Examples of using Logistic regression model in English and their translations into Spanish
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the basis in particular of logistic regression model, the most prevalent form of regression analysis for categorical response data.
we developed a logistic regression model, presented below, in which the value that citizens give a candidate's plaform before voting is measured on a scale of 1 to 7.
we ran a logistic regression model using the following variables as predictors:
Multiple logistic regression models were used to determine the variables associated with mortality.
We used logistic regression models to predict the presence of a BCG scar.
Descriptive analyses were conducted and logistic regression models were adjusted.
GLMs with this setup are logistic regression models(or logit models). .
Logistic regression models were constructed to assess the risk for mineral deficiencies.
The data were analysed by use of 2x2 contingency tables and logistic regression models.
With this, it was determined to carry out three logistic regression models.
Prevalence was calculated and associations were established by binary logistic regression models.
covariates was evaluate by logistic regression models.
The data was analyzed using Fisher's exact test and logistic regression models.
Multivariate logistic regression models were applied to calculate the odds ratios for the delay.
Logistic regression models were adjusted, obtaining adjusted odds ratio and their confidence intervals(95%).
Logistic regression models were constructed,
It has been estimated using binary logistic regression models and ordered logistic regression models. .
The 2004 LAPOP study applied logistic regression models to study the characteristics of the people who attend municipal meetings
Logistic regression models, they can be used to estimate the probabilities of things like lightning striking,
tables of correlation based on logistic regression models are established between antibody titre and clinical protection.