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Quality-adjusted survival analysis is a method for evaluating the effects of treatment on survival which allows the consideration of quality of life as well as the quantity of life. For instance, a highly toxic treatment with number of side effects might delay disease recurrence and increase the survival relative to a less toxic treatment. In this type of situation, the trade-off between negative quality-of-life impact and positive quantity-of-life impact of the more toxic therapy should be evaluated when determining which treatment is most probable to advantage a patient. The method precedes by defining the quality function which assigns a 'score' to the patient which is a composite measure of quality and quantity of life both. In common the quality function assigns a small value to the short life with poor quality and high value to the long life with good quality. The assigned scores are then taken in use to calculate quality- adjusted survival times for the analysis.
The problem that the studies are not uniformly probable to be published in the scientific journals. There is evidence that the statistical significance is a main determining factor
HOW TO CONSTRUCT A BIVARIATE FREQUENCY DISTRIBUTION
Lancaster models : The means of representing the joint distribution of the set of variables in terms of the marginal distributions, supposing all the interactions higher than a par
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The Null Hypothesis - H0: γ 1 = γ 2 = ... = 0 i.e. there is no heteroscedasticity in the model The Alternative Hypothesis - H1: at least one of the γ i 's are not equal
The Null Hypothesis - H0: There is no heteroscedasticity i.e. β 1 = 0 The Alternative Hypothesis - H1: There is heteroscedasticity i.e. β 1 0 Reject H0 if Q = ESS/2 >
Attitude scaling : The process of analysing the positions of the individuals on scales purporting to measure attitudes, for instance a liberal-conservative scale, ora risk-willingn
A radically different approach of dealing with the uncertainty than the traditional probabilistic and the statistical methods. The necessary feature of the fuzzy set is a membershi
Paired samples are the two samples of the observations with the characteristic feature with each of the observation in one sample have only one matching observation in the other s
This is the powerful visualization tool for studying how the response relies on an explanatory variable given the values of other explanatory variables. The plot comprises of a num
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