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This reflects the fact that fitting a model to a single variable does not result in as much over-optimism (over-fitting) as building a multivariate model using a large number of predictors.
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These variables were then used for building a multivariate logistic model.
It is clear from the data that the strongest association with blood pressure from all the anthropometric measurements is the gain in abdominal circumference; however, we acknowledge that when building a multivariate regression model of best fit, there is an element of chance as to which variables are included, even when they are not highly correlated.
The predictive factors with an OR where the confidence interval did not include 1 in the bivariate analysis were taken into account and entered into an analysis for the purpose of building a multivariate logistic regression model in order to calculate the OR adjusted to the predictive factors of the cohort.
A multivariate model was developed in the derivation cohort using an exhaustive modeling approach.
A multivariate model was designed in which the contributions due to the height of the buildings and the distance between buildings had a significant effect on the received power signal.
A multivariate model of early reading acquisition.
The impact of malnutrition on morbidity, mortality, length of hospital stay and costs evaluated through a multivariate model analysis.
It is a multivariate model.
These effects remained in a multivariate model after adjusting for age and disease status.
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.
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com