# What is CFI and Rmsea?

Table of Contents

## What is CFI and Rmsea?

RMSEA is an absolute fit index, in that it assesses how far a hypothesized model is from a perfect model. On the contrary, CFI and TLI are incremental fit indices that compare the fit of a hypothesized model with that of a baseline model (i.e., a model with the worst fit).

## What is an acceptable Rmsea?

It has been suggested that RMSEA values less than 0.05 are good, values between 0.05 and 0.08 are acceptable, values between 0.08 and 0.1 are marginal, and values greater than 0.1 are poor [8].

## What is an acceptable CFI?

CFI values range from 0 to 1, with larger values indicating better fit. Previously, a CFI value of . 90 or larger was considered to indicate acceptable model fit. However, recent studies have indicated that a value greater than . 90 is needed to ensure that misspecified models are not deemed acceptable.

## What is a good CFI value?

CFI is a normed fit index in the sense that it ranges between 0 and 1, with higher values indicating a better fit. The most commonly used criterion for a good fit is CFI ≥ . 95 (Hu & Bentler, 1999; West et al., 2012).

## How to use one factor confirmatory factor analysis?

1. One Factor Confirmatory Factor Analysis. The most fundamental model in CFA is the one factor model, which will assume that the covariance (or correlation) among items is due to a single common factor. Much like exploratory common factor analysis, we will assume that total variance can be partitioned into common and unique variance.

## How to perform a confirmatory factor analysis in R?

This seminar will show you how to perform a confirmatory factor analysis using lavaan in the R statistical programming language. Its emphasis is on understanding the concepts of CFA and interpreting the output rather than a thorough mathematical treatment or a comprehensive list of syntax options in lavaan.

## How are Modification indices used in confirmatory factor analysis?

However, the idea that CFA is solely a “confirmatory” analysis may sometimes be misleading, as modification indices used in CFA are somewhat exploratory in nature. Modification indices show the improvement in model fit if a particular coefficient were to become unconstrained.

## What is the difference between RMSEA and CFI?

CFI is the confirmatory factor index – values can range between 0 and 1 (values greater than 0.90, conservatively 0.95 indicate good fit) RMSEA is the root mean square error of approximation (values of 0.01, 0.05 and 0.08 indicate excellent, good and mediocre fit respectively, some go up to 0.10 for mediocre).