Staff profile

• Mixture models
• Nonparametric regression
• Principal curves
• Random effect modelling

• 2000: Associate Editor, Statistical Modelling:
• 2000: Associate Editor, Advances in Statistical Analysis:
• 2000: Member of the Executive Committee of the SMS: The Statistical Modelling Society (SMS) is an international society with the purpose of promoting and encouraging statistical modelling, and which organizes the annual conference "International Workshop on Statistical Modelling". I have been elected member of the SMS Executive Committee 2011-12 and 2015-18, and continue to be member on the Committee as the Representative of the WG for Communication

Chapter in book

• A Distance-Based Statistic for Goodness-of-Fit Assessment
  Jayakumari, D., Einbeck, J., Hinde, J., & Moral, R. A. (2024). A Distance-Based Statistic for Goodness-of-Fit Assessment. In J. Einbeck, H. Maeng, E. Ogundimu, & K. Perrakis (Eds.), Developments in Statistical Modelling (263-268). Springer. https://doi.org/10.1007/978-3-031-65723-8_40
• Estimating Dose and Time of Exposure from a Protein-Based Radiation Biomarker
  Cai, Y., Einbeck, J., Barnard, S., & Ainsbury, E. (2024). Estimating Dose and Time of Exposure from a Protein-Based Radiation Biomarker. In Developments in Statistical Modelling (239-245). Springer. https://doi.org/10.1007/978-3-031-65723-8_37
• Tools for Assessing Goodness of Fit of GLMs: Case Studies in Entomology
  Jayakumari, D., Hinde, J., Einbeck, J., & Moral, R. A. (2024). Tools for Assessing Goodness of Fit of GLMs: Case Studies in Entomology. In Modelling Insect Populations in Agricultural Landscapes (211-235). Springer International Publishing. https://doi.org/10.1007/978-3-031-43098-5_11
• Elicitation of Priors for Intervention Effects in Educational Trial Data
  Zhang, Q., Uwimpuhwe, G., Vallis, D., Singh, A., Coolen-Maturi, T., & Einbeck, J. (2024). Elicitation of Priors for Intervention Effects in Educational Trial Data. In J. Einbeck, H. Maeng, E. Ogundimu, & K. Perrakis (Eds.), Developments in Statistical Modelling (28-33). Springer. https://doi.org/10.1007/978-3-031-65723-8_5
• Uncertainty Quantification in Lasso-Type Regularization Problems
  Basu, T., Einbeck, J., & Troffaes, M. C. (2021). Uncertainty Quantification in Lasso-Type Regularization Problems. In Optimization Under Uncertainty with Applications to Aerospace Engineering (81-109). Springer Verlag. https://doi.org/10.1007/978-3-030-60166-9_3
• Estimating Exposure Fraction from Radiation Biomarkers: A Comparison of Frequentist and Bayesian Approaches
  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
• On the Use of Random Effect Models for Radiation Biodosimetry
  Einbeck, J., Ainsbury, E., Barnard, S., Oliveira, M., Manning, G., Puig, P., & Badie, C. (2017). On the Use of Random Effect Models for Radiation Biodosimetry. In E. Ainsbury, M. Calle, E. Cardis, J. Einbeck, G. Gómez, & P. Puig (Eds.), Extended abstracts Fall 2015 : Biomedical Big Data ; Statistics for Low Dose Radiation Research (89-94). Springer Verlag. https://doi.org/10.1007/978-3-319-55639-0_15
• Hotspots in Hindsight
  Julian, B. R., Foulger, G. R., Hatfield, O., Jackson, S. E., Simpson, E., Einbeck, J., & Moore, A. (2015). Hotspots in Hindsight. In The Interdisciplinary Earth: A Volume in Honor of Don L. Anderson (105-121). The Geological Society of America / AGU. https://doi.org/10.1130/2015.2514%2808%29
• Representing complex data using localized principal components with application to astronomical data.
  Einbeck, J., Evers, L., & Bailer-Jones, C. (2008). Representing complex data using localized principal components with application to astronomical data. In A. Gorban, B. Kegl, D. Wunsch, & A. Zinovyev (Eds.), Lecture Notes in Computational Science and Engineering (180-204). Springer Verlag. https://doi.org/10.1007/978-3-540-73750-6_7

Conference Paper

• Using linear mixed models to compare a self-assessed frailty score with clinician assessed scores in patients approaching major surgery
  Sayari, M., Durrand, J., Taylor, C., Einbeck, J., Kharatikoopaei, E., Craig, J., & Griffiths, N. (2024, July). Using linear mixed models to compare a self-assessed frailty score with clinician assessed scores in patients approaching major surgery. Presented at International Workshop on Statistical Modelling, Durham
• A multilevel multivariate response model for data with latent structures
  Zhang, Y., Einbeck, J., & Drikvandi, R. (2023, July). A multilevel multivariate response model for data with latent structures. Presented at The 37th International Workshop on Statistical Modelling, Dortmund, Germany
• Individual participant data meta-analysis: pooled effect of EEF funded educational trials on low baseline attaining group
  Uwimpuhwe, G., Singh, A., Akhter, N., Ashraf, B., Coolen-Maturi, T., Robinson, T., Higgins, S., & Einbeck, J. (2023, July). Individual participant data meta-analysis: pooled effect of EEF funded educational trials on low baseline attaining group. Presented at International Workshop on Statistical Modelling, Dortmund
• A Robust Bayesian Approach for Causal Inference Problems
  Basu, T., Troffaes, M. C. M., & Einbeck, J. (2023, September). A Robust Bayesian Approach for Causal Inference Problems. Presented at ECSQARU 2023, Arras, France
• Simultaneous linear dimension reduction and clustering with flexible variance matrices
  Zhang, Y., & Einbeck, J. (2022, December). Simultaneous linear dimension reduction and clustering with flexible variance matrices. Presented at International Workshop of Statistical Modelling, Trieste
• Bayesian Adaptive Selection Under Prior Ignorance
  Basu, T., Troffaes, M. C., & Einbeck, J. (2021, December). Bayesian Adaptive Selection Under Prior Ignorance. Presented at UQOP 2020
• Binary Credal Classification Under Sparsity Constraints
  Basu, T., Troffaes, M. C., & Einbeck, J. (2020, December). Binary Credal Classification Under Sparsity Constraints. Presented at Information Processing and Management of Uncertainty in Knowledge-Based Systems, Lisbon
• A sensitivity analysis and error bounds for the adaptive lasso
  Basu, T., Einbeck, J., & Troffaes, M. (2020, December). A sensitivity analysis and error bounds for the adaptive lasso. Presented at International Workshop on Statistical Modelling, Bilbao
• Robust uncertainty quantification for measurement problems with limited information
  Basu, T., Einbeck, J., Troffaes, M. C., & Forbes, A. (2019, July). Robust uncertainty quantification for measurement problems with limited information. Paper presented at ISIPTA 2019, Ghent, Belgium
• A sensitivity analysis of adaptive lasso
  Basu, T., Einbeck, J., & Troffaes, M. C. (2019, December). A sensitivity analysis of adaptive lasso. Paper presented at Innovations in Data and Statistical Sciences (INDSTATS 2019), Mumbai, India
• Box-Cox response transformations for random effect models
  Almohaimeed, A., & Einbeck, J. (2018, July). Box-Cox response transformations for random effect models. Presented at International Workshop on Statistical Modelling, Bristol
• Con fidence intervals for posterior intercepts, with application to the PIAAC literacy survey
  Einbeck, J., Gray, E., Sofroniou, N., Marques da Silva Junior, A., & Gledhill, J. (2017, July). Con fidence intervals for posterior intercepts, with application to the PIAAC literacy survey. Presented at 32nd International Workshop on Statistical Modelling, Groningen, Netherlands
• Gradient test for generalised linear models with random effects
  da Silva-Junior, A., Einbeck, J., & Craig, P. (2016, July). Gradient test for generalised linear models with random effects. Presented at International Workshop on Statistical Modelling, Rennes, France
• A diagnostic plot for assessing model fit in count data models
  Einbeck, J., & Wilson, P. (2016, July). A diagnostic plot for assessing model fit in count data models. Presented at International Workshop on Statistical Modelling, Rennes, France
• On statistical testing and mean parameter estimation for zero-modification in count data regression
  Wilson, P., & Einbeck, J. (2016, December). On statistical testing and mean parameter estimation for zero-modification in count data regression. Presented at International Workshop on Statistical Modelling, Rennes
• A simple and intuitive test for number-inflation or number-deflation
  Wilson, P., & Einbeck, J. (2015, July). A simple and intuitive test for number-inflation or number-deflation. Presented at 30th International Workshop on Statistical Modelling, Linz, Austria
• A study of online and blockwise updating of the EM algorithm for Gaussian mixtures
  Einbeck, J., & Bonetti, D. (2014, July). A study of online and blockwise updating of the EM algorithm for Gaussian mixtures. Presented at 29th International Workshop on Statistical Modelling, Göttingen
• Bayesian shape modelling of cross-sectional geological data
  Tsiftsi, T., Jermyn, I., & Einbeck, J. (2014, July). Bayesian shape modelling of cross-sectional geological data. Presented at 29th International Workshop on Statistical Modelling, Göttingen
• Bivariate Estimation of Distribution Algorithms for Protein Structure Prediction
  Bonetti, D., Delbem, A., & Einbeck, J. (2014, December). Bivariate Estimation of Distribution Algorithms for Protein Structure Prediction. Presented at 29th International Workshop on Statistical Modelling, Göttingen, Germany
• On the computation of the correlation integral for fractal dimension estimation
  Kalantan, Z., & Einbeck, J. (2012, December). On the computation of the correlation integral for fractal dimension estimation. Presented at International Conference on Statistics in Science, Business, and Engineering (ICSSBE), Langkawi, Kedah, Malaysia
• Penalized regression on principal manifolds with application to combustion modelling
  Einbeck, J., Isaac, B., Evers, L., & Parente, A. (2012, December). Penalized regression on principal manifolds with application to combustion modelling. Presented at International workshop on statistical modelling, Prague
• Generative linear mixture modelling
  Lawson, A., & Einbeck, J. (2012, December). Generative linear mixture modelling. Presented at International workshop on statistical modelling., Prague
• Multivariate regression smoothing through the 'fallling net'
  Taylor, J., & Einbeck, J. (2011, December). Multivariate regression smoothing through the 'fallling net'. Presented at 26th international workshop on statistical modelling., Valencia
• Localized regression on principal manifolds
  Einbeck, J., & Evers, L. (2010, July). Localized regression on principal manifolds. Presented at 25th International Workshop on Statistical Modelling., Glasgow
• Data compression and regression based on local principal curves
  Einbeck, J., Evers, L., & Hinchliff, K. (2010, December). Data compression and regression based on local principal curves. Presented at 32nd annual Conference of the German Classification Society, Hamburg
• Strategies for local smoothing in high dimensions: using density thresholds and adapted GCV
  Taylor, J., & Einbeck, J. (2010, December). Strategies for local smoothing in high dimensions: using density thresholds and adapted GCV. Presented at 25th International Workshop on Statistical Modelling, Glasgow, Scotland
• Constructing Economic Summary Indexes via Principal Curves
  Zayed, M., & Einbeck, J. (2010, December). Constructing Economic Summary Indexes via Principal Curves. Presented at COMPSTAT 2010, Paris, France
• League tables for literacy survey data based on random effect models
  Sofroniou, N., Hoad, D., & Einbeck, J. (2008, December). League tables for literacy survey data based on random effect models. Presented at 23rd international workshop on statistical modelling, Utrecht
• A comparative study of nonparametric derivative estimators.
  Newell, J., & Einbeck, J. (2007, July). A comparative study of nonparametric derivative estimators. Presented at 22nd International Workshop on Statistical Modelling., Barcelona, Spain
• Smoothing, Sampling, and Basu's elephants
  Einbeck, J., Augustin, T., & Singer, J. M. (2007, July). Smoothing, Sampling, and Basu's elephants. Presented at 22nd International Workshop on Statistical Modelling., Barcelona, Spain
• The fitting of multifunctions: an approach to nonparametric multimodal regression
  Einbeck, J., & Tutz, G. (2006, August). The fitting of multifunctions: an approach to nonparametric multimodal regression. Presented at COMPSTAT., Rome, Italy
• Analyzing Irish suicide rates with mixture models
  Sofroniou, N., Einbeck, J., Hinde, J., & Newell, J. (2006, July). Analyzing Irish suicide rates with mixture models. Presented at 21th International Workshop on Statistical Modelling., Galway, Ireland
• Model free endurance markers based on the second derivative of blood lactate curves
  Newell, J., Einbeck, J., Madden, N., & McMillan, K. (2005, July). Model free endurance markers based on the second derivative of blood lactate curves. Presented at 20th International Workshop on Statistical Modelling., Sydney
• Exploring Multivariate Data Structures with Local Principal Curves
  Einbeck, J., Tutz, G., & Evers, L. (2005, January). Exploring Multivariate Data Structures with Local Principal Curves. Presented at 28th Annual Conference of the German Classiciation Society., Magedeburg, Germany

Conference Proceeding

• Proceedings of the 38th International Workshop on Statistical Modelling
  (2024, July). Proceedings of the 38th International Workshop on Statistical Modelling. Presented at 38th International Workshop on Statistical Modelling (IWSM), Durham, UK

Doctoral Thesis

• Local Smoothing Methods for the Analysis of Multivariate Complex Data Structures
  Einbeck, J. Local Smoothing Methods for the Analysis of Multivariate Complex Data Structures. (Thesis). Institut fuer Statistik, LMU Muenchen. https://durham-repository.worktribe.com/output/1647400

Edited book

• Developments in Statistical Modelling
  Einbeck, J., Maeng, H., Ogundimu, E., & Perrakis, K. (Eds.). (2024). Developments in Statistical Modelling. Springer Nature. https://doi.org/10.1007/978-3-031-65723-8
• Extended Abstracts Fall 2015. Biomedical Big Data; Statistics for Low Dose Radiation Research
  Ainsbury, E., Calle, M., Cardis, E., Einbeck, J., Gómez, G., & Puig, P. (Eds.). (2017). Extended Abstracts Fall 2015. Biomedical Big Data; Statistics for Low Dose Radiation Research. Springer Verlag
• Proceedings of the 21st International Workshop on Statistical Modelling. Galway, Ireland, 3-7 July 2006
  Hinde, J., Einbeck, J., & Newell, J. (Eds.). (2006). Proceedings of the 21st International Workshop on Statistical Modelling. Galway, Ireland, 3-7 July 2006. National University of Ireland, Galway

Journal Article

• A two-level multivariate response model for data with latent structures
  Zhang, Y., Einbeck, J., & Drikvandi, R. (online). A two-level multivariate response model for data with latent structures. Statistical Modelling, https://doi.org/10.1177/1471082X241313024
• A Comparison of Threshold-Free Measures for Assessing the Effectiveness of Educational Interventions
  Einbeck, J., Coolen-Maturi, T., Uwimpuhwe, G., & Singh, A. (online). A Comparison of Threshold-Free Measures for Assessing the Effectiveness of Educational Interventions. The Journal of Experimental Education, https://doi.org/10.1080/00220973.2024.2405738
• Lack of effect of a parent‐delivered early language intervention: Evidence from a randomised controlled trial completed during COVID‐19
  Burgoyne, K., Hargreaves, S., Akhter, N., Cramman, H., Eerola, P., Einbeck, J., & Menzies, V. (online). Lack of effect of a parent‐delivered early language intervention: Evidence from a randomised controlled trial completed during COVID‐19. JCPP Advances, Article e12279. https://doi.org/10.1002/jcv2.12279
• Managing unusual sensory experiences in at-risk mental state for psychosis in England: A parallel group, single-blind, randomised controlled feasibility trial
  Dodgson, G., Singh, A., Barclay, N., Birkett, L., Boyle, C., Brandon, T., Dudley, R., Einbeck, J., Gibbs, C., Hamilton, J., Larry, V., Simpson, J., & Fernyhough, C. (2025). Managing unusual sensory experiences in at-risk mental state for psychosis in England: A parallel group, single-blind, randomised controlled feasibility trial. Psychiatry Research, 351, Article 116564. https://doi.org/10.1016/j.psychres.2025.116564
• Preferences for Psychological Therapy or Support Within an ARMS Psychological Therapies Trial: The Importance of Targeted Intervention for Unusual Sensory Experiences
  Hamilton, J., Singh, A., Gibbs, C., Barclay, N. A., Birkett, L., Boyle, C., Brandon, T., Dudley, R., Einbeck, J., Larry, V., Simpson, J., Dodgson, G., & Fernyhough, C. (2025). Preferences for Psychological Therapy or Support Within an ARMS Psychological Therapies Trial: The Importance of Targeted Intervention for Unusual Sensory Experiences. Early Intervention in Psychiatry, 19(4), Article e70035. https://doi.org/10.1111/eip.70035
• A fresh look at mean-shift based modal clustering
  Ameijeiras-Alonso, J., & Einbeck, J. (2024). A fresh look at mean-shift based modal clustering. Advances in Data Analysis and Classification, 18(4), 1067-1095. https://doi.org/10.1007/s11634-023-00575-1
• Directed Clustering of Multivariate Data Based on Linear or Quadratic Latent Variable Models
  Zhang, Y., & Einbeck, J. (2024). Directed Clustering of Multivariate Data Based on Linear or Quadratic Latent Variable Models. Algorithms, 17(8), Article 358. https://doi.org/10.3390/a17080358
• A Versatile Model for Clustered and Highly Correlated Multivariate Data
  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
• The effects of lockdown during the COVID-19 pandemic on fetal movement profiles
  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
• A Sequential Cross-Sectional Analysis Producing Robust Weekly COVID-19 Rates for South East Asian Countries
  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
• Use of a targeted, computer/web-based guided self-help psychoeducation toolkit for distressing hallucinations (MUSE) in people with an at-risk mental state for psychosis: protocol for a randomised controlled feasibility trial
  Hamilton, J., Arnott, B., Aynsworth, C., Barclay, N. A., Birkett, L., Brandon, T., Dixon, L., Dudley, R., Einbeck, J., Gibbs, C., Kharatikoopaei, E., Simpson, J., Dodgson, G., & Fernyhough, C. (2023). Use of a targeted, computer/web-based guided self-help psychoeducation toolkit for distressing hallucinations (MUSE) in people with an at-risk mental state for psychosis: protocol for a randomised controlled feasibility trial. BMJ Open, 13(6), Article e076101. https://doi.org/10.1136/bmjopen-2023-076101
• Association between Hyperemesis Gravidarum in pregnancy on postnatal ability of infants to attend to a play task with their mother
  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
• Cumulant-Based Goodness-of-Fit Tests for the Tweedie, Bar-Lev and Enis Class of Distributions
  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
• Biodose Tools: an R shiny application for biological dosimetry
  Hernández, A., Endesfelder, D., Einbeck, J., Puig, P., Benadjaoud, M. A., Higueras, M., Ainsbury, E., Gruel, G., Oestreicher, U., Barrios, L., & 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
• A robust Bayesian analysis of variable selection under prior ignorance
  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
• Response transformations for random effect and variance component models
  Almohaimeed, A., & Einbeck, J. (2022). Response transformations for random effect and variance component models. Statistical Modelling, 22(4), 297-326. https://doi.org/10.1177/1471082x20966919
• The effect of data aggregation on dispersion estimates in count data models
  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
• Multisite educational trials: estimating the effect size and its confidence intervals
  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
• The impact of a novel medication scanner on administration errors in the hospital setting: a before and after feasibility study
  Tolley, C. L., Watson, N. W., Heed, A., Einbeck, J., Medows, S., Wood, L., Campbell, 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
• Using Random Effect Models to Produce Robust Estimates of Death Rates in COVID-19 Data
  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
• Effects of maternal mental health on prenatal movement profiles in twins and singletons
  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
• The Impact of a Bedside Medication Scanning Device on Administration Errors in the Hospital Setting: A Prospective Observational Study
  Tolley, C., Watson, N., Heed, A., Einbeck, J., Medows, S., Wood, L., Campbell, L., & Slight, S. (2021). The Impact of a Bedside Medication Scanning Device on Administration Errors in the Hospital Setting: A Prospective Observational Study. International Journal of Pharmacy Practice, 29(Supplement_1), i9. https://doi.org/10.1093/ijpp/riab016.011
• A graphical tool for assessing the suitability of a count regression model
  Wilson, P., & Einbeck, J. (2021). A graphical tool for assessing the suitability of a count regression model. Austrian Journal of Statistics, 50(1), 1-23. https://doi.org/10.17713/ajs.v50i1.921
• Effects of maternal mental health on fetal visual preference for face-like compared to non-face like light stimulation
  Reissland, N., Wood, R., Einbeck, J., & Lane, A. (2020). Effects of maternal mental health on fetal visual preference for face-like compared to non-face like light stimulation. Early Human Development, 151, Article 105227. https://doi.org/10.1016/j.earlhumdev.2020.105227
• Practical Considerations on Nonparametric Methods for Estimating Intrinsic Dimensions of Nonlinear Data Structures
  Einbeck, J., Kalantan, Z., & Kruger, U. (2020). Practical Considerations on Nonparametric Methods for Estimating Intrinsic Dimensions of Nonlinear Data Structures. International Journal of Pattern Recognition and Artificial Intelligence, 34(9), Article 2058010. https://doi.org/10.1142/s0218001420580100
• Prenatal effects of maternal nutritional stress and mental health on the fetal movement profile
  Reissland, N., Millard, A., Wood, R., Ustun, B., McFaul, C., Froggatt, S., & Einbeck, J. (2020). Prenatal effects of maternal nutritional stress and mental health on the fetal movement profile. Archives of Gynecology and Obstetrics, 302(1), 65-75. https://doi.org/10.1007/s00404-020-05571-w
• Testing fetal abilities: A commentary on studies testing prenatal reactions to light stimulation
  Reissland, N., Wood, R., Einbeck, J., & Lane, A. (2020). Testing fetal abilities: A commentary on studies testing prenatal reactions to light stimulation
• Improving the accuracy of dose estimates from automatically scored dicentric chromosomes by accounting for chromosome number
  Endesfelder, D., Kulka, U., Einbeck, J., & Oestreicher, U. (2020). Improving the accuracy of dose estimates from automatically scored dicentric chromosomes by accounting for chromosome number. International Journal of Radiation Biology, 96(12), 1571-1584. https://doi.org/10.1080/09553002.2020.1829152
• Quantile-Based Estimation of the Finite Cauchy Mixture Model
  Kalantan, Z. I., & Einbeck, J. (2019). Quantile-Based Estimation of the Finite Cauchy Mixture Model. Symmetry, 11(9), Article 1186. https://doi.org/10.3390/sym11091186
• A new and intuitive test for zero modification
  Wilson, P., & Einbeck, J. (2019). A new and intuitive test for zero modification. Statistical Modelling, 19(4), 341--361. https://doi.org/10.1177/1471082x18762277
• A statistical framework for radiation dose estimation with uncertainty quantification from the γ-H2AX assay
  Einbeck, J., Ainsbury, E. A., Sales, R., Barnard, S., Kaestle, F., & Higueras, M. (2018). A statistical framework for radiation dose estimation with uncertainty quantification from the γ-H2AX assay. PLoS ONE, 13(11), https://doi.org/10.1371/journal.pone.0207464
• k-Boxplots for mixture data
  Qarmalah, N. M., Einbeck, J., & Coolen, F. P. (2018). k-Boxplots for mixture data. Statistical Papers, 59(2), 513-528. https://doi.org/10.1007/s00362-016-0774-7
• Fisher information under Gaussian quadrature models
  Marques da Silva Júnior, A. H., Einbeck, J., & Craig, P. S. (2018). Fisher information under Gaussian quadrature models. Statistica Neerlandica, 72(2), 74-89. https://doi.org/10.1111/stan.12116
• Self–consistency–based tests for bivariate distributions
  Einbeck, J., & Meintanis, S. (2017). Self–consistency–based tests for bivariate distributions. Journal of statistical theory and practice, 11(3), 478-492. https://doi.org/10.1080/15598608.2017.1318098
• Mixture Models for Prediction from Time Series, with Application to Energy Use Data
  Qarmalah, N. M., Einbeck, J., & Coolen, F. P. (2017). Mixture Models for Prediction from Time Series, with Application to Energy Use Data. Archives of data science. Series A, 2(1), 1-15. https://doi.org/10.5445/ksp/1000058749/07
• Uncertainty of fast biological radiation dose assessment for emergency response scenarios
  Ainsbury, E. A., Higueras, M., Puig, P., Einbeck, J., Samaga, D., Barquinero, J. F., Barrios, L., Brzozowska, B., Fattibene, P., Gregoire, E., Jaworska, A., Lloyd, D., Oestreicher, U., Romm, H., Rothkamm, K., Roy, L., Sommer, S., Terzoudi, G., Thierens, H., Trompier, F., …Woda, C. (2017). Uncertainty of fast biological radiation dose assessment for emergency response scenarios. International Journal of Radiation Biology, 93(1), 127-135. https://doi.org/10.1080/09553002.2016.1227106
• The correlation threshold as a strategy for gene filtering, with application to irritable bowel syndrome and breast cancer microarray data
  Jackson, S. E., Einbeck, J., Kasim, A., & Talloen, W. (2016). The correlation threshold as a strategy for gene filtering, with application to irritable bowel syndrome and breast cancer microarray data. Reinvention, 9(2),
• Zero-inflated regression models for radiation-induced chromosome aberration data: A comparative study
  Oliveira, M., Einbeck, J., Higueras, M., Ainsbury, E., Puig, P., & Rothkamm, K. (2016). Zero-inflated regression models for radiation-induced chromosome aberration data: A comparative study. Biometrical Journal, 58(2), 259-279. https://doi.org/10.1002/bimj.201400233
• A summer with genes: Simple disease classification from microarray data
  Einbeck, J., Jackson, S. E., & Kasim, A. (2015). A summer with genes: Simple disease classification from microarray data. Mathematics today, 51(4), 186-188
• Some asymptotics for localized principal components and curves
  Einbeck, J., & Zayed, M. (2014). Some asymptotics for localized principal components and curves. Communications in Statistics - Theory and Methods, 43(8), 1736-1749. https://doi.org/10.1080/03610926.2012.673676
• Implementation of a local principal curves algorithm for neutrino interaction reconstruction in a liquid argon volume
  Back, J., Barker, G., Boyd, S., Einbeck, J., Haigh, M., Morgan, B., Oakley, B., Ramachers, Y., & Roythorne, D. (2014). Implementation of a local principal curves algorithm for neutrino interaction reconstruction in a liquid argon volume. The European Physical Journal C, 74(3), Article 2832. https://doi.org/10.1140/epjc/s10052-014-2832-4
• Discussion of ‘Beyond mean regression’
  Einbeck, J. (2013). Discussion of ‘Beyond mean regression’. Statistical Modelling, 13(4), 349-354. https://doi.org/10.1177/1471082x13494526
• Validation tests for semi-parametric models
  Meintanis, S., & Einbeck, J. (2013). Validation tests for semi-parametric models. Journal of Statistical Computation and Simulation, 85(1), 131-146. https://doi.org/10.1080/00949655.2013.806922
• Challenging the curse of dimensionality in multivariate local linear regression
  Taylor, J., & Einbeck, J. (2013). Challenging the curse of dimensionality in multivariate local linear regression. Computational Statistics, 28(3), 955-976. https://doi.org/10.1007/s00180-012-0342-0
• A number-of-modes reference rule for density estimation under multimodality
  Einbeck, J., & Taylor, J. (2013). A number-of-modes reference rule for density estimation under multimodality. Statistica Neerlandica, 67(1), 54-66. https://doi.org/10.1111/j.1467-9574.2012.00531.x
• Goodness-of-fit tests in semi-linear models
  Meintanis, S., & Einbeck, J. (2012). Goodness-of-fit tests in semi-linear models. Statistics and Computing, 22(4), 967-979. https://doi.org/10.1007/s11222-011-9266-8
• Using principal curves to analyse traffic patterns on freeways
  Einbeck, J., & Dwyer, J. (2011). Using principal curves to analyse traffic patterns on freeways. Transportmetrica, 7(3), 229-246. https://doi.org/10.1080/18128600903500110
• Bandwidth Selection for Mean-shift based Unsupervised Learning Techniques: a Unified Approach via Self-coverage
  Einbeck, J. (2011). Bandwidth Selection for Mean-shift based Unsupervised Learning Techniques: a Unified Approach via Self-coverage. Journal of pattern recognition research, 6(2), 175-192. https://doi.org/10.13176/11.288
• Data compression and regression through local principal curves and surfaces
  Einbeck, J., Evers, L., & Powell, B. (2010). Data compression and regression through local principal curves and surfaces. International Journal of Neural Systems, 20(3), 177-192. https://doi.org/10.1142/s0129065710002346
• Weighted Repeated Median Smoothing and Filtering
  Fried, R., Einbeck, J., & Gather, U. (2007). Weighted Repeated Median Smoothing and Filtering. Journal of the American Statistical Association, 102(480), 1300-1308. https://doi.org/10.1198/016214507000001166
• A new package for fitting random effect models
  Einbeck, J., Hinde, J., & Darnell, R. (2007). A new package for fitting random effect models. R news, 7(1), 26-30
• On design-weighted local fitting and its relation to the Horvitz-Thompson estimator
  Einbeck, J., & Augustin, T. (2007). On design-weighted local fitting and its relation to the Horvitz-Thompson estimator. Statistica sinica, 19(1), 103-123
• Software for calculating blood lactate endurance markers
  Newell, J., Higgins, D., Madden, N., Cruickshank, J., Einbeck, J., McMillan, K., & McDonald, R. (2007). Software for calculating blood lactate endurance markers. Journal of Sports Sciences, 25(12), 1403-1409. https://doi.org/10.1080/02640410601128922
• Modelling beyond regression functions: An application of multimodal regression to speed-flow data
  Einbeck, J., & Tutz, G. (2006). Modelling beyond regression functions: An application of multimodal regression to speed-flow data. Journal of the Royal Statistical Society: Series C, 55(4), 461-475. https://doi.org/10.1111/j.1467-9876.2006.00547.x
• A note on NPML estimation for exponential family regression models with unspecified dispersion parameter
  Einbeck, J., & Hinde, J. (2006). A note on NPML estimation for exponential family regression models with unspecified dispersion parameter. Austrian Journal of Statistics, 35(2&3), 233-243
• Local Principal Curves
  Einbeck, J., Tutz, G., & Evers, L. (2005). Local Principal Curves. Statistics and Computing, 15(4), 301-313. https://doi.org/10.1007/s11222-005-4073-8
• Local fitting with a power basis
  Einbeck, J. (2004). Local fitting with a power basis. Revstat Statistical Journal, 2(2), 102-126
• Local Smoothing with Robustness against outlying Predictors
  Einbeck, J., Andre, C. D., & Singer, J. M. (2004). Local Smoothing with Robustness against outlying Predictors. Environmetrics, 15(6), 541-554. https://doi.org/10.1002/env.644
• A Simple Unifying Formula for Taylor's Theorem and Cauchy's Mean Value Theorem
  Einbeck, J. (2004). A Simple Unifying Formula for Taylor's Theorem and Cauchy's Mean Value Theorem. International Journal of Pure and Applied Mathematics, 14(1), 69-74
• Online Monitoring with Local Smoothing Methods and Adaptive Ridging
  Einbeck, J., & Kauermann, G. (2003). Online Monitoring with Local Smoothing Methods and Adaptive Ridging. Journal of Statistical Computation and Simulation, 73(12), 913-929. https://doi.org/10.1080/0094965031000104332
• Multivariate Local Fitting with General Basis Functions
  Einbeck, J. (2003). Multivariate Local Fitting with General Basis Functions. Computational Statistics, 18(2), 185-203. https://doi.org/10.1007/s001800300140

Presentation

• Sensitivity analysis of Bayesian variable selection and its application in causal estimation
  Basu, T., Einbeck, J., & Troffaes, M. C. M. (2025, July). Sensitivity analysis of Bayesian variable selection and its application in causal estimation. Poster presented at 14th International Symposium on Imprecise Probabilities: Theories and Applications, Bielefeld, Germany

Report

• The differential impact of Covid-19 related school closures on English primary school pupils’ writing performance
  Beckmann, J., Einbeck, J., & Hunt, A. (2025). The differential impact of Covid-19 related school closures on English primary school pupils’ writing performance. Nuffield Foundation
• Evaluating the impact of the Parents and Children Together (PACT) programme on the language skills of 3- to 4-year-old nursery children A two-armed randomised trial
  Menzies, V., Eerola, P.-S., Zhang, Q., Cramman, H., & Einbeck, J. (2024). Evaluating the impact of the Parents and Children Together (PACT) programme on the language skills of 3- to 4-year-old nursery children A two-armed randomised trial. Educational Endowment Foundation
• Improving power calculations in educational trials
  Singh, A., Uwimpuhwe, G., Vallis, D., Akhter, N., Coolen-Maturi, T., Einbeck, J., Higgins, S., Culliney, M., & Demack, S. (2023). Improving power calculations in educational trials. Education Endowment Foundation
• Parents and Children Together (PACT) Evaluation Report
  Menzies, V., Cramman, H., Eerola, P., Hugill-Jones, J., Akhter, N., & Einbeck, J. (2022). Parents and Children Together (PACT) Evaluation Report. [No known commissioning body]
• Individual-participant-data-meta-analysis-of-the-impact-of-EEF-trials-on-the-educational-attainment-of-pupils-on-Free-School-Meals
  Ashraf, B., Singh, A., Uwimpuhwe, G., Coolen-Maturi, T., Einbeck, J., Higgins, S., & Kasim, A. (2021). Individual-participant-data-meta-analysis-of-the-impact-of-EEF-trials-on-the-educational-attainment-of-pupils-on-Free-School-Meals. EEF