Generalized estimating equations (gee), Advanced Statistics

Technically the multivariate analogue of the quasi-likelihood with the same feature that it leads to consistent inferences about the mean responses without needing specific suppositions to be made about second and higher order moments. Most frequently used for the likelihood-based inference on longitudinal data where the response variable cannot be supposed to be normally distributed. Easy models are used for within-subject correlation and a working correlation matrix is introduced into the model specification to accommodate these correlations. The process gives consistent estimates for the mean parameters even if the covariance structure is incorrectly specified.

The technique assumes that the missing data are missing completely at the random; otherwise the resulting parameter estimates are biased. The amended approach, weighted generalized estimating equations, is available which produces the unbiased parameter estimates under the less stringent assumption that the missing data are missing at random.

Posted Date: 7/28/2012 3:54:33 AM | Location : United States







Related Discussions:- Generalized estimating equations (gee), Assignment Help, Ask Question on Generalized estimating equations (gee), Get Answer, Expert's Help, Generalized estimating equations (gee) Discussions

Write discussion on Generalized estimating equations (gee)
Your posts are moderated
Related Questions
Q1: The growth in bad debt expense for Aptara Pvt. Ltd. Company over the last 20 years is as follows. 1997 0.11 1998 0.09 1999 0.08 2000 0.08 2001 0.1 2002 0.11 2003 0.12 2004 0.1

Monty Hall problem : A apparently counter-intuitive problem in the probability which gets its name from the TV game show, 'Let's Make a Deal' hosted by the Monty Hall. On show a pa

Difference between tretment design and experimental design

The graphical process most frequently used in the analysis of data from a two-by-two crossover design. For each of the subject the difference between the response variable values o

The diagnostic tools or devices used to approach the closeness to the linearity of the non-linear model. They calculate the deviation of so-called expectation surface from the plan

Least significant difference test is an approach to comparing a set of means which controls the family wise error rate at some specific level, let's assume it to be α. The hypothe

The Null Hypothesis - H0:  There is no heteroscedasticity i.e. β 1 = 0 The Alternative Hypothesis - H1:  There is heteroscedasticity i.e. β 1 0 Reject H0 if Q = ESS/2 >

Bayesian confidence interval : An interval of the posterior distribution which is so that the density of it at any point inside the interval is greater than that of the density at

Records on the computer manufacturing process at Pratt-Zungia Limited show that the percentage of defective computers sent to  customers has been 5% over the last few years. Shipme

Computer-assisted interviews : A method or technique of interviewing subjects in which the interviewer reads the question from the computer screen instead of the printed page, and