title: Fitting limiting dilution experiments with generalized linear models results in a test of the single-hit Poisson assumption.
abstract: Limiting dilution analysis is a common technique that is used in immunology to estimate accurately the frequency of cells possessing a wide variety of functional activities such as growth, cytotoxicity and production of lymphokines. The reliability of the estimated frequency is usually checked by a standard chi-square (x2) test validating the goodness-of-fit to the single-hit Poisson model (SHPM). We present evidence that modelling limiting dilution data according to a generalized linear model offers an alternative to the standard x2 test for detecting departures from the SHPM, with a considerable increase in power compared to the x2 test.
authors.affiliation: ID9 SOFT, Grenoble, France.
authors.forename: T
authors.initials: T
authors.lastname: Bonnefoix
authors.forename: P
authors.initials: P
authors.lastname: Bonnefoix
authors.forename: P
authors.initials: P
authors.lastname: Verdiel
authors.forename: J J
authors.initials: JJ
authors.lastname: Sotto
mesh_terms: D007158:Immunologic Techniques; D007201:Indicator Dilution Techniques; D016014:Linear Models; D008432:Mathematical Computing; D015233:Models, Statistical; D016012:Poisson Distribution; D015203:Reproducibility of Results