Statistical Methodological Research

Within biometrical and epidemiological research we aim to develop statistical methods that optimize planning and analysis of clinical and epidemiological studies.

Our statistical research focuses on:

  • Adaptive Designs
  • Sample Size Calculation and Recalculation
  • Multilevel Models
  • Multistage Models
  • Multiple Testing Problems



Systematic comparison of approaches to analyze clustered competing risks data
Schmitt S, Buchholz A, Ozga A
BMC MED RES METHODOL. 2023;23(1):86.

Missing values and inconclusive results in diagnostic studies - A scoping review of methods
Stahlmann K, Reitsma J, Zapf A
STAT METHODS MED RES. 2023 [Epub ahead of print];9622802231192954.


A semiparametric approach for meta-analysis of diagnostic accuracy studies with multiple cut-offs
Frömke C, Kirstein M, Zapf A
RES SYNTH METHODS. 2022;13(5):612-621.

Convergence Behavior of Optimal Cut-Off Points Derived from Receiver Operating Characteristics Curve Analysis: A Simulation Study
Gerke O, Zapf A
MATHEMATICS-BASEL. 2022;10(22):.

Sample size recalculation based on the prevalence in a randomized test-treatment study
Hot A, Benda N, Bossuyt P, Gerke O, Vach W, Zapf A
BMC MED RES METHODOL. 2022;22(1):.

Weighted composite time to event endpoints with recurrent events: comparison of three analytical approaches
Ozga A, Rauch G
BMC MED RES METHODOL. 2022;22(1):.

Diagnostic accuracy of cerebrospinal fluid biomarkers for the differential diagnosis of sporadic Creutzfeldt-Jakob disease: a (network) meta-analysis
Rübsamen N, Pape S, Konigorski S, Zapf A, Rücker G, Karch A
EUR J NEUROL. 2022;29(5):1366-1376.

Blinded sample size re-estimation in a comparative diagnostic accuracy study
Stark M, Hesse M, Brannath W, Zapf A
BMC MED RES METHODOL. 2022;22(1):115.

A multiple testing framework for diagnostic accuracy studies with co-primary endpoints
Westphal M, Zapf A, Brannath W
STAT MED. 2022;41(5):891-909.


Biomarker-Guided Risk Assessment for Acute Kidney Injury: Time for Clinical Implementation?
Albert C, Haase M, Albert A, Zapf A, Braun-Dullaeus R, Haase-Fielitz A
ANN LAB MED. 2021;41(1):1-15.

Statistical model building: Background "knowledge" based on inappropriate preselection causes misspecification
Hafermann L, Becher H, Herrmann C, Klein N, Heinze G, Rauch G
BMC MED RES METHODOL. 2021;21(1):196.

Randomized test-treatment studies with an outlook on adaptive designs
Hot A, Bossuyt P, Gerke O, Wahl S, Vach W, Zapf A
BMC MED RES METHODOL. 2021;21(1):110.

Studies for the Evaluation of Diagnostic Tests- Part 28 of a Series on Evaluation of Scientific Publications
Hoyer A, Zapf A
DTSCH ARZTEBL INT. 2021;118:555-560.

A potential for seamless designs in diagnostic research could be identified
Vach W, Bibiza E, Gerke O, Bossuyt P, Friede T, Zapf A
J CLIN EPIDEMIOL. 2021;129:51-59.

Meta-analysis of diagnostic accuracy studies with multiple thresholds: Comparison of different approaches
Zapf A, Albert C, Frömke C, Haase M, Hoyer A, Jones H, Rücker G
BIOMETRICAL J. 2021;63(4):699-711.

12. Einsatz von Audience Response Systemen in der Lehre: Didaktisches Konzept und konkrete Beispiele
Zapf A, Cevirme S
2021. Zeig mir Health Data Science!. Herrmann C, Berger D, Weiß P, Burkholder P, Rauch P, Kruppa D (eds.). 1. ed. Berlin: Springer Spektrum, Berlin, Heidelberg, 143-159.


Reevaluation of risk factors for time to subsequent events after first stroke occurrence using a new weighted all-cause effect measure
Ozga A, Rauch B, Palm F, Urbanek C, Grau A, Becher H, Rauch G
BMC PUBLIC HEALTH. 2020;20(1):817.

Sample size calculation and re-estimation based on the prevalence in a single-arm confirmatory diagnostic accuracy study
Stark M, Zapf A
STAT METHODS MED RES. 2020;29(10):2958–2971.

Blinded sample size reestimation for negative binomial regression with baseline adjustment
Zapf A, Asendorf T, Anten C, Mütze T, Friede T
STAT MED. 2020;39(14):1980-1998.

Why do you need a biostatistician?
Zapf A, Rauch G, Kieser M
BMC MED RES METHODOL. 2020;20(1):23.

Adaptive trial designs in diagnostic accuracy research
Zapf A, Stark M, Gerke O, Ehret C, Benda N, Bossuyt P, Deeks J, Reitsma J, Alonzo T, Friede T
STAT MED. 2020;39(5):591-601.


Introducing a new estimator and test for the weighted all-cause hazard ratio
Ozga A, Rauch G
BMC MED RES METHODOL. 2019;19(1):118.

High Aldehyde Dehydrogenase Levels Are Detectable in the Serum of Patients with Lung Cancer and May Be Exploited as Screening Biomarkers
Rossi A, Voigtländer M, Klose H, Schlüter H, Schön G, Loges S, Paolini M, Bokemeyer C, Reck M, Tarro G, Binder M
J ONCOL. 2019;2019:8970645.

What makes a biostatistician?
Zapf A, Huebner M, Rauch G, Kieser M
STAT MED. 2019;38(4):695-701.


A systematic comparison of recurrent event models for application to composite endpoints
Ozga A, Kieser M, Rauch G
BMC MED RES METHODOL. 2018;18(1):2.

Appraising Heterogeneity
Zapf A
2018. Diagnostic Meta-Analysis . Biondi-Zoccai G (eds.). 1. ed. Berlin: Springer International Publishing, 125-160.


Investigation of the performance of trimmed estimators of life time distributions with censoring
Clarke B, Höller A, Müller C, Wamahiu K
AUST NZ J STAT. 2017;59(4):513-525.

Do we consent to rules of consent and confidentiality?
Wegscheider K, Friede T
BIOMETRICAL J. 2017;59(2):235-239.

Big Data Analytics
Wegscheider K, Koch-Gromus U
2017. Lehrbuch Versorgungsforschung Systematik - Methodik - Anwendung. Pfaff H, A.M. Neugebauer E, Glaeske G, Schrappe M (eds.). 2.. ed. Schattauer, 134-139.

Doppelgänger lehren uns das Grundprinzip des statistischen Testens
Zapf A, Frömke C, Rosenberger A
2017. Zeig mir mehr Biostatistik . Vonthein R, Burkholder I, Muche R, Rauch G (eds.). Berlin, Heidelberg: Springer Spektrum, Berlin, Heidelberg, 61-70.


Teilhabeforschung: Bedeutung, Konzepte, Zielsetzung und Methoden
Brütt A, Buschmann-Steinhage R, Kirschning S, Wegscheider K
BUNDESGESUNDHEITSBLA. 2016;59(9):1068-74.

Safety data from randomized controlled trials: applying models for recurrent events.
Hengelbrock J, Gillhaus J, Kloss S, Leverkus F
PHARM STAT. 2016;15(4):315-323.

Partial verification bias and incorporation bias affected accuracy estimates of diagnostic studies for biomarkers that were part of an existing composite gold standard
Karch A, Koch A, Zapf A, Zerr I, Karch A
J CLIN EPIDEMIOL. 2016;78:73-82.

Improving the Prognostic Ability through Better Use of Standard Clinical Data - The Nottingham Prognostic Index as an Example
Winzer K, Buchholz A, Schumacher M, Sauerbrei W
PLOS ONE. 2016;11(3):e0149977.

Measuring inter-rater reliability for nominal data - which coefficients and confidence intervals are appropriate?
Zapf A, Castell S, Morawietz L, Karch A

Propensity Scoring after Multiple Imputation in a Retrospective Study on Adjuvant Radiation Therapy in Lymph-Node Positive Vulvar Cancer
zu Eulenburg C, Suling A, Neuser P, Reuss A, Canzler U, Fehm T, Luyten A, Hellriegel M, Woelber L, Mahner S
PLOS ONE. 2016;11(11):e0165705.


Simulating recurrent event data with hazard functions defined on a total time scale
Jahn-Eimermacher A, Ingel K, Ozga A, Preussler S, Binder H

Nutzenbewertung aus Sicht der Versorgungsforschung und der Epidemiologie.
Wegscheider K, Drabik A, Bleich C, Schulz H
BUNDESGESUNDHEITSBLA. 2015;58(3):298-307.

Die Versorgungsforschung als möglicher Profiteur von Big Data
Wegscheider K, Koch-Gromus U
BUNDESGESUNDHEITSBLA. 2015;58(8):806-812.

A wild bootstrap approach for the selection of biomarkers in early diagnostic trials
Zapf A, Brunner E, Konietschke F

Nonparametric meta-analysis for diagnostic accuracy studies
Zapf A, Hoyer A, Kramer K, Kuss O
STAT MED. 2015;34(29):3831-3841.


Nonparametric ROC analysis for diagnostic trials.
Brunner E, Zapf A
2014. Methods and Applications of Statistics in Clinical Trials, . Balakrishnan N (eds.). June 2014. ed. Wiley, 483-495.

A measure for assessing functions of time-varying effects in survival analysis
Buchholz A, Sauerbrei W, Royston P
Open J Stat. 2014;4(11):977-998.

A modified Wald interval for the area under the ROC curve (AUC) in diagnostic case-control studies
Kottas M, Kuss O, Zapf A

Disease-Management-Programme - was wurde bisher erreicht?
Wegscheider K, Drabik A, Kaduszkiewicz H, Schäfer I, Bussche van den H
2014. Ergebnisverbesserung durch Qualitätsmanagement - Aktuelle Maßnahmen, Nachweise, Stand der Evaluierung. Jonitz G, Mansky T, Scriba P, Selbmann H (eds.). 1. ed. Köln: Deutscher Ärzte-Verlag, 145-154.


Difference of two dependent sensitivities and specificities: Comparison of various approaches
Wenzel D, Zapf A
BIOMETRICAL J. 2013;55(5):705-718.

Letzte Aktualisierung aus dem FIS: 25.09.2023 - 04:35 Uhr