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Respondent-driven sampling (RDS): The form of snowball sampling which starts with the recruitment of the small number of people in the target population to serve as the seeds. After participating the seeds are asked to recruit other people they know in target population. The sampling continues in this manner with the current sample members recruiting the next wave of the sample members until the desired sample size is achived. By using the mathematical model which weights the sample to compensate for the fact that the sample was collected in a non-random manner, the data provided by such a sampling scheme can be used to give asymptotically unbiased estimates about target population. An instance of the use of this approach is the estimation of the drug user's in New York who have HIV.
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Prognostic scoring system is a technique of combining the prognostic information contained in the number of threat factors, in a manner which best predicts each patient's risk of
Computer-aided diagnosis : The computer programs which are designed to support clinical decision making. In common, such systems are based on the repeated application of the Bay
Multi dimensional unfolding is the form of multidimensional scaling applicable to both the rectangular proximity matrices where the rows and columns refer to the different sets of
The marketing manager of Handy Foods Ltd. is concerned with the sales appeal of one of the company's present label for one of its products. Market research indicates that supermark
Point scoring is an easy distribution free method which can be used for the prediction of a response which is a binary variable from the observations on several explanatory variab
The Null Hypothesis - H0: β 1 = 0 i.e. there is homoscedasticity errors and no heteroscedasticity exists The Alternative Hypothesis - H1: β 1 ≠ 0 i.e. there is no homoscedasti
Back-projection: A term most often applied to the procedure for reconstructing plausible HIV incidence curves from the AIDS incidence data. The method or technique assumes that th
Nearest-neighbour methods are the methods of discriminant analysis are based on studying the training set subjects much similar to the subject to be classified. Classification mig
how to resolve sequencing problem if jobs 6 given and 4 machines given. how to apply johnson rule for making to machines under this conditions. please give solution as soon as poss
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