Dr. Michael Höfler

Technische Universität Dresden,
Institute of Clinical Psychology and Psychotherapy,
Chemnitzer Strasse 46,
01187 Dresden (Germany);
 

Tel: ++49 351 463 36921 Michael.Hoefler@tu-dresden.de

Scientific Education and Academic Degrees

07/2007	Dissertation (Dr.phil.; Ph.D.), Universität Basel, Switzerland
12/1997	Diploma Statistics, Ludwig Maximilians Universität, Germany

Professional and Clinical Experience

since 01/2006	Research assistant at the Institute of Clinical Psychology and Psychotherapy, Dresden Technical University Consulting of PhD students a.o. in epidemiological and clinical statistics Analysis of several epidemiological studies, RCTs, experimental and other studies Lectures and seminars for master students of psychology in methods and statistics
1999-2005	Research assistant at the Max Planck Institute of Psychiatry, Department of Clinical Psychology and Epidemiology in Munich

Selected methodical publications

Höfler M, Venz J, Trautmann S, Miller R. Writing a discussion section: how to integrate substantive and statistical expertise. BMC Medical Rearch Methodology 2018; 18:34

Höfler M, Hoyer J. Population size matters: bias in conventional meta-analysis. International Journal of Social Research Methodology 2014, 17: 585-597.

Höfler M, Gloster AT, Hoyer J. Causal effects in psychotherapy: Counterfactuals counteract overgeneralization. Psychotherapy Research 2010; 20:668-79

Höfler M, Lieb R, Wittchen HU. Estimating causal effect from observational data conditionally on a model for multiple bias. International Journal of Methods in Psychiatry Research 2007; 16:77-87.

Höfler M, Seaman SR. Re-interpreting conventional interval estimates taking into account bias and extra-variation. BMC Medical Research Methodology 2006; 6:51.

Höfler M. Getting causal considerations back on the right track. Emerging Themes in Epidemiology 2006; 3:8.

Höfler M. The Bradford Hill considerations on causality: A counterfactual perspective. Emerging Themes in Epidemiology 2005; 2:11

Höfler M. Causal inference based on counterfactuals. BMC Medical Research Methodology 2005; 5: 28.