Multivariable regression models assessed good quality scores (≥50% of maximum) as the dependent variables and country, academic affiliation, being member of a healthcare consortium, confessional affiliation, and content management system (CMS) use as independent variables.
Overall the validity of those LUR models, assessed with the R (see Supplemental Material, Table S5), were good, although this varied across study sites.
The overall fit of the model, assessed by the comparative fit index, was good [CFI = 0.97, root mean square error of approximation (RMSEA) = 0.05, χ/d.f. = 1.85].
These procedures are good models to assess bone healing as the surgical procedure performed is standardised and weight-bearing can be assessed at regular intervals.
Furthermore, we conducted Hosmer and Lemeshow's goodness-of-fit test to assess how good the model fits the data.
In order to statistically assess the good specification of a model, we carried out an analysis of residuals.
To assess how good a fit our model is to a set of samples, the root mean square error, RMS, between the model and the data was calculated.
Fitted curves (3rd, 50th, and 97th centiles) from different models were assessed visually for a good fit and by comparing the deviances from each model.
As such, NVP is a good model to assess sex-dimorphic metabolism.
These results suggest that Arabidopsis could be a good model to assess new eIF4E alleles for resistance to TEV and may also be used to assess their durability.
