Abstract
The checking and assessment of generalized linear models is a largely neglected area of many statistical investigations. Statistical packages have been developed to facilitate the routine fitting of generalized linear models but most provide few facilities to enable the assessment of the adequacy of these models. Both the informal and formal techniques of model checking can be of equal importance and utility in this respect. Six types of assessment are needed to decide on the suitability of a particular model specification: assessment of the scale of independent variables; assessment of link function adequacy; assessment of variance function adequacy; investigation of systematic departure from assumed model; outlier investigation and investigation of omitted predictor variables. Techniques are discussed, together with details of their routine implementation within a knowledge-based front-end system GLIMPSE. Wherever possible, graphical displays are used; complemented by formal test statistics as appropriate.
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O’Brien, C.M. (1991). Glimpse: An Assessor of GLM Misspecification. In: Directions in Robust Statistics and Diagnostics. The IMA Volumes in Mathematics and its Applications, vol 34. Springer, New York, NY. https://doi.org/10.1007/978-1-4612-4444-8_7
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DOI: https://doi.org/10.1007/978-1-4612-4444-8_7
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