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Regression dilution is the term which is applied when a covariate in the model cannot be measured directly and instead of that a related observed value must be used in analysis. In common, if the model is correctly specified in the terms of the 'true' covariate, then an equivalent form of the model with a easy error structure will not hold for observed values. In such type of cases, ignoring the measured values will lead to the biased estimates of the parameters in the model. It is often also referred to as the errors in variables problem.
Opreation research phase
This term is sometimes used for the data collected in those longitudinal studies in which more than the single response variable is recorded for each subject on each occasion. For
Lorenz curve : Essentially the graphical representation of cumulative distribution of the variable, most often used for the income. If the risks of disease are not monotonically in
Cluster sampling : A method or technique of sampling in which the members of the population are arranged in groups (called as 'clusters'). A number of clusters are selected at the
Cochrane collaboration : An international network of the individuals committed to preparing , maintaining and disseminating the systematic reviews of the effects of the health care
Probabilistic matching is a method developed to maximize the accuracy of the linkage decisions based on the level of agreement and disagreement among the identifiers on different
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
Multiple correlation coefficient is the correlation among the observed values of dependent variable in the multiple regression, and the values predicted by estimated regression
The functions of the data and the parameters of interest which can be brought in use to conduct inference about the parameters when full distribution of the observations is unknown
Unequal probability sampling is the sampling design in which the different sampling units in the population have different probabilities of being included in sample. The differing
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