Publications

Peer-Reviewed Research Articles

  1. Bernhardt, P. W. (2022+). A comparison of multiple imputation strategies by fully conditional specification and joint modeling for generalized linear models with covariates subject to detection limit. Paper Resources.
  2. Bernhardt, P. W. (2022+). A Comparison of Stacked and Pooled Multiple Imputation.
  3. Ellis, D. M., Felgoise, S. H, Markey, D., Houton, E., Wackron, K., Dowdell, E., Bernhardt, P.W. (2022+). Students working together in an interprofessional team: Perceptions of competency and comfortability while collaborating during a mock code. Under Review.
  4. Ellis, D. M. Hickey, S. McLaughlin, C., Kim, L. Puleo, M., Becker, M., Feloise, S. H., Reddy, T., Markey, D., Prieto, P., O'Connor, M. Bernhardt, P. W. (2021). Interprofessional mock code simulation promotes collaboration and competency in Parkinson's medication safety during transitions in care. (25), 1-4. https://doi.org/10.1016/j.xjep.2021.100468.
  5. Ellis, D. M., Hickey, S., McLaughlin, C., Kim, L., Puleo, M., Becker, M., Felgoise, S. H., Reddy, T., Markey, D., Prieto, P., O’Connor, M., Bernhardt P.W. (2021). The impact of simulation on perceived comfort and competency to work in Interprofessional teams. Nursing Education Perspectives. doi/10.1097/01.NEP.0000000000000920.
  6. Bernhardt, P. W. (2018). Maximum likelihood estimation in a semicontinuous survival model with covariates subject to detection limits. Under Revision with The International Journal of Biostatistics. 14 (2). doi/10.1515/ijb-2017-0058/html. Paper Resources.
  7. Bernhardt, P. W. (2018). Model validation and influence diagnostics for regression models with missing covariates. Statistics in Medicine. 37, 1325-1342. Paper Resources.
  8. Bernhardt, P. W. (2016). A flexible parametric cure rate model with dependent censoring and a known cure threshold. Statistics in Medicine. 35, 4607-4623. Paper Resources.
  9. Bernhardt, P. W., Wang, H. J., and Zhang, D. (2015). A fast EM algorithm for fitting joint models of a binary response and multiple longitudinal covariates subject to detection limits.  Computational Statistics and Data Analysis. 85, 37-53.  Paper Resources.
  10. Bernhardt, P. W., Wang, H. J., and Zhang, D. (2015). Statistical methods for generalized linear models with covariates subject to detection limits.  Statistics in Biosciences. 7, 68-89. Paper Resources.
  11. Bernhardt, P. W., Wang, H. J., and Zhang, D. (2014). Flexible modeling of survival data with covariates subject to detection limits.  Computational Statistics and Data Analysis. 69, 81-91. Paper Resources.
  12. Rogers, J., Wilbur, J., Cole, S., Bernhardt, P. W., Bupp, J., Lennon, M., Langholz, N. and Steiner, C. (2011). Quantifying uncertainty in predictions of hepatic clearance.   Statistics in Biopharmaceutical Research. 3, 515-525.

 

Additional Publications (Non-research Articles)

  1. Bernhardt, P. W. (2016). Review of Statistical Data Analytics: Foundations for Data Mining, Informatics, and Knowledge Discovery by Walter W. Piegorsch. The American Statistician (Reviews of Books and Teaching Materials), 68 (3), 213.DOI 10.1080/00031305.2016.1234902
  2. Bernhardt, P. W. (2014). Review of Applied Statistics: Regression and Analysis of Variance by Bayo Lawal and Felix Famoye. The American Statistician (Reviews of Books and Teaching Materials), 68 (3), 213.  DOI 10.1080/00031305.2014.928562.
  3. Bernhardt, P. W. and Franklin, A. (2010). Some advice for beginning graduate students in statistics.   AMSTATNEWS. 3(4), 515-525.