Goodness of fit Index (GFI)

Goodness of fit Index (GFI)

ØGoodness of fit Index (GFI)

 

The RMR, GFI table can be found under: View → Text Output → Model fit → RMR, GFI

 
 

RMR, GFI

       

Model

RMR

GFI

AGFI

PGFI

Default model

0,148

0,963

0,978

0,623

Saturated model

0

1

   

Independence model

0,152

0,545

0,643

0,324

 

v RMR

RMR = Root Mean Square Residual.

Reference values for RMR (Root Mean Square Residual) depend on the size of the model, the number of variables, and the values of other fit indices. There is no one specific set of reference values that can be universally applied, as different studies may have different expectations for what constitutes an acceptable level of RMR.

 

Interpretation:

 

A value RMR = 0 represents a perfect fit.

 

A value RMR <0,05 indicates an acceptable fit

 

RMR ≤ 0.05 = acceptable fit

Diamantopoulos & Siguaw , 2000

RMR ≤ 0.07 = acceptable fit

Steiger, 2007

Some commonly used thresholds for RMR include values less than 0,08 or less than 0,05

Hu & Bentler, 1999; Kline, 2016

The smaller the RMR value the better.

 

 

www.StatistischeBeratung.de

 

It is important to note that these thresholds are not absolute and should be considered in conjunction with other fit indices when evaluating model fit.

RMR are 0,148 for our tested (default) model.

 

v GFI *

GFI stands for Goodness of fit Index and is used to calculate the minimum discrepancy function necessary to achieve a perfect fit under maximum likelihood conditions (Jöreskog & Sörbom, 1984; Tanaka & Huba, 1985). The Goodness of fit Index (GFI) is a measure of how well the model fits the data, with values ranging from 0 to 1.

GFI = Goodness of fit Index and takes values of ≤ 1.

 

Interpretation:

 

A value GFI = 1 represents a perfect fit.

 

Higher values indicate a better fit.

 

A value GFI ≥ 0,9 indicates a reasonable fit

Hu & Bentler, 1998

values above 0,90 indicate a good fit

Hair, Anderson, Tatham, and Black, 1998

A value GFI ≥ 0,9 indicates a reasonable fit

Homburg/Baumgartner, 1988, S.363

A value GFI ≥ 0,95 is considered an excellent fit

Kline, 2005

suggests that values between 0,90 and 0,95 are acceptable fit and values above 0,95 are excellent fit

Kline, 2016

 

www.StatistischeBeratung.de

 

GFI are 0,963 for our tested (default) model, this is considered an excellent fit.

 

v AGFI

 AGFI = Adjusted Goodness of fit Index and indicates the degree of freedom (df) for testing the model. A value of 1 indicates a perfect fit. Unlike GFI, AGFI values do not stop at 0.

The reference values for AGFI (Adjusted Goodness of fit Index) may vary depending on the specific research field and the complexity of the model. It is important to note that these are general guidelines and the specific threshold for an acceptable fit may vary depending on the research context and the complexity of the model.

 

Interpretation:

 

A value AGFI = 1 represents a perfect fit.

 

A value AGFI ≥ 0,9 indicates a reasonable fit

Bagozzi/Yi, 1988, S.82

A value AGFI ≥ 0,9 indicates a acceptable fit

Tabachnick & Fidell, 2007

AGFI values greater than 0,90 indicate an acceptable fit,

while values greater than 0,95 indicate a good fit

Hair et al., 2017

AGFI value of 0,80 or greater indicates an acceptable fit.

Hu and Bentler, 1999

 

www.StatistischeBeratung.de

 

AGFI are 0,978 for our tested (default) model, this is considered an excellent fit.

 

v PGFI

PGFI = Parsimony Goodness of fit Index is a modification of GFI (Mulaik et al.,1989) and calculates the degree of freedom for the model.

PGFI (Adjusted Goodness of fit Index) is not a commonly used fit index in structural equation modeling, so there are no established reference values for it. PGFI is a modification of the GFI that adjusts for the complexity of the model and the number of estimated parameters.

The reference values may depend on the complexity of the model and the sample size.

 

Interpretation:

 

A value PGFI = 1 represents a perfect fit.

 

A value PGFI > 0,50 indicates an acceptable fit

 

PGFI value of 0,5 or greater indicates an acceptable fit

Joreskog & Sorbom, 1993

 

www.StatistischeBeratung.de

 

PGFI are 0,623 for our tested (default) model, indicates an acceptable fit.

  


Cite this article in your research paper:
APA

Statistische Beratung Leonardo Miljko (datum) How to interpret SEM model fit results in AMOS. Retrieved from https://www.StatistischeDatenAnalyse.de/images/services/How_to_interpret_SEM_model_fit_results_in_AMOS.pdf .

Harvard

Statistische Beratung Leonardo Miljko  January 10, 2020 How to interpret SEM model fit results in AMOS. viewed datum < https://www.StatistischeDatenAnalyse.de/images/services/How_to_interpret_SEM_model_fit_results_in_AMOS.pdf >

 

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