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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.
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It is the art of attempting to exchange something quite small and certain, for something which are large and uncertain. Gambling is big business; in the US, for instance, it is at
what is operational gaining
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
Causality: The relating of the reasons to the effects they produce. Several investigations in medicine seek to establish the causal relations between the events, for instance, whi
Conditional logistic regression : The form of logistic regression designed to work with the clustered data, such as data including matched pairs of the subjects, in which subject-s
Literature controls : The patients with the disease of interest who have received, in the past, one of two treatments under the investigation, and for whom the results have been pu
what are tests for residual with nonconstant variance in regression diagnostic checking?
Regression line drawn as y= c+ 1075x ,when x was2, and y was 239,given that y intercept was 11. Calculate the residual ?
The graph for Partial Autocorrelation Function for RES1 shows that there is no autocorrelation even though there are alternating spikes because they fall inside the 5% significance
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