What is Xtgee?
Description. xtgee fits population-averaged panel-data models. In particular, xtgee fits generalized linear models and allows you to specify the within-group correlation structure for the panels. Quick start. Population-averaged linear regression of y on x1 and x2.
What is the GEE method?
Generalized Estimating Equations, or GEE, is a method for modeling longitudinal or clustered data. It is usually used with non-normal data such as binary or count data. The name refers to a set of equations that are solved to obtain parameter estimates (ie, model coefficients).
What is the link function in GEE?
GEEs start with maximum-likelihood estimation of our regression parameters (β) and the variance calculated using a link function, which is a transformation function that allows the dependent variable to be expressed as a vector of parameter estimates (y = β0 + β1X1 + β2X2 + β3X3 . . .) in the form of an additive model.
Is GEE Parametric?
GEE approach is an extension of GLMs. It provides a semi-parametric approach to longitudinal analysis of categorical response; it can be also used for continuous measurements.
When should we use GEE and when should we use GLMM?
I guess one really has to decide FIRST, if a marginal or a conditional model correctly answers the research question. If it is a conditional model, one should use a GLMM. If it is a marginal model, one can either use a GEE directly, or integrate the result from the GLMM (which I think is the way to go).
Can GEE handle unbalanced?
Both GEE and CS can handle unbalanced data. GEE works well if you have data missing and it is missing completely at random (MCAR). Under this assumption the GEE approach provides consistent estimators of the regression coefficients and of their robust variances even if the assumed working correlation is misspecified.
Is GEE a regression?
GEEs belong to a class of regression techniques that are referred to as semiparametric because they rely on specification of only the first two moments. They are a popular alternative to the likelihood–based generalized linear mixed model which is more sensitive to variance structure specification.
Why do we need link functions?
A link function transforms the probabilities of the levels of a categorical response variable to a continuous scale that is unbounded. Once the transformation is complete, the relationship between the predictors and the response can be modeled with linear regression.
What is canonical link function?
A. canonical link function is one in which transforms the mean, µ = E(yi), to the natural exponential (location) parameter for the exponential family of distributions (e.g., normal, binomial, Poisson, gamma). The canonical link function is the most commonly used link form in generalized linear models.
What does the Hausman test do?
The Hausman Test (also called the Hausman specification test) detects endogenous regressors (predictor variables) in a regression model. Endogenous variables have values that are determined by other variables in the system. This is what the Hausman test will do.
What is panel data in statistics?
In statistics and econometrics, panel data and longitudinal data are both multi-dimensional data involving measurements over time. Panel data is a subset of longitudinal data where observations are for the same subjects each time. A study that uses panel data is called a longitudinal study or panel study.