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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.
L'Abbe ´ plot is often used in the meta-analysis of the clinical trials where the result is the binary response of it. The event risk (number of events/number of the patients in a
Time series : The values of a variable recorded, generally at a regular interval, over the long period of time. The observed movement and fluctuations of several such series are
Bayesian inference : An approach to the inference based largely on Bayes' Theorem and comprising of the below stated principal steps: (1) Obtain the likelihood, f x q describing
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
Per-experiment error rate is the possibility of the incorrectly rejecting at least one null hypothesis or assumption in the experiment including one or more tests or comparisons,
Discuss the use of dummy variables in both multiple linear regression and non-linear regression. Give examples if possible
Case series : It is the series of reports on the condition of the individual patients made by treating physician. Such reports might be helpful and informative for the rare disease
the problem that demonstrates inference from two dependent samples uses hypothetical data from TB vaccinations and the number of new cases before and after vaccinations for cases o
Chapter 7 2. Describe the distribution of sample means (shape, expected value, and standard error) for samples of n =36 selected from a population with a mean of µ = 100 and a sta
Conditional probability : The probability that an event occurs given the outcome of other event. Generally written, Pr(A|B). For instance, the probability of a person being color b
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