Describe multiple imputation, Advanced Statistics

Multiple imputation: The Monte Carlo technique in which missing values in the data set are replaced by m> 1 simulated versions, where m is usually small (say 3-10). Each of simulated complete datasets is analyzed by the technique appropriate to the investigation at hand, and results are later combined to generate estimates, confidence intervals etc. The imputations are created by the Bayesian approach which needs specification of the parametric model for the complete data and, if necessary, a model for mechanism by which data become missing.

Hear also required is a prior distribution for unknown model parameters. Bayes' theorem is taken in use to simulate m independent samples from the conditional distribution of the missing values provided the observed values. In most of the cases special computation techniques such as Markov chain Monte Carlo methods will be required.

Posted Date: 7/30/2012 5:51:17 AM | Location : United States







Related Discussions:- Describe multiple imputation, Assignment Help, Ask Question on Describe multiple imputation, Get Answer, Expert's Help, Describe multiple imputation Discussions

Write discussion on Describe multiple imputation
Your posts are moderated
Related Questions
Occam's razor  is an early statement of the parsimony principle, which was given by William of Occam (1280-1349) namely 'entia non sunt multiplicanda praeter necessitatem'; which m

The graphical method for studying the behavior of the seasonal time series. In such a plot, the January values of seasonal component are graphed for the upcoming years, then the

Cellular proliferation models : Models are used to describe the growth of the  cell populations. One of the example is the deterministic model   where N(t) is the number of cel

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

Generalized principal components analysis: The non-linear version of the principal components analysis in which the goal is to determine the non-linear coordinate system which is

Bayesian inference : An approach to the inference based largely on Bayes' Theorem and comprising of the below stated principal steps: (1) Obtain the likelihood, f x q describing

A term which covers the large number of techniques for the analysis of the multivariate data which have in common the aim to assess whether or not the set of variables distinguish

Quittingill effect is a  problem which occurs most frequently in studies of the smoker cessation where smokers frequently quit smoking following the onset of the disease symptoms

The graphic representation of the alternatives in a decision making problem which summarizes all the possibilities foreseen by the decision maker. For instance, suppose we are give

Pattern recognition is a term for a technology that recognizes and analyses patterns automatically by machine and which has been used successfully in many areas of application inc