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Multivariate analyses were performed by conditional logistical regression by using a backward elimination model with Logistics (8 ).
The statistical evaluation of the data was carried out via step-wise logistical regression.
Using logistical regression and controlling for other variables, we found that the Administration in control at the time of decision is a statistically significant predictor of removal rates.
Multivariate analysis was performed with a logistical regression model.
Conditional logistical regression analysis was used to compare the migraine risks.
The logistical regression we used also gives indications for this concentration on the local area.
Risk of infection was modeled using a multivariate logistical regression analysis.
In a series of multivariate logistical regression models, we found cognitive restraint to be consistently and robustly associated with both measures of obesity.
Student's t-test was used to analyze hemorrhage size, midline shift, and Glasgow Outcome Score and logistical regression were used to measure allele affect on modified Rankin Score.
In a multivariate logistical regression model, increasing preoperative Zung self-rating depression scale scores were independently associated with patient dissatisfaction 2 years after revision lumbar surgery, (P<0.001).
Using BigQuery ML, developers can build models using linear and logistical regression right inside their data warehouse without having to transfer data back and forth as they build and fine-tune their models.
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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