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The effects of lockdown during the COVID-19 pandemic on fetal movement profiles (2024)
Journal Article
Reissland, N., Ustun, B., & Einbeck, J. (2024). The effects of lockdown during the COVID-19 pandemic on fetal movement profiles. BMC Pregnancy and Childbirth, 24(1), 56. https://doi.org/10.1186/s12884-024-06259-8

Purpose: The current study investigated the direct impact of the COVID-19 lockdown on fetal movements, addressing a critical research gap. While previous research has predominantly examined the effects of lockdown on maternal health and postnatal out... Read More about The effects of lockdown during the COVID-19 pandemic on fetal movement profiles.

A Versatile Model for Clustered and Highly Correlated Multivariate Data (2024)
Journal Article
Zhang, Y., & Einbeck, J. (2024). A Versatile Model for Clustered and Highly Correlated Multivariate Data. Journal of statistical theory and practice, 18(1), Article 5. https://doi.org/10.1007/s42519-023-00357-0

For the analysis of multivariate data with an approximately one-dimensional latent structure, it is suggested to model this latent variable by a random effect, allowing for the use of mixed model methodology for dimension reduction purposes. We imple... Read More about A Versatile Model for Clustered and Highly Correlated Multivariate Data.

A fresh look at mean-shift based modal clustering (2023)
Journal Article
Ameijeiras-Alonso, J., & Einbeck, J. (2023). A fresh look at mean-shift based modal clustering. Advances in Data Analysis and Classification, https://doi.org/10.1007/s11634-023-00575-1

Modal clustering is an unsupervised learning technique where cluster centers are identified as the local maxima of nonparametric probability density estimates. A natural algorithmic engine for the computation of these maxima is the mean shift procedu... Read More about A fresh look at mean-shift based modal clustering.

A Sequential Cross-Sectional Analysis Producing Robust Weekly COVID-19 Rates for South East Asian Countries (2023)
Journal Article
Almohaimeed, A., & Einbeck, J. (2023). A Sequential Cross-Sectional Analysis Producing Robust Weekly COVID-19 Rates for South East Asian Countries. Viruses, 15(7), Article 1572. https://doi.org/10.3390/v15071572

The COVID-19 pandemic has expanded fast over the world, affecting millions of people and generating serious health, social, and economic consequences. All South East Asian countries have experienced the pandemic, with various degrees of intensity and... Read More about A Sequential Cross-Sectional Analysis Producing Robust Weekly COVID-19 Rates for South East Asian Countries.

Cumulant-Based Goodness-of-Fit Tests for the Tweedie, Bar-Lev and Enis Class of Distributions (2023)
Journal Article
Bar-Lev, S. K., Batsidis, A., Einbeck, J., Liu, X., & Ren, P. (2023). Cumulant-Based Goodness-of-Fit Tests for the Tweedie, Bar-Lev and Enis Class of Distributions. Mathematics, 11(7), Article 1603. https://doi.org/10.3390/math11071603

The class of natural exponential families (NEFs) of distributions having power variance functions (NEF-PVFs) is huge (uncountable), with enormous applications in various fields. Based on a characterization property that holds for the cumulants of the... Read More about Cumulant-Based Goodness-of-Fit Tests for the Tweedie, Bar-Lev and Enis Class of Distributions.

Association between Hyperemesis Gravidarum in pregnancy on postnatal ability of infants to attend to a play task with their mother (2023)
Journal Article
Reissland, N., Matthewson, J., & Einbeck, J. (2023). Association between Hyperemesis Gravidarum in pregnancy on postnatal ability of infants to attend to a play task with their mother. Infant Behavior & Development, 71, https://doi.org/10.1016/j.infbeh.2023.101823

Research indicates a higher prevalence of attention deficits in children exposed to HG in utero compared to controls with some claiming that the deficit is due to prenatal effects of malnutrition in HG mothers and others that it is due to maternal me... Read More about Association between Hyperemesis Gravidarum in pregnancy on postnatal ability of infants to attend to a play task with their mother.

Biodose Tools: an R shiny application for biological dosimetry (2023)
Journal Article
Hernández, A., Endesfelder, D., Einbeck, J., Puig, P., Benadjaoud, M. A., Higueras, M., …Barquinero, J. F. (2023). Biodose Tools: an R shiny application for biological dosimetry. International Journal of Radiation Biology, 99(9), https://doi.org/10.1080/09553002.2023.2176564

Introduction: In the event of a radiological accident or incident, the aim of biological dosimetry is to convert the yield of a specific biomarker of exposure to ionizing radiation into an absorbed dose. Since the 1980s, various tools have been used... Read More about Biodose Tools: an R shiny application for biological dosimetry.

Using Random Effect Models to Produce Robust Estimates of Death Rates in COVID-19 Data (2022)
Journal Article
Almohaimeed, A., Einbeck, J., Qarmalah, N., & Alkhidhr, H. (2022). Using Random Effect Models to Produce Robust Estimates of Death Rates in COVID-19 Data. International Journal of Environmental Research and Public Health, 19(22), https://doi.org/10.3390/ijerph192214960

Tracking the progress of an infectious disease is critical during a pandemic. However, the incubation period, diagnosis, and treatment most often cause uncertainties in the reporting of both cases and deaths, leading in turn to unreliable death rates... Read More about Using Random Effect Models to Produce Robust Estimates of Death Rates in COVID-19 Data.

A robust Bayesian analysis of variable selection under prior ignorance (2022)
Journal Article
Basu, T., Troffaes, M. C., & Einbeck, J. (2023). A robust Bayesian analysis of variable selection under prior ignorance. Sankhya A - Mathematical Statistics and Probability, 85(1), 1014-1057. https://doi.org/10.1007/s13171-022-00287-2

We propose a cautious Bayesian variable selection routine by investigating the sensitivity of a hierarchical model, where the regression coefficients are specified by spike and slab priors. We exploit the use of latent variables to understand the imp... Read More about A robust Bayesian analysis of variable selection under prior ignorance.

The impact of a novel medication scanner on administration errors in the hospital setting: a before and after feasibility study (2022)
Journal Article
Tolley, C. L., Watson, N. W., Heed, A., Einbeck, J., Medows, S., Wood, L., …Slight, S. P. (2022). The impact of a novel medication scanner on administration errors in the hospital setting: a before and after feasibility study. BMC Medical Informatics and Decision Making, 22(1), Article 86. https://doi.org/10.1186/s12911-022-01828-3

Objective: The medication administration process is complex and consequently prone to errors. Closed Loop Medication Administration solutions aim to improve patient safety. We assessed the impact of a novel medication scanning device (MedEye) on the... Read More about The impact of a novel medication scanner on administration errors in the hospital setting: a before and after feasibility study.

Estimating Exposure Fraction from Radiation Biomarkers: A Comparison of Frequentist and Bayesian Approaches (2021)
Book Chapter
Errington, A., Einbeck, J., & Cumming, J. (2021). Estimating Exposure Fraction from Radiation Biomarkers: A Comparison of Frequentist and Bayesian Approaches. In M. Vasile, & D. Quagliarella (Eds.), Advances in Uncertainty Quantification and Optimization Under Uncertainty with Aerospace Applications (393-405). Springer Verlag. https://doi.org/10.1007/978-3-030-80542-5_24

If individuals are exposed to ionising radiation, due to some radiation accident, for medical reasons, or during spaceflight, there is often a need to estimate the contracted radiation dose. The field of biodosimetry is concerned with estimating the... Read More about Estimating Exposure Fraction from Radiation Biomarkers: A Comparison of Frequentist and Bayesian Approaches.

Bayesian Adaptive Selection Under Prior Ignorance (2021)
Presentation / Conference Contribution
Basu, T., Troffaes, M. C., & Einbeck, J. (2021). Bayesian Adaptive Selection Under Prior Ignorance. In M. Vasile, & D. Quagliarella (Eds.), . https://doi.org/10.1007/978-3-030-80542-5_22

Bayesian variable selection is one of the popular topics in modern day statistics. It is an important tool for high dimensional statistics, where the number of model parameters is greater than the number of observations. Several Bayesian models have... Read More about Bayesian Adaptive Selection Under Prior Ignorance.

Effects of maternal mental health on prenatal movement profiles in twins and singletons (2021)
Journal Article
Reissland, N., Einbeck, J., Wood, R., & Lane, A. (2021). Effects of maternal mental health on prenatal movement profiles in twins and singletons. Acta Paediatrica: Nurturing the Child, 110(9), 2553-2558. https://doi.org/10.1111/apa.15903

Aim: Prenatal experiences, including maternal stress, depression and anxiety, form crucial building blocks affecting the maturation of the fetal central nervous system. Previous research has examined fetal movements without considering effects of mat... Read More about Effects of maternal mental health on prenatal movement profiles in twins and singletons.

The effect of data aggregation on dispersion estimates in count data models (2021)
Journal Article
Errington, A., Einbeck, J., Cumming, J., Rössler, U., & Endesfelder, D. (2022). The effect of data aggregation on dispersion estimates in count data models. International Journal of Biostatistics, 18(1), 183-202. https://doi.org/10.1515/ijb-2020-0079

For the modelling of count data, aggregation of the raw data over certain subgroups or predictor configurations is common practice. This is, for instance, the case for count data biomarkers of radiation exposure. Under the Poisson law, count data can... Read More about The effect of data aggregation on dispersion estimates in count data models.

Multisite educational trials: estimating the effect size and its confidence intervals (2021)
Journal Article
Singh, A., Uwimpuhwe, G., Li, M., Einbeck, J., Higgins, S., & Kasim, A. (2022). Multisite educational trials: estimating the effect size and its confidence intervals. International Journal of Research & Method in Education, 45(1), 18-38. https://doi.org/10.1080/1743727x.2021.1882416

In education, multisite trials involve randomisation of pupils into intervention and comparison groups within schools. Most analytical models in multisite educational trials ignore that the impact of an intervention may be school dependent. This stud... Read More about Multisite educational trials: estimating the effect size and its confidence intervals.