Sentence examples for tests of deviance from inspiring English sources

We also carry out tests of deviance to compare different models, allowing for overdispersion.

Statistical significance of a coefficient was tested under full maximum likelihood (ML) estimation, using a Chi-square test of deviance.

Statistical significance of fixed effects was tested by comparing the goodness of fit of different models using a chi-square test of deviance.

Statistical significance was tested by comparing the goodness of fit of a model with, and without the variable, using a chi-square test of deviance.

Model selection and Wald chi-squared test of deviance (compared with the null model that did not have any prediction variable) results are shown in Table 2.

Including all statistics was calculated based on the paired-end reads We compared mRNA expression in floral buds and flowers of DAH3615 and DAH3615-MS samples (Fig.  1) using two different statistical tests [analysis of deviance (ANODEV and Fisherr's exact test], in order to detect sterility-related genes (Fig.  2a and Additional file 1).

Both linear and quadratic trends were examined and goodness-of-fit tests of the deviance between linear and quadratic models were used to assess most appropriate fit.

In addition, we considered both the statistical and qualitative aspects of the observed geographic patterns, tempering interpretation of areas of sparse data by considering tests of global deviance and changes in the optimal span size along-side visual inspection of the patterns in our interpretation of results.

The frequency of sampling isofunctional homologs of ppk1, ppx and pstS showed a significant difference from the null model (p-value = 0.001, 9.674×10−5 and 3.08×10−6 respectively (d.f. = 37), calculated using a Fisher test analysis of deviance as is appropriate for models based on quasi-likelihood [50]).

The statistical significance of main effects and interaction terms in the model was tested with F-tests by analysis of deviance, which involved looking at the change in deviance caused by the removal of each term from the maximal model after having allowed for overdispersion in the data by calculating a variance heterogeneity coefficient with the Williams algorithm (25, 26 ).

Chi-square tests from analyses of deviance comparing models with and without the smooth exposure term were performed, and no statistical departures from linearity were apparent at a p < 0.05 level of significance.