# estfun: Extract Empirical Estimating Functions In lavaan: Latent Variable Analysis

 estfun R Documentation

## Extract Empirical Estimating Functions

### Description

A function for extracting the empirical estimating functions of a fitted lavaan model. This is the derivative of the objective function with respect to the parameter vector, evaluated at the observed (case-wise) data. In other words, this function returns the case-wise scores, evaluated at the fitted model parameters.

### Usage

```estfun.lavaan(object, scaling = FALSE, ignore.constraints = FALSE,
remove.duplicated = TRUE, remove.empty.cases = TRUE)
lavScores(object, scaling = FALSE, ignore.constraints = FALSE,
remove.duplicated = TRUE, remove.empty.cases = TRUE)
```

### Arguments

 `object` An object of class `lavaan`. `scaling` If `TRUE`, the scores are scaled to reflect the specific objective function used by lavaan. If `FALSE` (the default), the objective function is the loglikelihood function assuming multivariate normality. `ignore.constraints` Logical. If `TRUE`, the scores do not reflect the (equality or inequality) constraints. If `FALSE`, the scores are computed by taking the unconstrained scores, and adding the term `t(R) lambda`, where `lambda` are the (case-wise) Lagrange Multipliers, and `R` is the Jacobian of the constraint function. Only in the latter case will the sum of the columns be (almost) equal to zero. `remove.duplicated` If `TRUE`, and all the equality constraints have a simple form (eg. a == b), the unconstrained scores are post-multiplied with a transformation matrix in order to remove the duplicated parameters. `remove.empty.cases` If `TRUE`, empty cases with only missing values will be removed from the output.

### Value

A n x k matrix corresponding to n observations and k parameters.

### Author(s)

Ed Merkle; the `remove.duplicated`, `ignore.constraints` and `remove.empty.cases` arguments were added by Yves Rosseel

lavaan documentation built on Jan. 9, 2023, 9:05 a.m.