Sentence examples for model with statistically from inspiring English sources

Still, a preceding birth interval of 24 to 36 months was the major contributor into the model, with statistically negative effects with reference category.

Inhibition data obtained from the checkerboard method, in the form of binary code, was used to compute a logistic response model with statistically significant results (p < 0.05).

Variables were selected by the best-subsets model-selection method, where the smallest model with statistically significant variables was included; the P value for inclusion in the model was less than 0.05.

Backward elimination (deleting the covariate with the largest P value, one at a time) was performed from the initial model until we reached a final model with statistically significant covariates.

In selecting the best structure, we looked for models with statistically significant data (P value <0.05) and then looked for the smallest confidence interval with average close to 0. For those that required further refinement, structures were tested until they fit this requirement.

This chapter discusses and illustrates variable selection that rigorously validate quantitative structure activity relationship (QSAR) models with statistically significant external predictive power ultimately afford their application as reliable virtual screening tools for database mining or chemical library design.

For models with statistically significant differences among visits, post hoc tests using Bonferroni-adjusted P-values were conducted to examine pairwise comparisons of means between visits.

In addition, the percent of variability in the immune response measures explained by the haplotypes was modest, even for the two models with statistically significant global tests (r-squared = 0.80% for the association of antibody levels with the combined class I and class II haplotype, and 4.98% for the class II only extended haplotype).

If the models with statistically significant coefficients that we report here had included these 28 low-creatinine observations, the estimates would have changed by 2 40%.

Multiple models were developed to ensure that conclusions of the analysis were not being dominated by individual covariates and to present variations of differing models with statistically relevant and clinically logical covariates.

In total, nine distinct multiple linear regression models with statistically significant differences were generated with genotypes and alleles data; in Table 4, the results obtained with the alleles are shown.