title: Maximum likelihood.
abstract: The maximum likelihood method is a popular statistical inferential procedure widely used in many areas to obtain the estimates of the unknown parameters of a population of interest. This chapter gives a brief description of the important concepts underlying the maximum likelihood method, the definition of the key components, the basic theory of the method, and the properties of the resulting estimates. Confidence interval and likelihood ratio test are also introduced. Finally, a few examples of applications are given to illustrate how to derive maximum likelihood estimates in practice. A list of references to relevant papers and software for a further understanding of the method and its implementation is provided.
authors.affiliation: GlaxoSmithKline Services Unlimited, Brentford, Middlesex, UK. shuying.y.yang@gsk.com
authors.forename: Shuying
authors.initials: S
authors.lastname: Yang
authors.forename: Daniela
authors.initials: D
authors.lastname: De Angelis
mesh_terms: D000818:Animals; D016001:Confidence Intervals; D004305:Dose-Response Relationship, Drug; D006801:Humans; D016013:Likelihood Functions; D016014:Linear Models; D008252:Macaca fascicularis; D008954:Models, Biological; D012867:Skin / Q000473:pathology; D012984:Software; D018675:Toxicity Tests