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Randomized response technique: The procedure for collecting the information on sensitive issues by means of the survey, in which an element of chance is introduced as to what query a respondent has to answer. In the survey about abortion, for instance, a woman may be posed both the questions 'have you had an abortion' and 'have you never had an abortion', and is asked to respond to one or the other depending on the outcome of a randomizing device in her control. The response is now not revealing since no one except the respondent knows which question has been answered. Yet the data attained can be used to estimate the quantities of interest, here, for instance, the proportion of women who have had an abortion (π); if the probability of selecting the question 'have you had an abortion', P, is known and is not equal to 0.5. If y is the proportion of 'yes' answers to this question in a random sample of n respondents, one estimator of π can be given by the following formula This estimator is unbiased and has the variance, V
An unusual aggregation of the health events, real or perceived. The events might be grouped in the particular region or in some short period of time, or they might happen among the
Classification matrix: A term many times used in discriminant analysis for the matrix summarizing the results and outputs obtained from the derived classi?cation rule, and obtaine
Cauchy distribution : The probability distribution, f (x), can be given as follows where α is the position of the parameter (median) and the beta β a scale parameter. Moments
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Missing values : The observations missing from the set of data for some of the reason. In longitudinal studies, for instance, they might occur because subjects drop out of the stud
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Invariant transformations to combine marginal probability functions to form multivariate distributions motivated by the need to enlarge the class of multivariate distributions beyo
Radical statistics group : The national network of the social scientists in United Kingdom committed to the critique of statistics as taken in use in the policy making procedure. T
Glim is the software package specifically suited for fitting the generalized linear models (the acronym stands for the Generalized Linear Interactive Modelling), including the log
Introduction to Generalized Linear Models (GLM) We introduce the notion of GLM as an extension of the traditional normal-theory-based linear regression models. This will be very
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