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Non linear model: A model which is non-linear in the parameters, for instance are Some such type of models can be converted into the linear models by linearization (the second equation above, for instance, by taking logarithms throughout). Those which cannot are often referred to as the intrinsically non-linear, though these can often be approximated by the linear equations in some circumstances. Parameters in such type of models usually have to be estimated using an optimization procedure like the Newton-Raphson technique. In such models linear parameters are those for which second partial derivative of the model function with respect to parameter is zero (β1 and β3 in the first example given above); when this is not case (β2 and β4 in the ?rst example above) they are called as non-linear parameters.
Human capital model : The model for evaluating the economic implication of the disease in terms of the economic loss of a person succumbing to morbidity or the mortality at some pa
Intention-to-treat analysis is the process in which all the patients randomly allocated to a treatment in the clinical trial are analyzed together as representing that particular
Atomistic fallacy : A fallacy which arises because of the association between two variables at the individual level might vary from the association between the same two variables m
MAREG is the software package for the analysis of the marginal regression models. The package permits the application of generalized estimating equations and the maximum likelihoo
Protocol is the formal document outlining the proposed process for carrying out the clinical trial. The basic features of the document are to study the objectives, patient selecti
The number of employees absent from work at a large electronics manufacturing plant over aperiod of 106 days is given in the table below. 146 141 139 140 145 141 142 131 142 140
Johnson-Neyman technique: The technique which can be used in the situations where analysis of the covariance is not valid because of the heterogeneity of slopes. With this method
Pattern recognition is a term for a technology that recognizes and analyses patterns automatically by machine and which has been used successfully in many areas of application inc
A term which covers the large number of techniques for the analysis of the multivariate data which have in common the aim to assess whether or not the set of variables distinguish
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
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