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Prior distributions: The probability distributions which summarize the information about a random variable or parameter known or supposed at a given time instant, prior to attaining further information from the empirical data. It is used almost entirely within the context of Bayesian inference. In any specific study a variety of such kind of distributions might be assumed. For instance, reference priors represent the minimal prior information; clinical priors are used to formalize the opinion of well-informed specific individuals, frequently those taking part in the trial themselves. Lastly, sceptical priors are used when the large treatment differences are considered unlikely.
Treatment allocation ratio is the ratio of the number of subjects allocated to the two treatments in a clinical trial. The equal allocation is most usual in practice, but it might
A unified approach to all problems of prediction, estimation, and hypothesis testing. It is based on concept of the decision function, which tells the performer of experiment how t
Harris and Stevens forecasting is the method of making short term forecasts in the time series which is subject to abrupt changes in pattern and the transient effects. Instances o
Longini Koopman model : In epidemiology the model for primary and secondary infection, based on the classification of the extra-binomial variation in an infection rate which might
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
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Q1: The growth in bad debt expense for Aptara Pvt. Ltd. Company over the last 20 years is as follows. 1997 0.11 1998 0.09 1999 0.08 2000 0.08 2001 0.1 2002 0.11 2003 0.12 2004 0.1
Protopathic bias is the type of bias (also called as reverse-causality) that is a consequence of differential misclassification of the exposure related to timing of occurrence. It
The generalization of the normal distribution used for the characterization of functions. It is known as a Gaussian process because it has Gaussian distributed finite dimensional m
This is an alternative to the Newton-Raphson technique for optimization (finding out the minimum or the maximum) of some function, which includes replacing the matrix of second der
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