Examples of 'multivariate logistic' in a sentence
Meaning of "multivariate logistic"
multivariate logistic: Multivariate logistic refers to a statistical technique used to analyze the relationship between multiple independent variables and a categorical dependent variable. It is commonly employed in research, data analysis, and predictive modeling to understand and predict outcomes based on the input variables
How to use "multivariate logistic" in a sentence
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multivariate logistic
Odds ratios are from a multivariate logistic regression.
Multivariate logistic regression analysis kept this relationship.
These variables were then submitted to a multivariate logistic regression.
Bivariate and multivariate logistic regression analyses were conducted.
The predictive values were analyzed using a multivariate logistic regression.
Two multivariate logistic regression analyses will be conducted.
Independent variables analysed in the multivariate logistic regression analyses.
A multivariate logistic model was constructed.
Predefined prognostic factors were tested using multivariate logistic regression.
Univariate and multivariate logistic regression models were used.
Its statistical analysis was performed using multivariate logistic regression.
Multivariate logistic regression explored variables related to tobacco smoking.
Correlations were analyzed using simple and multivariate logistic regression analysis.
Univariate and multivariate logistic regressions were performed to identify risk factors.
Risk factors for mortality were explored through multivariate logistic regression.
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The multivariate logistic regression analysis was used to determine odds ratios.
The joint effect of all variables was identified by a multivariate logistic regression model.
Multivariate logistic regression was used to assess independent predictors of postoperative events.
This association remained even when analyzed in a multivariate logistic regression model.
Multivariate logistic regression was used with the use of a hierarchical model to.
The results were also submitted to the exact multivariate logistic regression analysis.
A multivariate logistic model was built up using the variables mentioned before.
Significant parameters were then entered into the multivariate logistic regression model.
Multivariate logistic regression analysis was performed to test assumed risk factors.
Descriptive statistics and stepwise univariate and multivariate logistic regression analyses were performed.
Multivariate logistic regression analysis was performed to identify factors associated with hospital mortality.
Seven other variables of acknowledged importance in literature comprised the multivariate logistic regression analysis.
Multivariate logistic regression was performed to investigate the factors associated with sleepiness in adolescents.
All these nine variables mentioned above were included in the multivariate logistic regression analysis.
Multivariate logistic regression was applied to identify possible predictors of pre and postoperative analgesia.
Predictors of postoperative employment were analyzed with univariate and multivariate logistic regression analysis.
A multivariate logistic and a linear regression model were built to control for confounding variables.
Adjusted multivariate linear regression analyses and adjusted multivariate logistic regression analysis were performed.
Multivariate logistic regression is commonly used in the fields of medical and social science.
They analysed the data appropriately using a technique called multivariate logistic regression analysis.
Univariate and multivariate logistic regression were estimated to access the independent effects of explanatory variables.
Feeling depressed was the only independent variable associated with loneliness in a multivariate logistic regression model.
Univariate and multivariate logistic regression were used to identify factors associated with hospital mortality.
They then compared all variables between the groups and performed multivariate logistic regression analyses.
Multivariate logistic regression and cox proportional hazards were used to identify outcome related co variables.
Risk factors associated with PAD were entered into a multivariate logistic regression model.
Multivariate logistic regression was used to determine factors independently associated with complete mental health.
The NARAF association with living areas remained significant after inclusion in the multivariate logistic regression.
Five of the studies used multivariate logistic regression models to account for these confounders.
Thus, these variables were selected for multivariate logistic model.
The multivariate logistic regression was used for the joint evaluation of variables associated with death.
Table 2 describes the results of the multivariate logistic regression analysis.
Multivariate logistic regression analysis and principal component analysis were the main statistical techniques used.
Method, a case-control study was conducted through multivariate logistic regression analysis.
Univariate and multivariate logistic regression identified associations between independent variables and favorable results and conclusions.
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Extant logistic principles and procedures apply
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Decrease of total logistic cost on selected corridors
Examples of using Multivariate
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It does not engage in multivariate analysis or extensive interpretation
Multivariate analysis was performed by means of logistic regression
To answer this question a multivariate analysis was performed
