Examples of 'binary logistic regression' in a sentence
Meaning of "binary logistic regression"
Binary logistic regression is a statistical analysis 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 social sciences and medical research, to predict the probability of an event occurring based on certain predictors
How to use "binary logistic regression" in a sentence
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binary logistic regression
They are binary logistic regression models.
Multivariate analysis was calculated by means of binary logistic regression.
Binary logistic regression was used in the other situations.
Results of the binary logistic regression.
Binary logistic regression analysis was conduct to test the proposed hypotheses.
Most statistical software can do binary logistic regression.
Procedures of binary logistic regression were used for the multivariable analysis.
Tests to analyze associations and binary logistic regression were used.
A binary logistic regression model was employed to analyse the collected data.
The research method was binary logistic regression analysis.
A binary logistic regression was used to express the degree of association between variables.
The multivariate analysis was calculated using binary logistic regression.
Binary logistic regression was used in the statistical analysis of the data.
The control of possible confounding factors was performed by binary logistic regression.
Cross tabulation and binary logistic regression were the main statistical analyzes.
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Red blood cell transfusions were treated as dependent variables in binary logistic regression.
Binary logistic regression was used to predict what variable was associated with treatment failure.
The presence of pike fry was analysed with binary logistic regression.
Descriptive statistics and binary logistic regression model were employed to analyze the data.
All statistically significant variables were evaluated for inclusion in a binary logistic regression analysis.
Binary logistic regression was used for bivariate analysis aiming at identifying predictors for postpartum depression.
The relationship between psychopathy was assessed with binary logistic regression analysis.
The previous example uses binary logistic regression because the response variable has two levels.
Association between motor performance and frailty tests was verified by binary logistic regression technique.
Binary logistic regression models Enter method were run with all these variables.
All variables that showed differences between the groups were evaluated by binary logistic regression.
The binary logistic regression model was adjusted to assess possible risk factors for UI.
A multivariate analysis was performed using binary logistic regression through the Enter method.
The binary logistic regression model is as follows,.
Example of Contour Plot with a binary logistic regression model.
Then, binary logistic regression was performed.
In the multivariable analysis, binary logistic regression was used.
Therefore, binary logistic regression was employed using the backward method.
For multivariate analyses, we used a binary logistic regression.
Secondly, the binary logistic regression was applied to identify the magnitude of the associations.
The analysis consisted of, frequency distribution, univariate and multivariate analysis using binary logistic regression.
For multivariate analysis, the binary logistic regression model was used.
Next, binary logistic regression was performed to identify the same associations adjusted by potential confounders.
The analysis covered the use of descriptive procedures, chi-square test and binary logistic regression.
In all analyzes, was conducted binary logistic regression with correction for the design effect.
Table 3 shows VAP-related factors, selected by binary logistic regression.
Finally, we performed a binary logistic regression analysis including the main risk factors for extubation failure.
Odds ratios and the corresponding 95 % confidence intervals were calculated using binary logistic regression.
Table 5 Results of binary logistic regression model.
This binary logistic regression model known as Fibrotest was developed by Dr. T. Poynard ref.
For more information, go to How data formats affect goodness-of-fit in binary logistic regression.
The results of the binary logistic regression are presented in Table 4.
The variables with p < 0.10 were subjected to binary logistic regression model.
For this purpose, binary logistic regression through the backward LR method was used.
The variables presenting p < = 0.25 were included in the binary logistic regression analysis Enter method.
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