Sentence examples for maximum likelihood logistic from inspiring English sources

Penalized maximum likelihood logistic regressions were carried out to predict episodes experiencing extreme length of stay.

Factors significant at p < 0.05 in univariate analysis were included in a maximum likelihood logistic regression model in ascending order.

Penalized maximum likelihood logistic regressions were carried out to estimate probabilities of episodes to experience a very long stay and a very short stay, respectively [ 14, 15].

Penalized maximum likelihood logistic regressions were carried out to estimate probabilities of episodes to experience a very long stay and a very short stay, respectively.

Variables with significance values of p < 0.1 in the univariate analysis were examined in a multivariate model using forward stepwise maximum likelihood logistic regression.

Modeling by least squares linear regression for continuous outcome variables and maximum likelihood logistic regression for dichotomous outcome variables was used to assess individual effects while adjusting for individually significant covariables.

The mutation status of EGFR, KRAS, BRAF and PIK3CA and their association with gender, age and smoking history were evaluated using Maximum Likelihood Multivariate Logistic Regression.

To assess the hierarchical structure of the data (center > patient > site), a linear mixed model using the restricted maximum likelihood method (multilevel logistic models for binary outcomes) was constructed to analyse the PPD, mBoP and suppuration, adjusting for factors such as age, gender and past smoke exposure.

Odds ratios (ORs) were estimated by maximum likelihood using unconditional logistic regression.

The prevalence of CM use was calculated using maximum likelihood estimation of logistic regression.

Boosting approximates the best linear combination of all possible weak classifiers (e.g different features) via maximum likelihood on a logistic scale, thereby solving statistical dependence problems [21].