Publications
Peer-Reviewed Research Articles
- 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.
- Bernhardt, P. W.
(2022+). A Comparison of Stacked and Pooled Multiple Imputation.
- 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.
- 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.
-
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.
- 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.
- Bernhardt, P. W.
(2018). Model validation and influence diagnostics for regression models
with missing covariates. Statistics in Medicine. 37, 1325-1342.
Paper Resources.
- 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.
- 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.
- 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.
- 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.
- 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)
- 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
- 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.
- Bernhardt, P. W.
and Franklin, A. (2010). Some advice for beginning graduate students in statistics. AMSTATNEWS.
3(4), 515-525.