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Models were checked for goodness of fit.
The final multiple logistic regression model was checked for goodness of fit using the Hosmer-Lemeshow test.
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The final model was checked for goodness-of-fit using Hosmer Lemeshow statistics [ 10].
Segregations were checked for goodness-of-fit to the expected Mendelian ratio using a chi-square test at significance levels of 0.05 and 0.01.
We ran a series of diagnostic tests to ensure the model was correctly specified, to check for goodness of fit, multicollinearity and heteroskedasticity.
To analyze the consistency, measurements were analyzed graphically and statically checked for the goodness of fit (Chi-Square Test).
However, the logistic models have been checked for a goodness of fit using their residuals against fitted value plots, the factors included in the models were statistically significant; therefore, the analysis is valid.
The curve estimates for each patient were checked for their goodness-of-fit through analysis of their residual variance and R square.
However, obtaining an ARIMA model that closely fit a type of time series data requires that different ARIMA models are simultaneously constructed and checked for their goodness-of-fit prior to reach the satisfactory final model [ 11, 12, 14].
All models were checked for collinearity and goodness of fit [ 44].
The Cochran-Armitage test was used as a trend test for proportions, after checking for the goodness-of-fit of the underlying linear model (12 ).
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