018). On the reliability of N-mixture models for count data. Biometrics, 74(1), 369-377. doi: 10.1111/biom.12734

Journal - Research Article

Bilton, T. P., Schofield, M. R., Black, M. A., Chagné, D., Wilcox, P. L., & Dodds, K. G. (2018). Accounting for errors in low coverage high-throughput sequencing data when constructing genetic maps using biparental outcrossed populations. Genetics, 209(1), 65-76. doi: 10.1534/genetics.117.300627

Journal - Research Article

Schofield, M. R., Barker, R. J., Gelman, A., Cook, E. R., & Briffa, K. R. (2016). A model-based approach to climate reconstruction using tree-ring data. Journal of the American Statistical Association, 111(513), 93-106. doi: 10.1080/01621459.2015.1110524

Journal - Research Article

Schofield, M. R., Barker, R. J., & Gelling, N. (2018). Continuous-time capture—recapture in closed populations. Biometrics, 74(2), 626-635. doi: 10.1111/biom.12763

Journal - Research Article

Link, W. A., Schofield, M. R., Barker, R. J., & Sauer, J. R. (2018). On the robustness of N-mixture models. Ecology, 99(7), 1547-1551. doi: 10.1002/ecy.2362

Journal - Research Article

Bonner, S. J., Schofield, M. R., Noren, P., & Price, S. J. (2016). Extending the latent multinomial model with complex error processes and dynamic Markov bases. Annals of Applied Statistics, 10(1), 246-263. doi: 10.1214/15-AOAS889

Journal - Research Article

Schofield, M., & Barker, R. (2016). 50-year-old curiosities: Ancillarity and inference in capture-recapture models. Statistical Science, 31(2), 161-174. doi: 10.1214/16-STS550

Journal - Research Article

Schofield, M. R., & Barker, R. J. (2017). Model fitting and evaluation in climate reconstruction of tree-ring data: A comment on Steinschneider et al. (2017): Hierarchical regression models for dendroclimatic standardization and climate reconstruction. Dendrochronologia, 46, 77-84. doi: 10.1016/j.dendro.2017.10.004

Journal - Research Article

Schofield, M. R. (2017). Comment: Estimating abundance: A non parametric mark recapture approach for open and closed systems. Environmental & Ecological Statistics, 24(4), 587-594. doi: 10.1007/s10651-017-0382-2

Journal - Research Other

Button, C., Schofield, M., & Croft, J. (2016). Distance perception in an open water environment: Analysis of individual differences. Attention, Perception & Psychophysics, 78(3), 915-922. doi: 10.3758/s13414-015-1049-4

Journal - Research Article

Schofield, M. R., & Bonner, S. J. (2015). Connecting the latent multinomial. Biometrics, 71(4), 1070-1080. doi: 10.1111/biom.12333

Journal - Research Article

Barker, R. J., Schofield, M. R., Wright, J. A., Frantz, A. C., & Stevens, C. (2014). Closed-population capture—recapture modeling of samples drawn one at a time. Biometrics, 70(4), 775-782. doi: 10.1111/biom.12241

Journal - Research Article

Schofield, M. R., & Barker, R. J. (2014). Hierarchical modeling of abundance in closed population capture—recapture models under heterogeneity. Environmental & Ecological Statistics, 21(3), 435-451. doi: 10.1007/s10651-013-0262-3

Journal - Research Article

Bonner, S., & Schofield, M. (2014). MC(MC)MC: Exploring Monte Carlo integration within MCMC for mark—recapture models with individual covariates. Methods in Ecology & Evolution, 5(12), (pp. 1305-1315). doi: 10.1111/2041-210X.12095

Conference Contribution - Published proceedings: Full paper

Welch, K. D., Schofield, M. R., Chapman, E. G., & Harwood, J. D. (2014). Comparing rates of springtail predation by web-building spiders using Bayesian inference. Molecular Ecology, 23(15), 3814-3825. doi: 10.1111/mec.12721

Journal - Research Article

Schofield, M. R., Barker, R. J., & Taylor, P. (2013). Modeling individual specific fish length from capture—recapture data using the von Bertalanffy growth curve. Biometrics, 69(4), 1012-1021. doi: 10.1111/biom.12069

Journal - Research Article

Westneat, D. F., Schofield, M., & Wright, J. (2013). Parental behavior exhibits among individual variance, plasticity and heterogeneous residual variance. Behavioral Ecology, 24(3), 598-604. doi: 10.1093/beheco/ars207

Journal - Research Article

More publications...