Suggestions(1)
Exact(1)
A multivariate logistic regression model with 30-day mortality as the independent outcome was built with the initial inclusion of variables with a P<0·2 on univariate analysis and backwards stepwise elimination of variables using a likelihood ratio test to determine the statistical significance of candidate explanatory variables.
Similar(59)
Initial inclusion of the variable into model was set at P <0.1 but a P value <0.05 was considered for final comparison.
The initial inclusion of comments and grouping into codes proceeded collaboratively, with multiple perspectives and consensus.
Likelihood ratio tests determined appropriate inclusion of variables in the multivariate logistic regression model.
Inclusion of variables was performed as described in the tables.
The selection of variables for inclusion in the model was based on the backward elimination procedure with an initial inclusion probability of p < 0.05 and an exclusion probability of p ≥ 0.1.
An important component of the model was inclusion of variable prey preferences for zooplankton.
It is the inclusion of variable costs that makes the model quadratic.
We chose practice, doctor, and patient related variables for initial inclusion on the basis of a theoretical justification or evidence from previous literature indicating that they might relate to patients' satisfaction or experience.
1. Obtain an initial estimate of variables.
This period extends to 2.5 years from the date of initial inclusion.
Write better and faster with AI suggestions while staying true to your unique style.
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