The Performance of RMSEA in Models With Small Degrees of Freedom

Sociological Methods and Research - Tập 44 Số 3 - Trang 486-507 - 2015
David A. Kenny1, Burcu Kaniskan2, D. Betsy McCoach1
1University of Connecticut, Storrs, CT USA
2National Conference of Bar Examiners (NCBE) Madison, WI, USA

Tóm tắt

Given that the root mean square error of approximation (RMSEA) is currently one of the most popular measures of goodness-of-model fit within structural equation modeling (SEM), it is important to know how well the RMSEA performs in models with small degrees of freedom ( df). Unfortunately, most previous work on the RMSEA and its confidence interval has focused on models with a large df. Building on the work of Chen et al. to examine the impact of small df on the RMSEA, we conducted a theoretical analysis and a Monte Carlo simulation using correctly specified models with varying df and sample size. The results of our investigation indicate that when the cutoff values are used to assess the fit of the properly specified models with small df and small sample size, the RMSEA too often falsely indicates a poor fitting model. We recommend not computing the RMSEA for small df models, especially those with small sample sizes, but rather estimating parameters that were not originally specified in the model.

Từ khóa


Tài liệu tham khảo

10.1037/0033-2909.88.3.588

Breivik Einar, 2001, Structural Equation Modeling: Present and Future, 169

Browne Michael W., 1993, Testing Structural Equation Models, 136

10.1177/0049124108314720

Curran Patrick J., 2000, Multivariate Applications in Substance Use Research, 1

10.1177/0049124103256130

10.1207/S15327906MBR3701_01

10.1037/1082-989X.1.1.16

Fishbein Martin, 1975, Belief, Attitude, Intervention, and Behavior: An Introduction to Theory and Research

10.1177/014920639402000303

10.1007/BF01065881

10.1080/10705519909540118

10.1037/a0014694

10.1037/0278-6133.27.2.258

10.1207/S15328007SEM1003_1

10.1207/s15328007sem1203_2

10.1097/01.PSY.0000107886.51781.9C

10.1207/s15327906mbr2502_2

10.1037/1082-989X.1.2.130

10.1207/S15324796ABM2501_01

10.1177/1745691610388766

10.1037/1082-989X.7.1.64

10.1016/j.paid.2006.09.021

Muthén Linda K., 2007, Mplus User’s Guide. Version 5

10.1080/00220970009600095

10.1080/10705519609540052

10.1177/0265407505056443

Steiger James H., Lind John C. 1980. “Statistically Based Tests for the Number of Common Factors.” Paper presented at the annual meeting of the Psychometric Society, May, Iowa City, IA.

West Stephen G., 2012, Handbook of Structural Equation Modeling, 209

10.1037/0021-9010.71.2.219

Thông tin
Thông tin xuất bản

Sociological Methods and Research

Tập 44 Số 3

486-507

Thông tin tác giả