Sentence examples for Predictor variable in the model from inspiring English sources

The effect size of the predictor variables was calculated using Eta-squared, which represents the proportion of total sum of squares explained by each predictor variable in the model [56].

We therefore included the number of pins as a predictor variable in the model.

In our proposed random effects mixture model, serial correlation can be incorporated by including a lagged response variable as a predictor variable in the model [ 37].

The basis of the model is a decision tree, which uses a binary recursive partitioning procedure to measure the amount of variation in a response variable explained by each predictor variable in the model, splitting the response variable successively by the variable explaining the majority of the remaining variance.

The impact of smoke-free legislation, defined as a change in the rate of admissions for myocardial infarction after the legislation, was assessed by including a binary predictor variable in the model with a value of 1 assigned to myocardial infarction events occurring from week 27 of that year (that is, from 2 July 2007 onwards) and 0 before.

Finally, we tested for evidence of the constant risk fallacy by testing for interactions between the centre and each predictor variable in the model individually against outcome (death at seven days) to investigate whether the risk for a given factor was constant across centres, as evidence of interactions indicates that risk is not constant between centres.

These and other comparisons of binary outcomes will be performed using logistic regression with the intervention group as a predictor variable in the models.

GRUMP population density and urban extents are predictor variables in the model in this paper.

Multiple hemodynamic features were extracted from the arterial pressure waveform and used as predictor variables in the model.

Partial dependency plots were used for interpretation and to quantify the relationship between each predictor variable and the disease, after accounting for the average effect of all other predictor variables in the model.

The BIC penalizes the log likelihood of a model (a measure of its fit) by a factor related to the number of predictor variables in the model (a measure of its complexity) and the number of cases [29].