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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.
Incidental parameter problem is a problem which sometimes occurs when the number of parameters increases in the tandem with the number of observations. For instance, models for pa
Individual differences scaling is a form of multidimensional scaling applicable to the data comprising of a number of proximity matrices from the different sources that is differe
Ask quesoil company is considering whether or not to bid for an offshore drilling contract. If they bid, the value would be $600m with a 65% chance of gaining the contract. The com
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
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
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Hill-climbing algorithm is an algorithm which is made in use in those techniques of cluster analysis which seek to find the partition of n individuals into g clusters by optimizin
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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
The non-trivial extraction of implicit, earlier unknown and potentially useful information from data, specifically high-dimensional data, using pattern recognition, artificial inte
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