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Testing adequacy of fit (in addition to testing what is the best fitting model) is important as the best fitting model could still not fit the data adequately (Goldman 1993), and the use of models that do not fit the data adequately can drive the appearance of tree reconstruction artifacts.

The best fitting model is shown in Fig. 5.

Therefore, the best fitting model is selected by relatively compared values over all indices.

The best fitting model is a matched Q matrix of which the match is not that strict or smooth with regard to the degree of overlap.

The best fitting model is printed in bold font.

Our best fitting model is described in table 6.

Thus, based on all fit indices, the best fitting model was retained in all following analyses.

In confirmatory factor analysis, the selection of the best fitting model was based on several fit indices.

The best fitting model was chosen according to the statistical criteria.

In the end the deviations from the best fitting model were investigated.

The parameters of the best fitting model are listed in Table 1.