The phrase "a logistics regression" is not correct in English; it should be "a logistic regression." You can use it in contexts related to statistics or data analysis, specifically when discussing a type of regression analysis used for binary classification.
Example: "In our study, we applied a logistic regression to predict the likelihood of customer churn based on various factors."
Alternatives: "a logistic model" or "a logistic analysis."
To adjust for the clustering of patients within hospitals, a multilevel logistics regression was applied on all unplanned readmissions to examine the factors relating to the characteristics of index hospitalization that induced the avoidable readmission at 95% confidence intervals using the software Stata.
Third, a Multi-Nominal Logistics Regression Analysis was conducted for examining the influences of independent variables (at child and parental level) on the latent profile group according to the change in children's behavioral problems.
The second stage was to the application of logistics regression and ensuring a valid type 1 error was achieved by excluding non-significant candidates after Bonferroni correction.
Then, to control the effect of possible confounders, multiple logistics regression was computed with a confidence interval of 95%.
A significant difference on the knowledge of respondents among different groups of age, educational status, occupation, monthly household income, parity, knowing someone with cervical cancer and visit to a health institution was detected during the bivariate logistics regression analysis.
Prescreening using univariate logistics regression analysis followed by unconditional binary logistic regression analysis showed that maternal age ≤20 years, low educational level, history of one or more spontaneous abortions, history of one or more stillbirths, pregnancy-induced hypertension, anemia, premature rupture of membranes, oligohydramnios, preterm birth, and BMI <18.5 were risk factors.
*p < 0.05; **p < 0.01; ***p < 0.001; ORU: univariate odds ratio obtained using logistic regression; ORm: odds ratio obtained from stepwise multivariate logistics regression analysis using univariately significant variables as candidate variables; NS: not statistically significant in multivariate analysis.
*p < 0.05; **p < 0.01; ***p < 0.001; ORU: univariate odds ratio obtained from logistic regression models; ORm: odds ratios obtained from stepwise multivariate logistics regression analysis, using univariately significant variables as candidate variables; NS: not statistically significant in multivariate analysis.
