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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.
Cointegration : The vector of not motionless time sequence is said to be cointegrated if the linear combination of the individual series is stationary. Facilitates suitable testing
Median absolute deviation (MAD) : It is the very robust estimator of the scale given by the following equation or, in other words we can say that, the median of the absolute
Coefficient of concordance : The coef?cient is taken in use to assess the agreement among m raters ranking n individuals according to some of the speci?c characteristic. Which can
HOW TO OBTAIN THE LASPEYRES QUANTITY INDEX AND THE FORMULA
Orthogonal is a term which occurs in several regions of the statistics with different meanings in each case. Most commonly the encountered in the relation to two variables or t
Laplace distribution : The probability distribution, f(x), given by the following formula Can be derived as the distribution of the difference of two independent random var
meaning,uses,shortcomings and drawbacks of vital statistics
Suppose we estimate the following model: Passengersi = 1 + 2Populationi + ui a) Generate a scatter plot with passengers on the vertical axis and population on the horizonta
A value related with the square matrix which represents sums and products of its elements. For instance, if the matrix is then the determinant of A (conventionally written as
In the time series plot and scatter graphs there were many outliers that were clearly visible. These have been removed to identify if they were influential or had high leverage and
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