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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.
A subject who withdraws from the study for whatever reason, adverse side effects, noncompliance, moving away from the district, etc. In number of cases the reason may not be known.
The estimator of the group by the time period interaction in a study in which the subjects in two different groups are observed in two different time periods. Normally one of th
This is acronym for the Epidemiological, Graphics, Estimation and Testing of the program developed for the analysis of the data from studies in epidemiology. It can be made in use
Lattice distribution : A class of probability distributions to which most of the distributions for discrete random variables used in statistics belongs. In such type of distributio
The theorem relating structure of the likelihood to the concept of the sufficient statistic. Officially the necessary and sufficient condition which a statistic S be sufficient for
Canonical correlation analysis : A process of analysis for investigating the relationship between the two groups of variables, by ?nding the linear functions of one of the sets of
A term commonly encountered in the analysis of the contingency tables. Such type of frequencies are the estimates of the values to be expected under hypothesis of interest. In a tw
The term used in a variety of methods in statistics, but mostly to refer to the categorical variable, with a less number of levels, under examination in an experiment as a possible
Nested design is the design in which levels of one or more factors are subsampled within one or more other factors such that, for instance, each level of a factor B happens at onl
Mean squarederror is the expected value of square of the difference between an estimator and the true value of the parameter. If the estimator is unbiased then the mean of the squ
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