Sentence examples for exclusion of variables from inspiring English sources

This modelling was performed using a set of constant parameters only, i.e. with exclusion of variables.

Data reduction, in this case by indicator selection, is only considered in the components where instability is suspected in the CATPCA solution and corrected by the exclusion of variables.

However, there are limitations to the validity and quality of data in psychiatric registries, including over-representation of severe cases or inpatient data, sparse clinical detail, exclusion of variables not available from all institutions reporting to the register, and insufficient linking to other registries such as cause of death (Munk-Jørgensen et al. 2014).

One has to choose the values of the F statistic for the partial F tests that will determine if a variable is to enter or be removed from the model; F = 0.25 has been chosen as the threshold for inclusion and exclusion of variables.

p ≥ 0.1 for F-values was taken as criterion for exclusion of variables.

For these, the P value for the inclusion and exclusion of variables was set at 0.05.

In this subsection I briefly intend to explain why our main results are not driven by the exclusion of variable TRUTHFUL from the crime process.

Additionally, because collinearity can lead to unjustified exclusion of explanatory variables, all variables not significantly associated in the univariate analyses were added to the multivariable model one by one.

The multiple imputation analyses are not presented as the main analyses as it was technically impossible to perform an imputation without comprehensive manipulation of the data, such as redefinition of the continuous variables into binary or ordinary variables and exclusion of the variable "academic problems" (important to calculate the propensity score) because of collinearity.

Given the nature of ENMs, especially the restricted set of abiotic variables and the complete exclusion of biotic variables from the analyses, such results must be treated with caution [33], [80].

The best subsets of explanatory variables were selected through exclusion of the variables with the smallest contribution to the model (the largest p-values).