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Hazard function: The risk which an individual experiences an event in a small time interval, given that the individual has survived up to the starting of the interval.
It is the measure of how likely an individual is to experience the event as a function of time.
Generally denoted h(t), the function can be given in terms of the probability distribution of the survival times f (t) and the survival function S(t), as h(t)= f (t)/S(t). The hazard function might remain constant, increase, decrease or take on some much more complex shape. The function can be expected as the proportion of the individuals experiencing an event in the interval per unit time, provided that they have survived to the beginning of the interval, Care is required in the interpretation of the hazard function because of both the selection effects due to dissimilarity between the individuals and variation within each individual over time. For instance, individuals with a high risk are more prone to experience an event soon, and those remaining at risk will tend to be the selected group with a lower risk. This will result in hazard rate being 'pulled down' to an increasing extent as the time passes.
The diagnostic tools or devices used to approach the closeness to the linearity of the non-linear model. They calculate the deviation of so-called expectation surface from the plan
Informed consent: The consent needed from each potential participant former to random assignment in the clinical trial as speci?ed in the year 1996 version of Helsinki declaration
Recurrence risk : Usually the probability that an individual experiences an event of interest given previous experience(s) of the event; for example, the probability of recurrence
Collapsing categories : A procedure generally applied to contingency tables in which the two or more row or column categories are combined, in number of cases so as to yield the re
we are testing : Ho: µ=40 versus Ha: µ>40 (a= 0.01) Suppose that the test statistic is z0=2.75 based on a sample size of n=25. Assume that data are normal with mean mu and standa
1.Sam Lucarelli, owner of Lucarelli Products, is evaluating whether to produce a new product line. After thinking through the production process and the costs of raw materials and
You may have the opportunity to buy some electronic components. These components may be reliable (1) or unreliable (2). The potential pro?ts are £10,000 if the components are rel
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 |t | > t = 1.96
The method of summarizing the large amounts of data by forming the frequency distributions, scatter diagrams, histograms, etc., and calculating statistics like means variances and
Gllamm is a program which estimates the generalized linear latent and mixed models by the maximum likelihood. The models which can be fitted include structural equation models mul
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