Examples of using Logistic regression in English and their translations into French
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Logistic Regression This non-linear form of regression model is preferred when the dependent variable is a probability(P)
Analysis: Binary logistic regression Discussion: Smyth et al.(2009)
This variable is entered into a logistic regression of perceived discrimination to estimate the correlation between the individual characteristic of being exposed to unemployment,
I have used python to do the logistic regression using functions from the scikit-learn package.
their corresponding 95% CIs were always compared to ascertain the magnitude of differences identified as statistically significant through logistic regression.
These results suggest that the logistic regression models for Vallisneria are very good for all sectors of the river,
Applied Logistic Regression,(now in its 3 rd edition), Applied Survival Analysis(now
A similar logistic regression model as the one carried out for whether
In the last part, we will use logistic regression models to verify whether all these identified factors stand up to analysis with“all other things being equal”.
Logistic regression analyses were used to examine how the probabilities of birds being caught varied with factors associated with fishing tactics,
As a first approach, the logistic regression models were estimated using all of the variables,
Use of this model with the models that use logistic regression improves the performance of the models by approximately 20%,
Using data from Ontario to conduct a logistic regression analysis, the study found that teaching hospitals were 60% more likely to convert potential donors into actual donors than community hospitals.
Factors Associated With Conversion A hierarchical logistic regression(main fixed effects model without random effects)
If p is the probability from a logistic regression model corresponding only to the effect of the dose and if m is natural mortality,
a number of factors assessed in the logistic regression analysis.
binary logistic regression model, multinomial logistic regression model and linear regression model.
are estimated by logistic regression(see text)
His book Regression Modeling Strategies with Applications to Linear Models, Logistic Regression, and Survival Analysis(2001, Springer-Verlag) contains theory, examples,
To determine a statistically significant relationship between two variables: logistic regression was used for binary dependent variables; ordinal regression was used for ordered