Sentence examples for correlates model from inspiring English sources

In order to deal with sample attrition, the models were estimated using FIML estimation with auxiliary variables that predicted missingness or were predictive of the missing values themselves in a saturated correlates model (Graham et al., 2003; Spratt et al., 2010).

Unadjusted (model 1), partially adjusted (age and sex; model 2) and fully adjusted (age, sex, behavioural and sociodemographic correlates; model 3) logistic regression modelling was used to generate odds of low mental well-being compared with middle range (table 2), and high mental well-being compared with middle range (table 3) for different levels of behavioural correlates using SPSS V.21.

Akaike information criteria and partial rank correlation coefficients were employed to correlate model inputs with outcomes that were selected based on clinical and biologic relevance.

Auto-correlated model error terms will be included to allow for additional correlation among observations from the same patient in adjacent months.

In the Nodal SRLG-like correlated model, we assumed that only the links that share the same node follow the SRLG-like correlated model.

The Shortest Path under the Deterministic Correlated Model (SPDCM) problem is to find a path from a source s to a destination t with minimum cost.

In the Widest Path under the Deterministic Correlated Model (WPDCM) problem, if (m>1) correlated links in a path have a joint weight value W, then for each link the maximum average/amortized weight is (frac{W}{m}).

Although the SPDCM problem is NP-hard, we will show that, by transforming the original graph to an auxiliary graph, the Shortest Path under the Nodal Deterministic Correlated Model (SPNDCM) problem is solvable in polynomial time.

Third, compared to a more traditional data analysis (contrasts of mean BOLD responses in the factorial experimental design) the method of individually correlating model parameters to BOLD proved superior provided one accepts the theoretical assumptions underlying each of the approaches.

One of the main causes of poor mixing in the MCMC algorithm is correlated model parameters.

The admixture model and the allele frequencies correlated model were used to estimate the number of probable clusters (K value).