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Indirect standardization is the procedure of adjusting the crude mortality or morbidity rate for one or more variables by making use of a known reference population. It may, for instance, be needed to compare cancer mortality rates of single and married women with the adjustment being made for the likely different age distributions in two groups. Age-specific mortality rates in the reference population are applied individually to the age distributions of the two groups to obtain the probable number of deaths in each. These can then be summed with the observed number of deaths in the two groups to obtain comparable mortality rates.
Genetic algorithms: The optimization events motivated by the biological analogies. The prime idea is to try to mimic the 'survival of the fittest' rule of the genetic mutation in
Link functions: The link function relates the linear predictor ηi to the expected value of the data. In classical linear models the mean and the linear predictor are identical
Nuisance parameter : The parameter of the model in which there is no scienti?c interest but whose values are generally required (but in usual are unknown) to make inferences about
Designs in which the information on main effects and low-order inter- actions are attained by running only the fraction of the complete factorial experiment and supposing that part
Bayes factor : A summary of evidence for the modelM1 against the another modelM0 provided by the set of data D, which can be used in the model selection. Given by the ratio of post
Technically the multivariate analogue of the quasi-likelihood with the same feature that it leads to consistent inferences about the mean responses without needing specific supposi
Categorizing continuous variables : A practice which involves the conversion of the continuous variables into the series of the categories, which is common in the field of medical
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
Imprecise probabilities is a n approach used by soft techniques in which uncertainty is represented by the closed, convex sets of probability distributions and the probability of
Quantalassay: The experiment in which the groups of subjects are exposed to the different doses of, generally, a drug, to which the particular number respond. Data from such type
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