caa a22 4500 469029234 CHVBK 20180323132739.0 cr unu---uuuuu 170328e19921201xx s 000 0 eng 10.1007/BF00406959 doi (NATIONALLICENCE)springer-10.1007/BF00406959 Maul A. Département Statistique, Université de METZ, Ile du Saulcy, 57000, METZ, France aut Application of generalized linear models to the analysis of toxicity test data [Elektronische Daten] [A. Maul] Generalized linear models give a unified approach to the performance of regression analysis of dichotomous, count or continuous data. This paper studies binomial, negative binomial and gamma regression models and gives a detailed description of inference procedures based on them. In particular, the maximum likelihood procedure is described for a logistic function (binomial regression) or a log-linear regression model (negative binomial and gamma regression). The process of model fitting and evaluation is illustrated by examples referring to the determination of endpoints in acute and chronic toxicity tests. Kluwer Academic Publishers, 1992 Environmental Monitoring and Assessment Kluwer Academic Publishers 23/1-3(1992-12-01), 153-163 0167-6369 23:1-3<153 1992 23 10661 https://doi.org/10.1007/BF00406959 text/html Onlinezugriff via DOI 1 research-article jats NATIONALLICENCE 856 40 https://doi.org/10.1007/BF00406959 text/html Onlinezugriff via DOI NATIONALLICENCE 100 1- Maul A. Département Statistique, Université de METZ, Ile du Saulcy, 57000, METZ, France aut NATIONALLICENCE 773 0- Environmental Monitoring and Assessment Kluwer Academic Publishers 23/1-3(1992-12-01), 153-163 0167-6369 23:1-3<153 1992 23 10661 Metadata rights reserved Springer special CC-BY-NC licence nationallicence BK010053 XK010053 XK010000 NATIONALLICENCE NATIONALLICENCE NL-springer