Sentence examples for multivariate modeling the from inspiring English sources

In this study, multivariate prediction models achieved a higher level of accuracy than narrow-band vegetation indices, making multivariate modeling the best choice for mapping.

In multivariate modeling, the relationship of GEDV and GEDVI with age was highly significant and non-linear.

In contrast to traditional multivariate modeling, the random forest analysis can account for inter-relationships among all potential predictors including highly multilevel unordered categorical covariates in building a tree-based predictive model.

On multivariate modeling, the number of prior concussions was associated with increased scores on impulse control (P = 0.021) and increased baseline total scores on the Post-Concussion Symptom Scale (P < 0.001).

In multivariate modeling, the main outcome measures were Preterm delivery (before 34 and 37 weeks), low Apgar score (5 min ., small-for-gestational-age, fetal death, asphyxia, Cesarean delivery, induction, blood transfusion and admission to a Neonatal Intensive Care Unit.

10 Although the association of prior concussion and cognitive composite scores did not remain in multivariate modeling, the association between baseline symptoms and number of concussions was present after controlling for possible confounders.

In this multivariate model, the strongest independent predictors of survival were (in order of statistical significance) overall stage, patient age, vascular invasion, and SI score.

For the multivariate models, the independent variables that were significant on univariate analyses were included.

In the sense of solving the problems attributed to multivariate models, the classical univariate prediction models (UPMs) were developed.

After running this data through a multivariate model, the authors were able to calculate the factors that best predicted whether a marriage would end in divorce.

For these multivariate models, the best fit RMSE is obtained from SARIMAX 0,1,2)(1,0,0) with LST, rainfall and relative humidity as covariates.