**[ME] estat recovariance** -- Display estimated random-effects covariance
matrices

__Syntax__

**estat** __recov__**ariance** [**,** __relev__**el(***levelvar***)** __corr__**elation** *matlist_options*]

__Menu for estat__

**Statistics > Postestimation**

__Description__

**estat recovariance** is for use after estimation with **menl**, **mixed**,
**meqrlogit**, and **meqrpoisson**.

**estat recovariance** displays the estimated variance-covariance matrix of
the random effects for each level in the model.

__Options__

**relevel(***levelvar***)** specifies the level in the model for which the
random-effects covariance matrix is to be displayed. By default, the
covariance matrices for all levels in the model are displayed.
*levelvar* is the name of the model level and is either the name of the
variable describing the grouping at that level or is **_all**, a special
designation for a group comprising all the estimation data. The **_all**
designation is not supported with **menl**.

**correlation** displays the covariance matrix as a correlation matrix.

*matlist_options* are style and formatting options that control how the
matrix (or matrices) is displayed; see **[P] matlist** for a list of
options that are available.

__Example__

Setup
**. webuse pig**
**. mixed weight week || id: week, covariance(unstructured)**

Random-effects correlation matrix for level ID
**. estat recovariance, correlation**

__Stored results__

**estat recovariance** stores the following in **r()**:

Scalars
**r(relevels)** number of levels

Matrices
**r(Cov***#***)** level-*#* random-effects covariance matrix
**r(Corr***#***)** level-*#* random-effects correlation matrix (if option
**correlation** was specified)

For a G-level nested model, *#* can be any integer between 2 and G.