Epitope profiling via mixture modeling of ranked data

• Published in: Statistics in medicine Vol. 33; no. 21; pp. 3738 - 3758
• Main Authors: Mollica, Cristina, Tardella, Luca
• Format: Journal Article
• Language: English
• Published: England Blackwell Publishing Ltd 20.09.2014; Wiley Subscription Services, Inc
• Subjects: Algorithms; Bioassays; Cluster Analysis; Computer Simulation; Data Interpretation, Statistical; EM algorithm; epitope mapping; Estimating techniques; Humans; Likelihood Functions; Maximum likelihood method; Medical statistics; mixture models; Models, Statistical; multistage ranking models; Plackett-Luce model; Probability distribution; ranking data; mixture models; EM algorithm; Plackett-Luce model; epitope mapping; multistage ranking models; ranking data

We propose the use of probability models for ranked data as a useful alternative to a quantitative data analysis to investigate the outcome of bioassay experiments when the preliminary choice of an appropriate normalization method for the raw numerical responses is difficult or subject to criticism....