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The phrase "a fair fit" is correct and usable in written English.
It can be used to describe something that is reasonably suitable or appropriate for a particular situation or context.
Example: "After reviewing the candidates, I believe she is a fair fit for the role based on her experience and skills."
Alternatives: "a suitable match" or "an appropriate choice".
Exact(10)
The results show a fair fit between the mean values of observed and predicted work hour alternatives.
Although some authors consider a value of.06 a fair fit, the cut-off point of <.05 is usually used.
An RMSEA lower than 0.05 indicated a good fit while values lower than 0.08 indicated a fair fit.
An RMSEA lower than 0.08 indicates a fair fit, and a CFI higher than 0.9 indicates that the model satisfactorily fits the data.
Fit statistics indicate a fair fit of the model to the data (χ=408.8, degrees of freedom=76, p-value<0.01; CFI=0.79; TLI=0.63; RMSEA=0.12).
There was a fair fit of the model to the data (χ = 110.6, df = 38, p = 0.00, ratio 2.9, NFI = 0.74, and RMSEA of 0.09), it explained 8% of the variance of exercise behavior at six months post hip fracture.
Similar(50)
A fairer fit of the model with the observed for all parameters over Jicamarca suggests that equatorial regions are better represented on the model.
The models were evaluated by means of Bentler Satorra chi-square score, root mean square error of approximation (RMSEA) (23), goodness-of-fit index (GFI), and adjusted goodness-of-fit index (AGFI), where the values of RMSEA less than 0.05 indicate a close fit, values in the range of 0.05 to 0.08 indicate fair fit, and that values above 0.1 indicate poor fit.
The format of Vanity Fair fit Benchley's style very well, allowing his columns to have a humorous tone, often as straight parodies.
Generally, RMSEA that was smaller than 0.05 suggested good fit, 0.05-0.08 fitr fit while greater than 0.10 poor fit.
This model achieved fair fit with data (RMSEA = .06); however, the RMSEA confidence interval indicated sampling instability (RMSEAC.I. =.000 -.111).
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com