Wolfgang Wiedermann, Ph.D.
MPSI Methodology Branch Co-Director

Home Miz­zou Depart­ment: 
Edu­ca­tion­al, School & Coun­sel­ing Psychology

Email: wiedermannw@missouri.edu

Phone: 573–882-7732

13B Hill Hall, Colum­bia MO

Wolf­gang Wie­der­mann received his Ph.D. in Quan­ti­ta­tive Psy­chol­o­gy from the Uni­ver­si­ty of Kla­gen­furt, Aus­tria. Dr. Wiedermann’s research inter­ests include the devel­op­ment of meth­ods for causal infer­ence, meth­ods to eval­u­ate the direc­tion of depen­dence in sta­tis­ti­cal mod­els, and meth­ods for per­son-ori­ent­ed research. Cur­rent­ly, he serves as a lead method­ol­o­gist for three IES-fund­ed MPSI projects (R305A200297, PI: Reinke; R305C190014, PI: Reinke, and R305A150517, PI: Thomp­son). He has served as the PI on a grant that focused on the devel­op­ment and imple­men­ta­tion of Direc­tion Depen­dence Analy­sis (DDA) in the edu­ca­tion­al sci­ences, and has served as the method­ol­o­gist in var­i­ous fund­ed projects in the edu­ca­tion­al, health, and psy­cho­log­i­cal sci­ences. Dr. Wie­der­mann has (co-)edited 3 vol­umes on advances in 1) sta­tis­ti­cal meth­ods for causal infer­ence, 2) sta­tis­ti­cal mod­el­ing of the direc­tion of depen­dence (both pub­lished by Wiley in 2016 and 2020), and 3) sta­tis­ti­cal meth­ods for depen­dent data analy­sis in the social and behav­ioral sci­ences (pub­lished by Springer, 2015). He has edit­ed 4 spe­cial issues on meth­ods for causal infer­ence, meth­ods for cat­e­gor­i­cal data, and meth­ods for per­son-ori­ent­ed research (pub­lished in Pre­ven­tion Sci­ence and the Jour­nal for Per­son-Ori­ent­ed Research). In addi­tion, Dr. Wie­der­mann has authored/­co-authored 49 peer-reviewed papers/book chap­ters that focus on the the­o­ry of sta­tis­ti­cal meth­ods and 30 peer-reviewed papers/book chap­ters that focus on the appli­ca­tion of sta­tis­ti­cal meth­ods in exper­i­men­tal and non-exper­i­men­tal data set­tings. Togeth­er with grad­u­ate stu­dents, he has pub­lished 5 soft­ware pack­ages in R and SPSS.


  • Quan­ti­ta­tive Methods