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Probit analysis is the technique most commonly employed in the bioassay, specifically toxicological experiments where the group of animals is subjected to known levels of a toxin and a model is needed to relate the proportion surviving at the particular dose, to the dose. In this kind of evaluation the probit transformation of a proportion is modeled as a linear function of the dose or more frequently, the logarithm of the dose. Estimates of the parameters in the model are found by the maximum likelihood estimation.
Lexis diagram is the diagram for displaying the simultaneous effects of the two time scales (generally age and calendar time) on a rate. For instance, mortality rates from cancer
Classification and regression tree technique (CART): The alternative to the multiple regression and associated techniques or methods for determining subsets of the explanatory va
Naor's distribution is the discrete probability distribution which arises from the following model; Assume an urn contains n balls of which one is red and the remainder is whit
Collector's problem : A problem which derives from the schemes in which packets of a particular brand of coffe, cereal etc., are sold with coupons, cards, or other tokens. There ar
Continual reassessment method: An approach which applies Bayesian inference for determining the maximum tolerated dose in a phase I trial. The method starts by assuming a logistic
An approach to decrease the size of very large data sets in which the data are first 'binned' and then statistics such as the mean and variance/covariance are calculated on each bi
Probabilistic matching is a method developed to maximize the accuracy of the linkage decisions based on the level of agreement and disagreement among the identifiers on different
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
This is an approach to the modelling of time-frequency surfaces which consists of a Bayesian regularization scheme in which the prior distributions over the time-frequency coeffici
The Null Hypothesis - H0: β 1 = 0 i.e. there is homoscedasticity errors and no heteroscedasticity exists The Alternative Hypothesis - H1: β 1 ≠ 0 i.e. there is no homoscedasti
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