D. Böhning

D. Böhning, S. Sornmani, F. Schelp, 1990, Tropical medicine and parasitology : official organ of Deutsche Tropenmedizinische Gesellschaft and of Deutsche Gesellschaft fur Technische Zusammenarbeit.

Upper bound estimators of the population size based on ordinal models for capture‐recapture experiments

D. Böhning, M. Alfò, I. Rocchetti, 2020, Biometrics.

Prevention of Neurological Complications During COVID-19: Protocol for a Retrospective Analysis of the ISARIC4C National Cohort

D. Böhning, Chieh-Hsi Wu, I. Galea, 2022, SSRN Electronic Journal.

Uncertainty estimation in heterogeneous capture–recapture count data

D. Böhning, A. Maruotti, Orasa Anan, 2017 .

Correspondence: Some general points regarding Ledberg and Wennberg, BMC Medical Research Methodology 2014 April 27;14:58

D. Böhning, P. V. D. van der Heijden, 2015, BMC Medical Research Methodology.

Extending Zelterman's Approach for Robust Estimation of Population Size to Zero‐truncated Clustered Data

D. Böhning, V. J. Del Rio Vilas, W. C. W. Navaratna, 2008, Biometrical journal. Biometrische Zeitschrift.

Delayed antibiotic prescribing for respiratory tract infections: individual patient data meta-analysis

D. Böhning, B. Arroll, B. Stuart, 2021, BMJ.

A simple test for the difference of means in meta-analysis when study-specific variances are unreported

D. Böhning, P. Sangnawakij, 2020, Journal of Statistical Computation and Simulation.

A modification of Chao’s lower bound estimator in the case of one-inflation

D. Böhning, P. V. D. van der Heijden, P. V. D. Heijden, 2018, Metrika.

Estimating the size of undetected cases of the COVID-19 outbreak in Europe: an upper bound estimator

D. Böhning, A. Maruotti, H. Holling, 2020 .

Capture-Recapture Methods for the Social and Medical Sciences

J. Bunge, D. Böhning, P. V. D. Heijden, 2017 .

The 2nd special issue on advances in mixture models

Geoffrey J. McLachlan, Paul D. McNicholas, Christian Hennig, 2014, Computational Statistics & Data Analysis.

Estimation of Effect Heterogeneity in Rare Events Meta-Analysis

D. Böhning, H. Holling, K. Jansen, 2022, Psychometrika.

General flation models for count data

D. Böhning, Helen Ogden, 2020, Metrika.

Imputing unobserved values with the EM algorithm under left and right‐truncation, and interval censoring for estimating the size of hidden populations

D. Böhning, Matthew L. Robb, 2011, Biometrical journal. Biometrische Zeitschrift.

Jeffreys' Likelihood Ratio for the 2×2-Table — A Monte Carlo Study —

D. Böhning, H. Rolling, G. Kaufhold, 1984 .

The Effects of Recombinant Human Insulin-Like Growth Factor-I/Insulin-Like Growth Factor Binding Protein-3 Administration on Body Composition and Physical Fitness in Recreational Athletes.

D. Böhning, P. Sönksen, R. Holt, 2015, The Journal of clinical endocrinology and metabolism.

Evaluation of the Cumulative Evidence for Freedom from BSE in Birth Cohorts

D. Böhning, M. Greiner, 2005, European Journal of Epidemiology.

Estimating risk and rate ratio in rare events meta-analysis with the Mantel–Haenszel estimator and assessing heterogeneity

D. Böhning, H. Holling, P. Sangnawakij, 2022, The international journal of biostatistics.

Some general points on the $$I^2$$I2-measure of heterogeneity in meta-analysis

D. Böhning, H. Holling, R. Lerdsuwansri, 2017 .

A Generalization of Chao's Estimator for Covariate Information

D. Böhning, C. Viwatwongkasem, M. Arnold, 2013, Biometrics.

Population size estimation based upon zero-truncated, one-inflated and sparse count data

D. Böhning, H. Friedl, 2021, Statistical Methods & Applications.

General flation models for count data

D. Böhning, Helen E. Ogden, 2020, Metrika.

On the Turing estimator in capture–recapture count data under the geometric distribution

D. Böhning, A. Maruotti, Orasa Anan, 2018, Metrika.

Population size estimation and heterogeneity in capture–recapture data: a linear regression estimator based on the Conway–Maxwell–Poisson distribution

D. Böhning, A. Maruotti, Orasa Anan, 2016, Statistical Methods & Applications.

Capture–recapture estimation based upon the geometric distribution allowing for heterogeneity

D. Böhning, P. V. D. van der Heijden, H. Holling, 2012, Metrika.

Count outcome meta-analysis for comparing treatments by fusing mixed data sources: comparing interventions using across report information

D. Böhning, P. Sangnawakij, 2020, AStA Advances in Statistical Analysis.

Computer-assisted analysis of mixtures (C.A.MAN) statistical algorithms

Bruce G. Lindsay, Dankmar Böhning, Peter Schlattmann, 1992 .

Relationship of the morbidity of under-fives to anthropometric measurements and community health intervention.

D. Böhning, S. Sornmani, F. Schelp, 1990, Tropical medicine and parasitology : official organ of Deutsche Tropenmedizinische Gesellschaft and of Deutsche Gesellschaft fur Technische Zusammenarbeit.

Estimating population diversity with CatchAll

James A. Foster, John Bunge, Sean Connolly, 2012, Bioinform..

A mixed model approach to meta-analysis of diagnostic studies with binary test outcome.

Heinz Holling, Dankmar Böhning, Philipp Doebler, 2012, Psychological methods.

Evaluation of a new version of I2 with emphasis on diagnostic problems

Heinz Holling, Walailuck Böhning, Ehsan Masoudi, 2020, Commun. Stat. Simul. Comput..

Meta-analysis and meta-modelling for diagnostic problems

Heinz Holling, Walailuck Böhning, Dankmar Böhning, 2014, BMC Medical Research Methodology.

Meta-analysis of diagnostic studies based upon SROC-curves: a mixed model approach using the Lehmann family

Heinz Holling, Dankmar Böhning, Walailuck Böhning, 2012 .

Likelihood-Based Clustering of Meta-Analytic SROC Curves

Heinz Holling, Dankmar Böhning, Walailuck Böhning, 2012 .

Minimum MSE Weights of Adjusted Summary Estimator of Risk Difference in Multi-Center Studies

D. Böhning, Jirawan Jitthavech, C. Viwatwongkasem, 2012 .

Zero‐Inflated Poisson Models and C.A.MAN: A Tutorial Collection of Evidence

Dankmar Böhning, D. Böhning, 1998 .

A limitation of the diagnostic-odds ratio in determining an optimal cut-off value for a continuous diagnostic test

Heinz Holling, Dankmar Böhning, Valentin Patilea, 2011, Statistical methods in medical research.

Revisiting youden's index as a useful measure of the misclassification error in meta-analysis of diagnostic studies

Heinz Holling, Walailuck Böhning, Dankmar Böhning, 2008, Statistical methods in medical research.

Meta-Analysis of Binary Data Based upon Dichotomized Criteria

D. Böhning, H. Holling, W. Böhning, 2007 .

Meta-Analysis

D. Böhning, 2005, Methods of Information in Medicine.

Some general points in estimating heterogeneity variance with the DerSimonian-Laird estimator.

Chukiat Viwatwongkasem, Dankmar Böhning, Annibale Biggeri, 2002, Biostatistics.

Nonparametric estimation of heterogeneity variance for the standardised difference used in meta-analysis

Heinz Holling, Dankmar Böhning, Uwe Malzahn, 2000 .

Estimating Risk Difference in Multicenter Studies Under Baseline‐Risk Heterogeneity

D. Böhning, J. Sarol, 2000, Biometrics.

Estimation of stray dog and cat populations in metropolitan Ankara, Turkey

D. Böhning, D. Özen, I. S. Gürcan, 2016 .

Meta-analysis : new developments and applications in medical and social sciences

Heinz Holling, Dankmar Böhning, Ralf Schulze, 2003 .

Computer-Assisted Analysis of Mixtures and Applications: Meta-Analysis, Disease Mapping, and Others

Dankmar Böhning, D. Böhning, 1999 .

Prevalence estimation under heterogeneity in the example of bovine trypanosomosis in Uganda.

D. Böhning, M. Greiner, 1998, Preventive veterinary medicine.

Impact of biological factors on the interpretation of bovine trypanosomosis serology.

D. Böhning, M. Greiner, E. Dietz, 1997, Preventive veterinary medicine.

Non-parametric maximum likelihood estimators for disease mapping.

D Böhning, M Martuzzi, A Biggeri, 2000, Statistics in medicine.

A Capture–Recapture Approach for Screening Using Two Diagnostic Tests With Availability of Disease Status for the Test Positives Only

Dankmar Böhning, Valentin Patilea, D. Böhning, 2008 .

Asymptotic properties of the EM algorithm estimate for normal mixture models with component specific variances

Dankmar Böhning, Dechavudh Nityasuddhi, D. Böhning, 2003, Comput. Stat. Data Anal..

Analysis of longitudinal data using a finite mixture model

D. Böhning, E. Dietz, 1994 .

Pregnancy, nutrition and parasitic infection of rural and urban women in Northeast Thailand

D. Böhning, P. Lumbiganon, A. Hempfling, 1992 .

The development of decision limits for the GH-2000 detection methodology using additional insulin-like growth factor-I and amino-terminal pro-peptide of type III collagen assays.

D. Böhning, P. Sönksen, E. Bassett, 2015, Drug testing and analysis.

The zero‐inflated Poisson model and the decayed, missing and filled teeth index in dental epidemiology

Dankmar Böhning, Peter Schlattmann, Ekkehart Dietz, 1999 .

The identity of the zero-truncated, one-inflated likelihood and the zero-one-truncated likelihood for general count densities with an application to drink-driving in Britain

D. Böhning, P. V. D. Heijden, P. Heijden, 2019, The Annals of Applied Statistics.

Does thoracoscopy have advantages over open surgery for asymptomatic congenital lung malformations? An analysis of 1626 resections.

D. Böhning, P. Sangnawakij, M. Stanton, 2017, Journal of pediatric surgery.

Count outcome meta-analysis for comparing treatments by fusing mixed data sources: comparing interventions using across report information

D. Böhning, P. Sangnawakij, 2020, AStA Advances in Statistical Analysis.

Comparing interventions using across report information

D. Böhning, Patarawan, Sangnawakij, 2020 .

Statistical methodology for estimating the mean difference in a meta‐analysis without study‐specific variance information

D. Böhning, H. Holling, P. Sangnawakij, 2017, Statistics in medicine.

Bayesian spatio-temporal joint disease mapping of Covid-19 cases and deaths in local authorities of England

S. Sahu, D. Böhning, 2021, Spatial Statistics.

Delayed antibiotic prescribing for respiratory tract infections: individual patient data meta-analysis

D. Böhning, B. Arroll, B. Stuart, 2021, BMJ.

Fewer COVID‐19 Neurological Complications with Dexamethasone and Remdesivir

D. Böhning, Chieh-Hsi Wu, J. Baillie, 2022, Annals of neurology.

Can digital rectal examination be used to detect cauda equina compression in people presenting with acute cauda equina syndrome? A systematic review and meta-analysis of diagnostic test accuracy studies.

D. Böhning, N. Wilson, D. Phillips, 2022, Musculoskeletal science & practice.

Nonparametric Estimation of Effect Heterogeneity in Rare Events Meta-Analysis: Bivariate, Discrete Mixture Model

Heinz Holling, Patarawan Sangnawakij, Dankmar Böhning, 2021, Lobachevskii Journal of Mathematics.

A nonparametric random coefficient approach for life expectancy growth using a hierarchical mixture likelihood model with application to regional data from North Rhine-Westphalia (Germany)

R. Fehr, D. Böhning, C. Terschüren, 2013, BMC Medical Research Methodology.

Finite Mixture and Markov Switching Models by S. FRÜHWIRTH‐SCHNATTER

D. Böhning, 2007 .

Equivalence of Truncated Count Mixture Distributions and Mixtures of Truncated Count Distributions

Dankmar Böhning, Ronny Kuhnert, D. Böhning, 2006, Biometrics.

Editorial: recent developments in mixture models

Wilfried Seidel, Dankmar Böhning, D. Böhning, 2003, Comput. Stat. Data Anal..

A transitional non-parametric maximum pseudo-likelihood estimator for disease mapping

Dankmar Böhning, Annibale Biggeri, Corrado Lagazio, 2003, Comput. Stat. Data Anal..

Some News about C.A.MAN Computer Assisted Analysis of Mixtures

D. Böhning, E. Dietz, D. Böhning, 1998 .

A vertex-exchange-method in D-optimal design theory

Dankmar Böhning, D. Böhning, 1986 .

Numerical estimation of a probability measure

Dankmar Böhning, D. Böhning, 1985 .

Delayed antibiotic prescribing for respiratory tract infections: protocol of an individual patient data meta-analysis

D. Böhning, B. Arroll, B. Stuart, 2019, BMJ Open.

Sensitivity of contact-tracing for COVID-19 in Thailand: a capture-recapture application

D. Böhning, V. J. Del Rio Vilas, J. Polonsky, 2022, BMC Infectious Diseases.

Comparison of normal distribution–based and nonparametric decision limits on the GH‐2000 score for detecting growth hormone misuse (doping) in sport

D. Böhning, F. Bretz, Wei Liu, 2020, Biometrical journal. Biometrische Zeitschrift.

Estimating the undetected infections in the Monkeypox outbreak

D. Böhning, A. Maruotti, M. Ciccozzi, 2022, Journal of medical virology.

Alpha-2-macroglobulin, 3-methylhistidine and other biochemical parameters in healthy thai males

D. Böhning, F. Schelp, R. Tungtrongchitr, 1989 .

The Covariate-Adjusted Frequency Plot for the Rasch Poisson Counts Model

D. Böhning, H. Holling, W. Böhning, 2015 .

The EM algorithm with gradient function update for discrete mixtures with known (fixed) number of components

Dankmar Böhning, D. Böhning, 2003, Stat. Comput..

Estimators in capture–recapture studies with two sources

Dankmar Böhning, D. Böhning, Sarah Brittain, 2009 .

Investigating heterogeneity in meta-analysis of studies with rare events

Heinz Holling, Patarawan Sangnawakij, Dankmar Böhning, 2021, METRON.

The identity of two meta-analytic likelihoods and the ignorability of double-zero studies.

D. Böhning, P. Sangnawakij, 2020, Biostatistics.

Risk factors for traffic accidents in Bangkok Metropolis: a case-reference study.

D Böhning, D. Böhning, R S Na Ayuthya, 1997, The Southeast Asian journal of tropical medicine and public health.

Covariate adjusted mixture models and disease mapping with the program DismapWin.

P Schlattmann, D Böhning, E Dietz, 1996, Statistics in medicine.

Non-invasive tests for the detection of oesophageal varices in compensated cirrhosis: systematic review and meta-analysis

D. Böhning, S. Sami, I. Guha, 2018, United European gastroenterology journal.

Recent developments in life and social science applications of capture–recapture methods

D. Böhning, D. Boehning, P. V. D. Heijden, 2009 .

CAMCR: Computer-Assisted Mixture model analysis for Capture–Recapture count data

D. Böhning, R. Kuhnert, 2009 .

Mixture models for capture-recapture count data

Dankmar Böhning, Ekkehart Dietz, Dieter Schön, 2005, Stat. Methods Appl..

Erratum to: Correspondence: Some general points regarding Ledberg and Wennberg, BMC Medical Research Methodology 2014 April 27;14:58

D. Böhning, P. V. D. van der Heijden, 2015, BMC Medical Research Methodology.

A regression estimator for mixed binomial capture-recapture data

D. Böhning, M. Alfò, I. Rocchetti, 2014 .

An extension of Chao's estimator of population size based on the first three capture frequency counts

Dankmar Böhning, K. Lanumteang, D. Böhning, 2011, Comput. Stat. Data Anal..

Impact of Dexamethasone and Remdesivir on Neurological Complications during COVID-19

D. Böhning, Chieh-Hsi Wu, J. Baillie, 2022, Social Science Research Network.

Nurse staffing levels, missed vital signs observations and mortality in hospital wards: retrospective longitudinal observational study using routinely collected data - Final report

Jim Briggs, Antonello Maruotti, Dankmar Böhning, 2018 .

Editorial – Recent Developments in Capture‐Recapture Methods and Their Applications

Dankmar Böhning, D. Böhning, 2008, Biometrical journal. Biometrische Zeitschrift.

The relationship between alcohol consumption, health indicators and mortality in the German population.

D. Böhning, Gert B. M. Mensink, H. Hoffmeister, 1999, International journal of epidemiology.

Estimating the size of hard-to-reach populations using capture-recapture methodology, with a discussion of the International Labour Organization’s global estimate of forced labour : Special issue: Researching hidden populations: approaches to and methodologies for generating data on trafficking in p

D. Böhning, M. Cruyff, I. Vries, 2015 .

Some General Comparative Points on Chao's and Zelterman's Estimators of the Population Size

D. Böhning, 2010 .

Retrospective evaluation of factors affecting successful fit testing of respiratory protective equipment during the early phase of COVID-19

D. Böhning, D. Bader, P. Worsley, 2023, BMJ Open.

Novel Use of Capture-Recapture Methods to Estimate Completeness of Contact Tracing during an Ebola Outbreak, Democratic Republic of the Congo, 2018–2020

D. Böhning, V. D. Vilas, S. Ahuka-Mundeke, 2021, Emerging infectious diseases.

Youden’s Index and the Likelihood Ratio Positive in Diagnostic Testing

D. Böhning, 2015, Methods of Information in Medicine.

The Use of Two-Component Mixture Models with One Completely or Partly Known Component

Dankmar Böhning, D. Böhning, E. Dietz, 1997 .

Editorial for the discussion papers on the p‐value controversy

D. Böhning, M. Alfò, 2017, Biometrical journal. Biometrische Zeitschrift.

Re: Insights into latent class analysis of diagnostic test performance.

D. Böhning, A. Formann, 2008, Biostatistics.

A comparison of the active surveillance of scrapie in the European Union.

Dankmar Böhning, Ronny Kuhnert, D. Böhning, 2008, Veterinary research.

On estimation of the Poisson parameter in zero-modified Poisson models

Dankmar Böhning, D. Böhning, E. Dietz, 2000 .

Capture recapture to estimate criminal populations

D. Böhning, M. Cruyff, P. Heijden, 2014 .

An extension of an over-dispersion test for count data

Dankmar Böhning, M. Fazil Baksh, Rattana Lerdsuwansri, 2011, Comput. Stat. Data Anal..

Estimating Population Diversity with Unreliable Low Frequency Counts

James A. Foster, John Bunge, Dankmar Böhning, 2012, Pacific Symposium on Biocomputing.

Novel application of capture-recapture methods to estimate the completeness of contact tracing during a large outbreak of Ebola Virus Disease, Democratic Republic of Congo, 2018-2020

D. Böhning, S. Ahuka-Mundeke, Z. Yoti, 2021, medRxiv.

On the equivalence of one‐inflated zero‐truncated and zero‐truncated one‐inflated count data likelihoods

D. Böhning, 2022, Biometrical journal. Biometrische Zeitschrift.

Population size estimation based upon zero-truncated, one-inflated and sparse count data

D. Böhning, H. Friedl, 2021, Statistical Methods & Applications.

Chao’s lower bound estimator and the size of the Pleiades

D. Böhning, 2020, Environmental and Ecological Statistics.

On the Turing estimator in capture–recapture count data under the geometric distribution

D. Böhning, A. Maruotti, Orasa Anan, 2018, Metrika.

Estimating the number of dice snakes in Graz and flare stars in the Pleiades

D. Böhning, H. Friedl, 2020 .

Confidence interval estimation of a rate and the choice of sample size.

D. Böhning, 1988, Statistics in medicine.

On the question of proportionality of the count of observed Scrapie cases and the size of holding

D. Böhning, V. J. Del Rio Vilas, 2009, BMC veterinary research.

Meta-analysis of Binary Data Using Profile Likelihood

Dankmar Böhning, Ronny Kuhnert, Sasivimol Rattanasiri, 2008 .

Application of the Vertex Exchange Method to estimate a semi-parametric mixture model for the MIC density of Escherichia coli isolates tested for susceptibility against ampicillin.

Geert Verbeke, Dankmar Böhning, Marc Aerts, 2015, Biostatistics.

A Bagging‐Based Correction for the Mixture Model Estimator of Population Size

Dankmar Böhning, Ronny Kuhnert, D. Böhning, 2008, Biometrical journal. Biometrische Zeitschrift.

Advances in Mixture Models

Marco Alfò, Wilfried Seidel, Dankmar Böhning, 2007, Comput. Stat. Data Anal..

A comparison of three different models for estimating relative risk in meta‐analysis of clinical trials under unobserved heterogeneity

Dankmar Böhning, Ronny Kuhnert, D. Böhning, 2007, Statistics in medicine.

Asymptotic Normality in Mixtures of Power Series Distributions

Dankmar Böhning, Valentin Patilea, D. Böhning, 2005 .

Exact statistical calculation of the uncertainty term in the decision limits of the GH-2000 score for growth hormone misuse (doping) detection

D. Böhning, Wei Liu, P. Sönksen, 2019, Statistical methods in medical research.

Exact statistical calculation of the uncertainty term in the decision limits based on the GH-2000 score for growth hormone misuse detection ( doping )

D. Böhning, Wei Liu, P. Sönksen, 2017 .

A modification of Chao’s lower bound estimator in the case of one-inflation

D. Böhning, P. V. D. van der Heijden, Panicha Kaskasamkul, 2018, Metrika.

Use of the Ratio Plot in Capture–Recapture Estimation

D. Böhning, J. Gallagher, R. Lerdsuwansri, 2013 .

Why do endocrine profiles in elite athletes differ between sports?

D. Böhning, P. Sönksen, R. Holt, 2018, Clinical Diabetes and Endocrinology.

Computational Statistics and Data Analysis an Extension of an Over-dispersion Test for Count Data

D. Böhning, R. Lerdsuwansri, M. Fazil Baksh, 2022 .

On Bayesian analysis of mixtures with an unknown number of components. Discussion. Author's reply

J. Besag, P. Green, S. Richardson, 1997 .

Improved methods for surveying and monitoring crimes through likelihood based cluster analysis

Dankmar Böhning, Isak Neema, D. Böhning, 2010 .

Mixture models and disease mapping.

P Schlattmann, D Böhning, D. Böhning, 1993, Statistics in medicine.

Statistical Inference Based on a General Model of Unobserved Heterogeneity

Dankmar Böhning, D. Böhning, E. Dietz, 1995 .

1 A comparison of three different models for estimating relative risk in meta-analysis of clinical trials under 3 unobserved heterogeneity

D. Böhning, R. Kuhnert, 2006 .

On minimizing chi-square distances under the hypothesis of homogeneity or independence for a two-way contingency table

D. Böhning, H. Holling, 1986 .

A monte carlo study on minimizing chi-square distances under the hypothesis of homogeneity or independence for a two-way cotingeney table

D. Böhning, H. Holling, 1989 .

Confidence interval estimation for the Mantel–Haenszel estimator of the risk ratio and risk difference in rare event meta-analysis with emphasis on the bootstrap

D. Böhning, H. Holling, P. Sangnawakij, 2021, Journal of Statistical Computation and Simulation.

Editorial – Recent Developments in Capture‐Recapture Methods and Their Applications

D. Böhning, 2008, Biometrical journal. Biometrische Zeitschrift.

Space-time mixture modelling of public health data.

P Schlattmann, D Böhning, E Dietz, 2000, Statistics in medicine.

Empirical Bayes estimators and non‐parametric mixture models for space and time–space disease mapping and surveillance

Dankmar Böhning, D. Böhning, 2003 .