NCP

NCP

ØNCP

The NCP  table can be found under: View → Text Output → Model fit → NCP

NCP

Model

NCP

LO 90

HI 90

Default model

1,900

1,500

2,300

Saturated model

0

0

0

Independence model

1342,221

1234,123

1324,432

 

v NCP

 

NCP = value of non-centrality parameter with bounds expressed as LO (NcpLo) and Hi (NcpHi), respectively the lower and upper bounds of the 90% confidence interval for NCP.

The Normalized Chi-Square (NCP) is a fit index that measures the discrepancy between the observed covariance matrix and the implied covariance matrix derived from the model. It is calculated by dividing the chi-square value by its degrees of freedom and then by the number of observations. The reference values for NCP depend on the specific model and the number of variables and indicators included.

 

Interpretation:

 

General guidelines suggest that:

NCP values less than 2 indicate an acceptable fit,

while NCP values between 2 and 3 indicate a marginally acceptable fit,

and NCP values greater than 3 indicate a poor fit

Kline, 2011

 

www.StatistischeBeratung.de

 

LO 90 = 1,500 Lower limit (NCPLo method) of the 90% confidence interval for NCP.

HI 90 = 2,300 Upper bound (NCPHi method) 90% confidence interval for NCP.

From the example table above, the population NCP = 1,900 for the default model is between 1,500 and 2,300 with a confidence level of approximately 90 percent. NCP = 1,900 , values less than 2 indicate 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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