Examples of 'multinomial logistic' in a sentence
Meaning of "multinomial logistic"
multinomial logistic: This phrase is a statistical term referring to a type of regression analysis used to predict the outcome of categorical dependent variables with three or more categories. It is commonly used in statistical modeling and data analysis
How to use "multinomial logistic" in a sentence
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multinomial logistic
Multinomial logistic regression was used to determine the.
Results of the multinomial logistic regression.
Multinomial logistic regression was used in the multivariate analysis.
One form of multivariate analysis is the multinomial logistic regression.
We applied multinomial logistic regression models separately by sex.
The main method of analysis was multinomial logistic regression.
The multinomial logistic regression has the following specification.
The main method of analyzing was multinomial logistic regression.
Multinomial logistic regression was used for the analysis.
The transitions probabilities are estimated using multinomial logistic regressions.
Multinomial logistic regression and multinomial probit regression for categorical data.
The methodologies used are multinomial logistic regression and discriminant analysis.
Multinomial logistic regression is useful for modeling probabilities of multiple category outcomes simultaneously.
Below we use the nomreg command to estimate a multinomial logistic regression model.
The multinomial logistic model is estimated through an instrumental approach using meteorological data.
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Analytical procedures included descriptive statistics and multivariate modeling binary and multinomial logistic regression.
The method is based on the multinomial logistic regression applied to a longitudinal structure data.
The association between chronic diseases and independent variables was assessed through multinomial logistic regression.
The multinomial logistic regression model enabled to disaggregate functional capacity into more than two categories.
There are multiple equivalent ways to describe the mathematical model underlying multinomial logistic regression.
Multinomial logistic regression models were used to predict the diagnostic group with these independent variables.
Table 3 shows the results of multinomial logistic regression.
Multinomial logistic regressions were used to test our hypotheses '.
Statistics were generated using x2 and multinomial logistic regression.
Multinomial logistic regressions were performed to identify correlates of the " active transportation " cluster.
Table 7 shows the results from the multinomial logistic regression.
Multinomial logistic regression for the outcome variable ' depression ' among inmates.
We used bivariate and multivariate analyzes, with multinomial logistic regression.
Multinomial logistic regression final model is presented in Table 2.
Table 2presents the results of multinomial logistic risk factors of different categories of anemia.
In addition to descriptive statistics, statistical analysis was used via a multinomial logistic regression model.
The Table 3 showed the multinomial logistic regression analysis.
The analysis of determinants of EC non-use was performed with multinomial logistic regression.
When analyzing data with a multinomial logistic regression, there is no an equivalent statistic to R-squared.
Descriptive analysis was performed along with a bivariate and multinomial logistic regression model ( p < 0.05 ).
Note, The multinomial logistic regressions model compares denied and approved borrowers to discouraged borrower.
To estimate the association between functional capacity, the multinomial logistic regression technique was used.
Softplus Multinomial logistic regression Dirichlet distribution - an alternative way to sample categorical distributions Smooth maximum.
Note, Predicted probabilities are based on a multinomial logistic regression model.
Softplus Multinomial logistic regression Dirichlet distribution - an alternative way to sample categorical distributions Partition function.
Note, Predicted probabilities are based on multinomial logistic regression models as above.
Table 7, Multinomial logistic regression estimates, four collateral casesa.
The variables included in the multivariate model of multinomial logistic regression are presented in Table 3.
Multinomial logistic regression analyses were performed on the data of the Aboriginal Peoples Survey of 2012.
Thereafter, a comparison of the 583 girls and 543 boys was performed by multinomial logistic regression analyzes.
Nominal ( with more than 2 levels ), Multinomial logistic regression.
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Results of the multinomial logistic regression
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