Sentence examples for predicting trait from inspiring English sources

Further support for 2 distinct dimensions of function being captured by DLPFC activity to Go trials in EF versus EM blocks was obtained from a hierarchical regression analysis; this showed that these 2 indices had not only opposite but additive effects in predicting trait vulnerability to anxiety, Table  1.

Evidence that this DLPFC activation may reflect a different process from DLPFC activity to Go trials in blocks without commission errors was provided by a hierarchical regression analysis which showed that these indices of DLPFC activity had not only opposite but additive effects in predicting trait anxiety.

For predicting traits of offspring, older children wanted to know the traits of both the parents and their ancestors.

This is mainly because the individual marker effects are often small for predicting traits, especially quantitative traits, which are influenced by many genes.

Several studies have shown better performance of BayesB in predicting traits influenced by a few genes of large effect (VanRaden et al. 2009; Daetwyler et al. 2010; Jannink et al. 2010).

However, due to the insertion of these other species, the authors were able to successfully build a more diverse model, capable of predicting traits from both heart- and sapwood, and differences in tree age.

Measuring fitness values to help predict trait frequencies of populations of evolutionary individuals in the future would then involve counting just all the relevant organisms.

Moreover, this study suggests that it is possible to predict trait loss from plant communities in forests where degradation is mediated primarily through subsistence agriculture and resource extraction.

Study 1 (N = 326) examined the role of trait AP, worry, and rumination in predicting symptoms of social anxiety, depression, and trait anxiety and found that all three RNT styles predicted social anxiety, but only worry predicted trait anxiety and only rumination predicted depressive symptoms.

After this adjustment, the trait population mean was added to the observations to obtain predicted trait values.

We found that GEMOT's predicted trait pairs were supported by the best-correlated transcripts across a wide range of trait trait correlations.