Criteria Goodness Of Fit

In a scientific study, some problems studied typically based on theories that already exist. further research is done gradually, step by step scientifically, so that the study results in a scientific conclusion in accordance with the rules of science (Scientific Research). In the execution of research must not be separated from the basic guidelines thinking usually called a theoretical framework. In conducting an ongoing investigation, we as a researcher needs to develop a theoretical framework that is used as a basis of reasoning that can describe aspects of which we may highlight a problem that we have chosen.
Furthermore, the theory is still an assumption, and construction concepts, definitions and propositions in order to explain a problem that was appointed to study whether it is a social phenomenon that occurs in the wider community, in institutions systematically by way of formulating the relationship between concepts. As for subsequent researchers must conduct a test as a statistic which is the result of observations made in the field, the results of these observations were either on the answers of a questionnaire containing questions about issues being studied or the status of the respondents related to the issues being studied or also the individual characteristics can influence a problem that used in the research hypothesisIn the analysis of statistical data or test course, we will find with the name
  1. Chi Square. The purpose of this analysis is to develop and test whether a model that fits the data. Chi-Square-sensitive samples that little or too much. Therefore, this test should be complemented with other test equipment. As for the value of probability of Chi-squares> 0.05 it indicates the empirical data is identical to the model.
  2. Goodness of Fit Index (GFI) is the index that mnggambarkan the degree of similarity or conformity with the overall model which is calculated from the squared residuals of the model predicted, compared to the actual data. GFI value> 0.90, this suggests that the models tested has a good agreement.
  3. Root Mean Square Error of Approximation (RMSEA). This is a measure to try to correct the tendency chi-square statistic that rejects the model with a large number of samples. The RMSEA value between 0.05 and 0.08 indicating a good index to accept conformity to the model.
  4. Adjusted Goodness Of Fit Index (AGFI). According Ghozali, (2005) This index is the development of Goodness Of Fit Index (GFI) as adjusted for the ratio of the degree of freedom. Analogous to R2 in the regression. AFGI recommended value is> 0.90, the greater the value the better AFGI for suitability owned models.
  5. Tucker Lewis Index (TLI) is the index that compares the incremental conformity with the model that will be tested at baseline models. TLI is used to overcome the problems arising from the complexity of the model. Acceptance of the recommended value is the value of TLI> .90. TLI is an index that is less affected by sample size
  6. Normed Fit Index (NFI). This index is a measure to compare the proposed models and null models. The recommended value in NFI> 0.90.
  7. Comparative Fit Index (CFI). The CFI is an incremental suitability index. The magnitude of this index is in the range of 0 s / d 1 and a value close to 1. This indicates that the model has a good level of fitness. This index is recommended for use as the index is relatively insensitive to sample size and is less affected by the complexity of the model. The acceptance of the recommended value is CFI> 0.90

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