# popMisfitMACS: Find population misfit by sufficient statistics In simsem: SIMulated Structural Equation Modeling

## Description

Find the value quantifying the amount of population misfit: F_0, RMSEA, and SRMR. See the definition of each index at `summaryMisspec`.

## Usage

 `1` ```popMisfitMACS(paramM, paramCM, misspecM, misspecCM, dfParam=NULL, fit.measures="all") ```

## Arguments

 `paramM` The model-implied mean from the real parameters `paramCM` The model-implied covariance matrix from the real parameters `misspecM` The model-implied mean from the real and misspecified parameters `misspecCM` The model-implied covariance matrix from the real and misspecified parameters `dfParam` The degree of freedom of the real model `fit.measures` The names of indices used to calculate population misfit. There are three types of misfit: 1) discrepancy function (`"f0"`; see `popDiscrepancy`), 2) root mean squared error of approximation (`"rmsea"`; Equation 12 in Browne & Cudeck, 1992), and 3) standardized root mean squared residual (`"srmr"`)

## Value

The vector of the misfit indices

## Author(s)

Sunthud Pornprasertmanit ([email protected])

## References

Browne, M. W., & Cudeck, R. (1992). Alternative ways of assessing model fit. Sociological Methods & Research, 21, 230-258.

## Examples

 ```1 2 3 4 5``` ```m1 <- rep(0, 3) m2 <- c(0.1, -0.1, 0.05) S1 <- matrix(c(1, 0.6, 0.5, 0.6, 1, 0.4, 0.5, 0.4, 1), 3, 3) S2 <- matrix(c(1, 0.55, 0.55, 0.55, 1, 0.55, 0.55, 0.55, 1), 3, 3) popMisfitMACS(m1, S1, m2, S2) ```

simsem documentation built on June 3, 2018, 5:04 p.m.