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Hi. I am running an EFA with 12 categorical variables and all load strongly on a single factor (factor loadings range between .771 and .953). However, while my Chi Square is significant and the CFI = .989 and TLI = .987, the RMSEA is .184 and the SRMR is .061. Can you suggest any reason for the high RMSEA? Are there any steps that I should take to try and make it lower? Is it possible that the scale is still valid, even with the RMSEA out of an "acceptable" range? Thank you. 


The chisquare pvalue should be greater than .05 for good fit. It sounds like you need to modify your model. 


Linda, Thank you for your quick response. The Chi square pvalue being less than .05 can be attributed to the large sample size (n=1285), is there any reason that the CFI and TLI are good indicators of fit, while the RMSEA is not? Thanks again. 


If chisquare is not good, RMSEA will not be either. A low pvalue for chisquare cannot always be attributed to sample size. It is often truly a sign of poor fit. You might instead ask why CFI and TLI are good. This could be because of low correlations among your variables. 


Chisquare is not a reliable "fit index" since it is affected by sample size (it is always significant when N > 200). It is also affected by the complexity of the model (too many variables in one factor, just like your case). Check normality of the data since highly skewed and kurtotic variables would also increase chisquare values. 


Hi, We are running a CFA with two factors in Mplus. As a result we found the following fit indices: Chi square value:6959.053 pvalue:0.0000 RMSEA:0.130 CFI:0.955 TLI:0.944 All factor loadings were high, ranging between 0.603 and 0.882 Correlations among variables were high. Can you suggest any reason why the RMSEA is so high? The high chsquare can be attributed to the large sample size (n=7661) Thank you! 


I don't think these fit statistics show good fit. I would look at modification indices to seewhat is causing the misfit in the model. You might also consider an EFA to see if your CFA is correct the the data. 


Dear Ms. Muten, I´m running a CFA with three factors in Mplus (n>1000). As a result I got the following fit indices: chisquare: 1285 p .00000 CFI: 0.982 TLI: 0.979 RMSEA: 0.093 Factor loadings are very high (.80  .90) Factor correlations are high aswell (.80) CFI/TLI are very goog, while RMSEA is not. chisquare is (unfortunatly) significant. What do you think? Is the model fit ok? Can your recommend any papers accepting a RMSEA <.10 as an still appropriate model fit or discussing the problem (RMSEA bad, CFI/TLI very goog)? Thank you very much for your help in advance! 


I would explore the fit of this model further. You don't say what your sample size is but chisquare and RMSEA both show poor fit and CFI and TLI are similar in that they compare to a baseline model. 


My sample size is almost 1200 persons. 


This is not overly large. 

Xu, Man posted on Tuesday, March 26, 2013  11:49 am



The previous posts didn't show their df. I ran into a similar situation, but came across on the web that RMSEA could be artificially high for models with low df  actually it w. Kenny, D. A., Kaniskan, B., & McCoach, D. B. (2011). The performance of RMSEA in models with small degrees of freedom. Unpublished paper, University of Connecticut. 


I'm working with PISA data, and I'm using repweights, so i don't get a chisquare or CFI/NFIestimates, but I get this: RMSEA Estimate 0.056 90 Percent C.I. 0.053 0.059 Probability RMSEA <= .05 0.000 SRMR Value 0.026 Can the unacceptable RMSEA probability be contributed to my large sample (N=4686), or does the model really have unacceptable fit? My Mplus course teacher said that RMSEA and SRMR both under 0.06 showed good fit, but I'm unsure because of the probability. 


Please send the full output and your license number to support@statmodel.com. 


I'm having a similar problem. I'm running a CFA with one factor with four indicators, and I'm including one covariance between two indicator error variances, as mod indices of the model without the covariance indicated it would dramatically improve model fit. I have a sample size of N=1700. Chisquare is significant but has a very low value. My RMSEA is high, but CFI/TLI and SRMR are in a very good range. Should I be concerned about chisquare and RMSEA? ChiSquare Test of Model Fit Value 21.455 Degrees of Freedom 1 PValue 0.0000 RMSEA Estimate 0.109 90 Percent C.I. 0.072 0.151 Probability RMSEA <= .05 0.005 CFI/TLI CFI 0.995 TLI 0.972 ChiSquare Test of Model Fit for the Baseline Model Value 4429.274 Degrees of Freedom 6 PValue 0.0000 SRMR Value 0.007 


Also here are my correlations between the indicator variables, some of these are high, some are moderate, is this adding to the strange fit indices I'm getting Correlations DEL AGG DIS FIGHT ________ ________ ________ ________ DEL 1.000 AGG 0.775 1.000 DIS 0.485 0.599 1.000 FIGHT 0.541 0.614 0.820 1.000 


I just realized now that this is under an EFA discussion and not CFA...oops! Sorry, maybe someone can still answer though. Thanks! 


I would be concerned with the poor chisquare and RMSEA fits. It is quite possible this might not be the best model (e.g, why not 2 factors each with 2 indicators?), but with only 1 df and 4 indicators you have put yourself in a situation where it is hard to know. 

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