cov_nest

cor_nest

Compute covariance or correlation matrix with treatments for clusters and missing values

Determine the number of dimensions to retain in exploratory factor analysis. The main function, nest(), returns the solution and the plot(nest()) returns a plot.

P.-O. Caron

Rnest

Next Eigenvalue Sufficiency Test

cov_nest function

<dl><dt>.data</dt>
<dd>a data frame, a numeric matrix.</dd>
<dt>...</dt>
<dd>further arguments.</dd>
<dt>cluster</dt>
<dd>a variable name defining the clusters in a two-level dataset in the data frame.</dd>
<dt>missing</dt>
<dd>treatment to deal with missing values. Options are <code>"listwise"</code> or <code>"pairwise"</code>. Default if <code>"fiml"</code>.</dd>
<dt>ordered</dt>
<dd>a character vector identifying which variables have an ordered (ordinal) scale. If <code>TRUE</code>, all observed endogenous variables are treated as ordered (ordinal). If <code>FALSE</code>, all observed endogenous variables are considered to be numeric</dd>
<dt>pvalue</dt>
<dd>an argument to indicate if \(p\)-values are required.</dd></dl>

Arguments

Compute covariance or correlation matrix with treatments for clusters and missing values — cov_nest

<dl>

<dt>.data</dt>
<dd>a data frame, a numeric matrix.</dd>


<dt>...</dt>
<dd>further arguments.</dd>


<dt>cluster</dt>
<dd>a variable name defining the clusters in a two-level dataset in the data frame.</dd>


<dt>missing</dt>
<dd>treatment to deal with missing values. Options are <code>"listwise"</code> or <code>"pairwise"</code>. Default if <code>"fiml"</code>.</dd>


<dt>ordered</dt>
<dd>a character vector identifying which variables have an ordered (ordinal) scale. If <code>TRUE</code>, all observed endogenous variables are treated as ordered (ordinal). If <code>FALSE</code>, all observed endogenous variables are considered to be numeric</dd>


<dt>pvalue</dt>
<dd>an argument to indicate if \(p\)-values are required.</dd>

</dl>

cov_nest: Compute covariance or correlation matrix with treatments for clusters and missing values

Description

Usage

Value

Arguments

Details

References

Examples