School of Mathematical Sciences

Multi-stratum designs with categorical responses menu

Multi-stratum designs with categorical responses

Mohammad Lutfor RahmanSchool of Mathematical Sciences, Queen Mary, University of London
Thu, 25/11/2010 - 16:30
Seminar series: 

It is not possible to completely randomize the order of runs in some multi-factor factorial experiments.
This often results in a generalization of the factorial designs called split-plot designs. Sometimes in
industrial experiments complete randomization is not feasible because of having some factors whose
levels are difficult to change. When properly taken into account at the design stage, hard-to-change
factors lead naturally to multi-stratum structures. Mixed models are used to analyze multi-stratum
designs as each stratum may have random effects on the responses. We intend to design
experiments and analyze categorical data with hard-to-set factors with the motivation of random
effects structure in the mixed models. The current study is motivated by a polypropylene experiment
by four Belgian companies where responses are continuous and categorical. We have analyzed the
data from the current experiment using mixed binary logit and mixed cumulative logit models in a
Bayesian approach. Also we obtained outputs following the simplified models by Goos and Gilmour
(2010). While simplified models were used, the output obtained by Bayesian methods were similar to
those obtained by likelihood methods as non-informative priors were considered for the fixed effects.