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In practical dose response trials\, especially in a cell cultu
re context\, experimental designs to establish functional relationships be
tween dose and effect of a substance are generally chosen based on simple
rules of thumb. These designs are generally reasonably effective\, but not
optimal.
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\nIn this webinar we give an overview over the stat
istical optimal design approach in this context. We show how optimal desig
ns can be constructed\, covering mainly all-purpose designs (D-optimality)
but also more specific designs (c-optimality). We introduce a graphical r
epresentation. Next\, we show how these concepts can be extended to trials
aiming to estimate the interaction between two different substances given
simultaneously.
\n
\nFinally\, we present an R-Shiny applicatio
n which allows construction of optimal designs in most of these contexts w
ith a minimum of theoretical knowledge. \;
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Speaker \n | \n Biography \n |
\n Tim Holland-Letz \n | \n
Tim Holland-Letz studied Statistics at the Technical University of Dortmund. In 2010\, he completed his PhD in the same subject in cooper ation with the Department of Mathematics of the Ruhr-University Bochum\, f ocusing on the topic of optimal experimental design. At the same time he w as employed at the Department of Medical Informatics and Biometry also at the Ruhr-University\, working mainly on clinical studies and general appli ed statistics in medical research. In 2011\, he moved to the Biostatistics Division within the Deutsches Krebsforschungszentrum (DKFZ) in Heidelberg . From this moment on\, he has concentrated more on preclinical studies\, with a special focus on optimal experimental designs and dose-response ana lysis. However\, he still works on more or less all kinds of statistical p roblems arising in research and preclinical studies. In 2019 he completed his Habilitation in Medical Biostatistics at the University of Heidelberg. \n |
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