Welcome to the homepage of Frank Miller

Research

In my statistical research I focus on innovative methods needed in practice and feasible to implement. My research interests include:

  • Adaptive and sequential designs,
  • biostatistics,
  • clinical trials,
  • multiple comparisons,
  • optimal experimental designs.

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Publications of Frank Miller

Publications in peer-reviewed journals

  1. Friede T, Posch M, Zohar S, Alberti C, Benda N, Comets E, Day S, Dmitrienko A, Graf A, Günhan BK, Hee SW, Lentz F, Madan J, Miller F, Ondra T, Pearce M, Röver C, Toumazi A, Unkel S, Ursino M, Wassmer G, Stallard N (2018).
    Recent advances in methodology for clinical trials in small populations: the InSPiRe project.
    Orphanet Journal of Rare Diseases 13: 186.
  2. Miller F, Burman CF (2018).
    A decision theoretical modeling for Phase III investments and drug licensing.
    Journal of Biopharmaceutical Statistics, 28, 698-721.
  3. Miller F, Zohar S, Stallard N, Madan J, Posch M, Hee SW, Pearce M, Vågerö M, Day S (2018).
    Approaches to sample size calculation for clinical trials in rare diseases.
    Pharmaceutical Statistics, 17, 214-230.
    A pre-peer reviewed version is available on the InSPiRe-project homepage.
  4. Pearce M, Hee SW, Madan J, Posch M, Day S, Miller F, Zohar S, Stallard N (2018).
    Value of information methods to design a clinical trial in a small population to optimise a health economic utility function.
    BMC Medical Research Methodology, 18: 20.
  5. Posch M, Klinglmueller F, König F, Miller F (2018).
    Estimation after blinded sample size reassessment.
    Statistical Methods in Medical Research, 27, 1830-1846.
  6. Broberg P, Miller F (2017).
    Conditional estimation in two-stage adaptive designs.
    Biometrics, 73, 895-904.
    The author version of the paper is available on arXiv.
  7. Hee SW, Willis A, Smith CT, Day S, Miller F, Madan J, Posch M, Zohar S, Stallard N (2017).
    Does the low prevalence affect the sample size of interventional clinical trials of rare diseases? An analysis of data from the aggregate analysis of clinicaltrials.gov.
    Orphanet Journal of Rare Diseases, 12: 44.
  8. Stallard N, Miller F, Day S, Hee SW, Madan J, Zohar S, Posch M (2017).
    Determination of the optimal size for a clinical trial accounting for the population size.
    Biometrical Journal, 59, 609-625.
  9. Hee SW, Hamborg T, Day S, Madan J, Miller F, Posch M, Zohar S, Stallard N (2016).
    Decision theoretic designs for small trials and pilot studies: a review.
    Statistical Methods in Medical Research, 25, 1022-1038.
  10. Ondra T, Dmitrienko A, Friede T, Graf A, Miller F, Stallard N, Posch M (2016).
    Methods for identification and confirmation of targeted subgroups in clinical trials: a systematic review.
    Journal of Biopharmaceutical Statistics, 26, 99-119.
  11. Fackle-Fornius E, Miller F, Nyquist H (2015).
    Implementation of maximin efficient designs in dose-finding studies.
    Pharmaceutical Statistics, 14, 63-73.
  12. Karin A, Hannesdottir K, Jaeger J, Annas P, Segerdahl M, Karlsson P, Sjögren N, von Rosen T, Miller F (2014).
    Psychometric evaluation of ADAS-Cog and NTB for measuring drug response.
    Acta Neurologica Scandinavica, 129, 114-122.
  13. Miller F, Björnsson M, Svensson O, Karlsten R (2014).
    Experiences with an adaptive design for a dose-finding study in patients with osteoarthritis.
    Contemporary Clinical Trials, 37, 189-199.
  14. Miner PB Jr, Silberg DG, Ruth M, Miller F, Pandolfino J (2014).
    Dose-dependent effects of lesogaberan on reflux measures in patients with refractory gastroesophageal reflux disease: a randomized, placebo-controlled study.
    BMC Gastroenterology, 14: 188.
  15. Fransson B, Silberg DG, Niazi M, Miller F, Ruth M, Aurell Holmberg A (2012).
    Effect of food on the bioavailability of lesogaberan given as an oral solution or as modified-release capsules in healthy male volunteers.
    International Journal of Clinical Pharmacology and Therapeutics, 50, 307-314.
  16. Friede T, Miller F (2012).
    Blinded continuous monitoring of the nuisance parameter in clinical trials.
    J. Royal Stat. Soc. – Series C, 61, 601-618.
  17. Kalliomäki J, Miller F, Kågedal M, Karlsten R (2012).
    Early phase drug development for treatment of chronic pain – new options for clinical trial and program design.
    Contemporary Clinical Trials, 33, 689-699.
  18. Bischoff W, Miller F (2010).
    D-optimally lack-of-fit-tests-efficient designs with an application to a fertilizer-response-relationship.
    Journal of Statistics and Applications, 5, 119-137.
  19. Dragalin V, Bornkamp B, Bretz F, Miller F, Padmanabhan SK, Patel N, Perevozskaya I, Pinheiro J, Smith JR (2010).
    A simulation study to compare new adaptive dose-ranging designs.
    Statistics in Biopharmaceutical Research, 2, 487-512.
  20. Miller F (2010).
    Adaptive dose-finding: Proof of Concept with type I error control.
    Biometrical Journal, 52, 577-589.
  21. Niazi M, Silberg DG, Miller F, Ruth M, Aurell Holmberg A (2010).
    Evaluation of the Pharmacokinetic Interaction Between Lesogaberan (AZD3355), a Novel Reflux Inhibitor, and Esomeprazole in Healthy Subjects.
    Drugs in R&D, 10(4), 243-251.
  22. Peuskens J, Trivedi J, Brecher M, Miller F on behalf of the Study 4 investigators (2010).
    Long-term symptomatic remission of schizophrenia with once-daily extended release quetiapine fumarate: post-hoc analysis of data from a randomised withdrawal, placebo-controlled study.
    Int Clin Psychopharmacol. 25(3), 183-187.
  23. Pinheiro J, Sax F, Antonijevic Z, Bornkamp B, Bretz F, Chuang-Stein C, Dragalin V, Fardipour P, Gallo P, Gillespie W, Hsu CH, Miller F, Padmanabhan SK, Patel N, Perevozskaya I, Roy A, Sanil A, Smith JR (2010).
    Adaptive and model-based dose-ranging trials: quantitative evaluation and recommendations.
    Statistics in Biopharmaceutical Research, 2, 435-454. Rejoinder p.466-468.
  24. Bischoff W, Miller F (2009).
    A seamless phase II/III design with sample-size re-estimation.
    Journal of Biopharmaceutical Statistics, 19,595-609.
  25. Miller F, Friede T, Kieser M (2009).
    Blinded assessment of treatment effects utilizing information about the randomization block length.
    Statistics in Medicine, 28, 1690-1706.
  26. Newcomer J, Ratner R, Eriksson J, Emsley R, Meulien D, Miller F, Leonova-Edlund J, Leong R, Brecher M (2009).
    A 24-week, multicenter, open-label, randomized study to compare changes in glucose metabolism in patients with schizophrenia receiving treatment with olanzapine, quetiapine and risperidone.
    J Clin Psychiatry 70(4), 487-499.
  27. Möller HJ, Johnson S, Mateva T, Brecher M, Svensson O, Miller F, Meulien D (2008).
    Evaluation of the feasibility of switching from immediate release quetiapine to extended release quetiapine fumarate in stable outpatients with schizophrenia.
    International Clinical Psychopharmacology, 23 (2), 95-105.
  28. Miller F, Guilbaud O, Dette H (2007).
    Optimal designs for estimating the interesting part of a dose-effect curve.
    Journal of Biopharmaceutical Statistics, 17, 1097-1115.
    Link to preprint (at Ruhr-Universität Bochum).
  29. Peuskens J, Trivedi J, Malyarov S, Brecher M, Svensson O, Miller F, Persson I, Meulien D on behalf of the study D1444C00004 investigators (2007).
    Prevention of Schizophrenia Relapse with Extended Release Quetiapine Fumarate Dosed Once Daily: A Randomized, Placebo-Controlled Trial in Clinically Stable Patients.
    Psychiatry, 4, 34-50.
  30. Bischoff W, Miller F (2006).
    Lack-of-fit-efficiently optimal designs to estimate the highest coefficient of a polynomial with large degree.
    Statistics and Probability Letters, 15, 1701-1704.
  31. Bischoff W, Miller F (2006).
    Optimal designs which are efficient for lack of fit tests.
    Annals of Statistics, 34, 2015-2025.
  32. Bischoff W, Miller F. (2006).
    Efficient lack of fit designs that are optimal to estimate the highest coefficient of a polynomial.
    Journal of Statistical Planning and Inference, 136, 4239-4249.
  33. Bischoff W, Hashorva E, Hüsler J, Miller F (2005).
    Analsis of a change-point regression problem in quality control by partial sums processes and Kolmogorov type tests.
    Metrika,62, 85-98.
  34. Bischoff W, Miller F (2005).
    Adaptive two stage test procedures to find the best treatment in clinical trials.
    Biometrika, 92, 197-212.
  35. Miller F (2005).
    Variance estimation in clinical studies with interim sample size re-estimation.
    Biometrics, 61, 355-361.
    Link to preprint.
  36. Bischoff W, Hashorva E, Hüsler J, Miller F (2004).
    On the power of the Kolmogorov test to detect the trend of a Brownian bridge with applications to a change-point problem in regression models.
    Statistics & Probability Letters, 66, 105-115.
  37. Bischoff W, Hashorva E, Hüsler J, Miller F (2003).
    Exact asymptotics for boundary crossings of the Brownian bridge with trend with application to the Kolmogorov test.
    Annals of the Institute of Statistical Mathematics, 55, 849-864.
  38. Bischoff W, Miller F, Hashorva E, Hüsler J (2003).
    Asymptotics of a boundary crossing probability of a Brownian bridge with general trend.
    Methodology and Computing in Applied Probability, 5, 271-287.
  39. Bischoff W, Miller F (2002).
    A minimax two stage procedure for comparing treatments: looking at a hybrid test and estimation problem as a whole.
    Statistica Sinica, 12, 1133-1144.
  40. Friede T, Miller F, Bischoff W, Kieser M (2001).
    A note on change point estimation in dose-response trials.
    Computational Statistics and Data Analysis, 37, 219-232.
  41. Bischoff W, Miller F (2000).
    Asymptotically optimal tests and optimal designs for testing the mean in regression models with applications to change-point problems.
    Annals of the Institute of Statistical Mathematics, 52, 658-679.
  42. Friede T, Kieser M, Miller F (2000).
    Modeling the Recovery from Depressive Illness by an Exponential Model with Mixed Effects.
    Methods of Information in Medicine, 39, 12-15.

Book chapters, book review and discussion-paper

  1. Miller F (2015).
    When is an adaptive design useful in clinical dose-finding trials?
    In Fackle-Fornius E, editor, Festschrift in Honor of Hans Nyquist on the Occasion of his 65th Birthday. Department of Statistics, Stockholm University.
  2. Gaydos B, Koch A, Miller F, Posch M, Vandemeulebroecke M, Wang SJ (2012).
    Perspective on adaptive designs: 4 years European Medicines Agency reflection paper, 1 year draft US FDA guidance – where are we now?
    Clinical Investigation, 2, 235-240.
  3. Burman CF, Miller F, Wong KW (2010).
    Improving dose-finding – a philosophic view.
    Book chapter in Handbook of Adaptive Designs in Pharmaceutical and Clinical Development by Pong, A., Chow, S.C.
  4. Miller F, Wiklund SJ (2008).
    Book review: Adaptive design methods in clinical trials. Shein-Chung Chow and Mark Chang, Chapman & Hall/CRC, Boca Raton, FL, 2007.
    Statistics in Medicine, 27, 4611-4612.

Open access computer program

  1. Program for adaptive multiple contrast tests and other test considered in my article "Adaptive dose-finding: Proof of Concept with type I error control." (Biometrical Journal). Program was peer-reviewed. Open access.

Monographs in German (PhD and diploma thesis)

  1. Miller F (2002).
    Optimale Versuchspläne bei Einschränkungen in der Versuchspunktwahl (Optimal experimental designs under constraints – in German).
    PhD thesis. Fakultät für Mathematik – Universität Karlsruhe.
  2. Miller F (1997).
    Change-point-Probleme im Regressionsmodell und optimale Versuchsplanung (Change-point-problems in regression models and optimal experimental design – in German).
    Diploma thesis. Fakultät für Mathematik - Universität Karlsruhe.

Citations report

    at Google Scholar