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Log-linear models is the models for count data in which the logarithm of expected value of a count variable is modelled as the linear function of parameters; the latter represent associations between the pairs of variables and higher order interactions among more than two variables.
The estimated expected frequencies under the particular models can be found from the iterative proportional fitting. Such type of models is, essentially, the equivalent for the frequency data, of the models for the continuous data used in the analysis of variance, except that interest usually now centres on parameters representing interactions rather than those for the main effects.
Bivariate survival data : The data in which the two related survival times are of interest. For instance, in familial studies of disease incidence, data might be available on the a
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
It is the survey which is carried out in Great Britain on a continuous basis since 1971. About 100 000 households are included in this sample every year. The main goal of the surve
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Generally the final stage of an exploratory factor analysis in which factors derived initially are transformed to build their interpretation simpler. Generally the target of the pr
Minimization is the method or technique for allocating patients to the treatments in clinical trials which is usually the acceptable alternative to random allocation. The procedur
1) Let N1(t) and N2(t) be independent Poisson processes with rates, ?1 and ?2, respectively. Let N (t) = N1(t) + N2(t). a) What is the distribution of the time till the next epoch
Bioinformatics : Essentially the application of the information theory to biology to deal with the deluge of the information resulting from the advances in molecular biology. The m
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Matching coefficient is a similarity coefficient for data consisting of the number of binary variables which is often used in cluster analysis. It can be given as follows he
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