Examples of 'logistic regression analysis' in a sentence
Meaning of "logistic regression analysis"
Logistic regression analysis refers to a statistical method used to model the relationship between a binary dependent variable and one or more independent variables. It is commonly used in various fields, such as economics, social sciences, and healthcare, to predict the probability of an event occurring
How to use "logistic regression analysis" in a sentence
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logistic regression analysis
A logistic regression analysis was then conducted.
To check this association was used ordinal logistic regression analysis.
Multivariate logistic regression analysis kept this relationship.
The main statistical method was logistic regression analysis.
A logistic regression analysis allowed us to analyze these determinants.
Dwelling sites were modeled with logistic regression analysis.
Logistic regression analysis was employed for multivariate analysis.
The research method was binary logistic regression analysis.
Nonconditional logistic regression analysis was carried out stratified by gender.
All variables were then tested in a multiple logistic regression analysis.
Calculated by logistic regression analysis was used as.
Correlations were analyzed using simple and multivariate logistic regression analysis.
Logistic regression analysis was used to find predictive factors.
This greater time was identified by logistic regression analysis related to death.
Logistic regression analysis is often used to investigate the relationship.
See also
There were performed descriptive as well as bivariate and logistic regression analysis.
Estimated by logistic regression analysis after adjusting for age.
The factors contributing to admission were analysed by logistic regression analysis.
The multivariate logistic regression analysis was used to determine odds ratios.
Binary responses of individual trees were modeled using logistic regression analysis.
Logistic regression analysis was used as the main statistical method.
The results were also submitted to the exact multivariate logistic regression analysis.
Binary logistic regression analysis was conduct to test the proposed hypotheses.
Risk factors associated with nutritional status were identified by logistic regression analysis.
Multiple logistic regression analysis identified independent risk factors and confounders.
The probability of successful desistance was predicted using logistic regression analysis.
Multivariate logistic regression analysis was performed to test assumed risk factors.
A simulation study of the number of events per variable in logistic regression analysis.
Logistic regression analysis was done on all baseline demographic variables and disease characteristics.
All statistically significant variables were evaluated for inclusion in a binary logistic regression analysis.
Multivariate logistic regression analysis was performed to identify factors associated with hospital mortality.
The relationship between psychopathy was assessed with binary logistic regression analysis.
Backward stepwise logistic regression analysis was conducted to determine independent correlates of medication adherence.
The association between prognostic factor and outcome was determined using logistic regression analysis.
Logistic regression analysis has shown relative risk of being female and having pain.
Seven other variables of acknowledged importance in literature comprised the multivariate logistic regression analysis.
The logistic regression analysis was performed to assess the relationship between the methods.
All these nine variables mentioned above were included in the multivariate logistic regression analysis.
Logistic regression analysis was performed to determine factors independently associated with hospital mortality.
Associations between autistic traits and sleep were examined using logistic regression analysis.
The logistic regression analysis allowed us to test sensitivity at different screen positive rates.
Predictors of postoperative employment were analyzed with univariate and multivariate logistic regression analysis.
Logistic regression analysis was used to examine the association between victimisation and health.
Adjusted multivariate linear regression analyses and adjusted multivariate logistic regression analysis were performed.
Logistic regression analysis was applied to find the factors associated with potential drug interactions.
They analysed the data appropriately using a technique called multivariate logistic regression analysis.
The logistic regression analysis was used to adjust the predictors of severity for confounding variables.
The relationship between identity diffusion and experienced happiness was examined by using logistic regression analysis.
Multiple logistic regression analysis of age and body weight was significant for failure of wean.
SuPAR as prognostic marker was analysed using logistic regression analysis.
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