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A term usually used for unobserved individual heterogeneity. Such variation is of main concern in the medical statistics particularly in the analysis of the survival times where hazard functions can be strongly influenced by the selection effects operating in the population. There are several possible sources of this heterogeneity, the most apparent of which is that it reflects the biological differences, so that, for instance, some individuals are born with the weaker heart, or a genetic disposition for cancer. A further prospect is that the heterogeneity happens from the occured weaknesses which result from the stresses of life. Failure to take account of this kind of variation might often obscure comparisons between groups, for instance, by measures of relative risk. A simple model which attempts to permit for the variation between individuals is given as follows where Z is the quantity specific to an individual, considered as the random variable over the population of individuals, and the base rate is denoted by λ(t) . What is observed in a population for which this type of model holds is not the individual hazard rate but the net result for several individuals with different values of Z.
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Graphical deception : Statistical graphics which are not as honest as they should be. It is relatively simple. To mislead the unwary with the graphical material. For instance, c
This term is sometimes used for the analysis of data from the clinical trial in which treatments A and B are to be compared under the suppositions that the patients remain on their
Likelihood is the probability of a set of observations provided the value of some parameter or the set of parameters. For instance, the likelihood of the random sample of n observ
Residual plots are the plots of some type of residual which might be helpful in assessing the assumption made by the fitted model. In regression analysis there are various method
Hazard plotting is based on the hazard function of a distribution, this procedure gives estimates of distribution parameters, the proportion of units failing by the given time per
methods of measuring trend
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regression line drawn as Y=C+1075x, when x was 2, and y was 239, given that y intercept was 11. calculate the residual
Reasons for screening data Garbage in-garbage out Missing data a. Amount of missing data is less crucial than the pattern of it. If randomly
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