F. E. Tan

发表

Robust designs for linear mixed effects models

M. Berger, F. E. Tan, 2004 .

Detection of Influential Observations in Longitudinal Mixed Effects Regression Models

M. Berger, F. E. Tan, M. Ouwens, 2001 .

The effect of dropout on the efficiency of D‐optimal designs of linear mixed models

S. A. Ortega-Azurduy, M. Berger, F. E. Tan, 2008, Statistics in medicine.

The D-Optimality Item Selection Criterion in the Early Stage of CAT: A Study With the Graded Response Model

M. Berger, F. E. Tan, V. L. Passos, 2008 .

Optimal two-stage sampling for mean estimation in multilevel populations when cluster size is informative

F. E. Tan, G. V. van Breukelen, M. Candel, 2020, Statistical methods in medical research.

Relative efficiencies of two‐stage sampling schemes for mean estimation in multilevel populations when cluster size is informative

F. E. Tan, G. V. van Breukelen, M. Candel, 2018, Statistics in medicine.

Does the workplace-smoking ban eliminate differences in risk for environmental tobacco smoke exposure at work?

H. de Vries, F. E. Tan, R. Knibbe, 2009, Health policy.

Test Design Optimization in CAT Early Stage with the Nominal Response Model

M. Berger, F. E. Tan, V. Lima Passos, 2007 .

Robustness of Bayesian D-optimal design for the logistic mixed model against misspecification of autocorrelation

H. Abebe, M. Berger, F. E. Tan, 2014, Computational Statistics.

Imputation of Missing Covariates in Randomized Controlled Trials with Continuous Outcomes: Simple, Unbiased and Efficient Methods

F. E. Tan, G. V. van Breukelen, S. Jolani, 2022, Journal of biopharmaceutical statistics.

Highly Efficient Designs to Handle the Incorrect Specification of Linear Mixed Models

Martijn P. F. Berger, Frans E. S. Tan, S. A. Ortega-Azurduy, 2008, Commun. Stat. Simul. Comput..

Highly Efficient Designs for Logistic Models with Categorical Variables

M. Berger, F. E. Tan, F. Tekle, 2008 .

Imputation of missing covariate in randomized controlled trials with a continuous outcome: Scoping review and new results

Shahab Jolani, Gerard J P van Breukelen, Mutamba T Kayembe, 2020, Pharmaceutical statistics.

OPTIMAL DESIGNS FOR REPEATED MEASURES EXPERIMENTS

M. Berger, F. E. Tan, 2020 .

Bayesian D-optimal designs for the two parameter logistic mixed effects model

Martijn P. F. Berger, Frans E. S. Tan, Gerard J. P. Van Breukelen, 2014, Comput. Stat. Data Anal..

Conditions for D A -Maximin Marginal Designs for Generalized Linear Mixed Models to be Uniform

F. E. Tan, 2010 .

Interactive computer program for optimal designs of longitudinal cohort studies

Martijn P. F. Berger, Frans E. S. Tan, Fetene B. Tekle, 2009, Comput. Methods Programs Biomed..

A maximin criterion for the logistic random intercept model with covariates

Martijn P. F. Berger, Frans E. S. Tan, M. Berger, 2006 .

Robust designs for longitudinal mixed effects models

M. Berger, F. E. Tan, M. Ouwens, 2003 .

OPTIMAL ALLOCATION OF TIME POINTS FOR THE RANDOM EFFECTS MODEL

Martijn P. F. Berger, Frans E. S. Tan, M. Berger, 1999 .

A Multilevel Study of Students in Vietnam: Drinking Motives and Drinking Context as Predictors of Alcohol Consumption

F. E. Tan, N. D. de Vries, R. Knibbe, 2016, International journal of environmental research and public health.

Optimal Designs for One- and Two-Color Microarrays Using Mixed Models: A Comparative Evaluation of Their Efficiencies

Martijn P. F. Berger, Bjorn Winkens, Frans E. S. Tan, 2009, J. Comput. Biol..

Guidelines for multiple imputations in repeated measurements with time-dependent covariates: a case study.

Shahab Jolani, Frans E. S. Tan, Hilde Verbeek, 2018, Journal of clinical epidemiology.

DETECTING INFLUENTIAL OBSERVATIONS AND SUBJECTS IN GENERALIZED LINEAR MIXED MODELS

F. E. Tan, M. Ouwens, 2020 .

Local Influence to Detect Influential Data Structures for Generalized Linear Mixed Models

M. Berger, F. E. Tan, M J Ouwens, 2001, Biometrics.

JMASM45: A Computer Program for Bayesian D-Optimal Binary Repeated Measurements Designs (Matlab)

M. Berger, H. Abebe, F. E. Tan, 2017 .

Bayesian design for dichotomous repeated measurements with autocorrelation

M. Berger, H. Abebe, F. E. Tan, 2015, Statistical methods in medical research.

Robustness of Bayesian D-optimal design for the logistic mixed model against misspecification of autocorrelation

Martijn P. F. Berger, Frans E. S. Tan, Haftom Temesgen Abebe, 2014, Comput. Stat..

On the Choice of a Prior for Bayesian D-Optimal Designs for the Logistic Regression Model with a Single Predictor

Martijn P. F. Berger, Frans E. S. Tan, Gerard J. P. Van Breukelen, 2014, Commun. Stat. Simul. Comput..

Maximin D-optimal designs for binary longitudinal responses

Martijn P. F. Berger, Frans E. S. Tan, Fetene B. Tekle, 2008, Comput. Stat. Data Anal..

Too many cohorts and repeated measurements are a waste of resources.

Martijn P F Berger, Fetene B Tekle, Frans E S Tan, 2011, Journal of clinical epidemiology.

D‐optimal cohort designs for linear mixed‐effects models

Martijn P F Berger, Fetene B Tekle, Frans E S Tan, 2008, Statistics in medicine.

Best Practices in Analysis of Longitudinal Data: A Multilevel Approach

Frans E. S. Tan, F. E. Tan, 2008 .

A comparison of classroom and online asynchronous problem-based learning for students undertaking statistics training as part of a Public Health Masters degree

F. E. Tan, S. O’Connor, N. de Jong, 2012, Advances in health sciences education : theory and practice.

ODMixed: A tool to obtain optimal designs for heterogeneous longitudinal studies with dropout

Martijn P. F. Berger, Shirley Ortega, Frans E. S. Tan, 2011, Comput. Methods Programs Biomed..