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Two variables remained in the model, gender and practice size.
Using this model, gender and the family history of the cancer were found as significant predictors.
In the distance model, gender and absolute value of FEV1 were identified as significant independent variables.
While other factors were held constant in the multivariate model, gender and age remained statistically significant factors affecting patient survival after hip fracture.
Using linear regression models and log-cost as dependent variable the adjusted R2 was calculated in the unadjusted model (gender) and in consecutive models where age, listing with specific PHC and RUB were added.
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Equal and decoding questions have newly been introduced into DTs to directly model gender- and context-dependent acoustic space.
In all models gender and SES were included as potential between-subjects factors, testing the main effects and interactions with time.
In the first model, gender, malignancy and wound was included, in the second, operation and radiation was added, and thirdly lymphedema.
The additive and multiplicative models revealed similar results with regard to covariates selected to remain in the model: gender, race/ethnicity, and age.
The independent variables were entered stepwise into the model: gender, age, interaction between gender and age, and finally, BMI.
In the Cox proportional hazard model, gender, age, N stage, and initial surgery were included.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com