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Non parametric maximum likelihood (NPML) is a likelihood approach which does not need the specification of the full parametric family for the data. Usually, the non parametric maximum likelihood is a multinomial likelihood on a sample. Simple examples comprise the empirical cumulative distribution function and the product-limit estimator. It is also used to relax the parametric assumptions regarding random effects in the multilevel models. It is losely related to the empirical likelihood.
Ascertainment bias : A feasible form of bias, particularly in the retrospective studies, which arises from the relationship between the exposure to the risk factor and the probabil
Obuchowski and Rockette method is an alternative to the Dorfman-Berbaum-Metz technique for analyzing multiple reader receiver operating curve data. Instead of the modelling the ja
Computer-aided diagnosis : The computer programs which are designed to support clinical decision making. In common, such systems are based on the repeated application of the Bay
Bonferroni correction : A procedure for guarding against the rise in the probability of a type I error when performing the multiple signi?cance tests. To maintain probability of a
Information theory: This is the branch of applied probability theory applicable to various communication and signal processing problems in the field of engineering and biology. In
Mardia's multivariate normality test is a test that a set of the multivariate data arise from the multivariate normal distribution against departures due to the kurtosis. The test
Hypergeometric distribution is t he probability distribution related with the sampling without replacement from the population of finite size. If the population comprises of r ele
Multivariate analysis of variance is the procedure for testing equality of the mean vectors of more than two populations for the multivariate response variable. The method is dire
Completeness : A term applied to a statistic t when there is only one function of that the statistic which can have the given expected value. If, for instance, the one function of
Non linear model : A model which is non-linear in the parameters, for instance are Some such type of models can be converted into the linear models by linearization (the s
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