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We used a multiple logistic regression model to evaluate the relationship between support for landscape planning and a natural property rights values.
All variables with a p value lower than 0.05 were included in a multiple logistic regression model to assess their independent association with "complete PEEP-absorber" behavior, with their effect expressed as odds ratio (OR) with 95%% confidence interval (95%% CI).
Thirty-four patients' data were retrospectively analyzed using a multiple logistic regression model to predict response.
The complication rates are expected to be too small to fit a multiple logistic regression model to determine important predictors.
We created a multiple logistic regression model to identify factors independently associated with the use of statins following kidney transplantation.
We then used a multiple logistic regression model to test the association between supermarket presence, deprivation tertile and time.
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A multiple logistic regression model was implemented to determine genotypes and other covariates associated with XPC.
A multiple logistic regression model was performed to evaluate the predictive value of potential perioperative variables.
A multiple logistic regression model was built to determine the predictors that impact upon compliance.
A multiple logistic regression model was developed in group A for DIC diagnosis.
A multiple logistic regression model was used for multivariate analysis.
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a binary logistic regression model to
a univariate logistic regression model to
a forward logistic regression model to
a multivariate logistic regression model to
a multinomial logistic regression model to
a bivariate logistic regression model to
a hierarchical logistic regression model to
a multiple logistic regression analysis to
a single logistic regression model to
a multivariable logistic regression model to
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