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Research

Dr Robin Mitra

Formerly at Lancaster University

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  1. Published

    Estimating propensity scores with missing covariate data using general location mixture models

    Mitra, R. & Reiter, J. P., 15/03/2011, In: Statistics in Medicine. 30, 6, p. 627-641 15 p.

    Research output: Contribution to Journal/Magazine › Journal article › peer-review

  2. Published

    Two-level stochastic search variable selection in GLMs with missing predictors

    Mitra, R. & Dunson, D., 1/01/2010, In: International Journal of Biostatistics. 6, 1

    Research output: Contribution to Journal/Magazine › Journal article › peer-review

  3. Published

    Propensity score matching with missing covariates via iterated, sequential multiple imputation

    Mitra, R. & Reiter, J. P., 1/04/2011.

    Research output: Working paper

  4. Published

    Estimating propensity scores with missing covariate data using general location mixture models

    Mitra, R. & Reiter, J. P., 1/08/2009.

    Research output: Working paper

  5. Published

    Two level stochastic search variable selection in GLMs with missing predictors

    Mitra, R. & Dunson, D. D., 1/02/2009.

    Research output: Working paper

  6. Published

    Multiply imputing missing values arising by design in transplant survival data

    Mitra, R., Kimber, A., Pankhurst, L. & Collett, D., 1/09/2020, In: Biometrical Journal. 62, 5, p. 1192-1207 16 p.

    Research output: Contribution to Journal/Magazine › Journal article › peer-review

  7. Published

    Confidentiality challenges in releasing longitudinally linked data

    Mitra, R., Blanchard, S., Dove, I., Tudor, C. & Spicer, K., 2020, In: Transactions on Data Privacy. 13, 2, p. 151-170 20 p.

    Research output: Contribution to Journal/Magazine › Journal article › peer-review

  8. Published

    A latent class model to multiply impute missing treatment indicators in observational studies when inferences of the treatment effect are made using propensity score matching

    Mitra, R., 31/03/2023, In: Biometrical Journal. 65, 3, 17 p., 2100284.

    Research output: Contribution to Journal/Magazine › Journal article › peer-review

  9. Published

    Learning from data with structured missingness

    Mitra, R., McGough, S. F., Chakraborti, T., Holmes, C., Copping, R., Hagenbuch, N., Biedermann, S., Noonan, J., Lehmann, B., Shenvi, A., Doan, X. V., Leslie, D., Bianconi, G., Sanchez-Garcia, R., Davies, A., Mackintosh, M., Andrinopoulou, E-R., Basiri, A., Harbron, C. & MacArthur, B. D., 25/01/2023, In: Nature Machine Intelligence. 5, 1, p. 13-23 11 p.

    Research output: Contribution to Journal/Magazine › Journal article › peer-review

  10. Published

    Using mixtures of t densities to make inferences in the presence of missing data with a small number of multiply imputed data sets

    Rashid, S., Mitra, R. & Steele, R. J., 1/12/2015, In: Computational Statistics and Data Analysis. 92, p. 84-96 13 p.

    Research output: Contribution to Journal/Magazine › Journal article › peer-review

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