Probability weighting, Advanced Statistics

Probability weighting is the procedure of attaching weights equal to inverse of the probability of being selected, to each respondent's record in the sample survey. These weights are taken in use to compensate for the facts that sample elements might be selected at unequal sampling rates and have different probabilities of responding to the survey, and that some population elements might not be included in the list or frame used for sampling. 

Posted Date: 7/31/2012 3:17:37 AM | Location : United States







Related Discussions:- Probability weighting, Assignment Help, Ask Question on Probability weighting, Get Answer, Expert's Help, Probability weighting Discussions

Write discussion on Probability weighting
Your posts are moderated
Related Questions
Blinder Oaxaca method: A method or technique used for assessing the effect of the role of income on racial wealth gap. The method or technique is based on the decomposition of the

Probability weighting is the procedure of attaching weights equal to inverse of the probability of being selected, to each respondent's record in the sample survey. These weights

Hypergeometric distribution is t he probability distribution related with the sampling without replacement from the population of finite size. If the population comprises of r ele

Oracle property is a name given to techniques for estimating the regression parameters in the models fitted to high-dimensional data which have the property that they can correctl

Median is the value in a set of the ranked observations which divides the data into two parts of equal size. When there are an odd number of observations the median is middle v

Naor's distribution is the discrete probability distribution which arises from the following model; Assume an urn contains n balls of which one is red and the remainder is whit

Linked micro map plot is a plot which provides the graphical overview and the details for spatially indexed statistical summaries. The plot shows the spatial patterns and statisti

Cauchy integral : The integral of the function, f (x), from a to b are de?ned in terms of the sum   In the statistics this leads to the below shown inequality for the expecte

Poisson regression In case of Poisson regression we use ηi = g(µi) = log(µi) and a variance V ar(Yi) = φµi. The case φ = 1 corresponds to standard Poisson model. Poisson regre

Please help with following problem: : Let’s consider the logistic regression model, which we will refer to as Model 1, given by log(pi / [1-pi]) = 0.25 + 0.32*X1 + 0.70*X2 + 0.