Graphical representation of the effects arising from the logistic mixed-effect mode fitted considering all significant predictors at once and accuracy achieved using numeric overlap to retrieve nearest neighbors as the dependent variable. 95% confidence bands are shown for each effect, and predictors are ordered according to how much they improve the model fit (first top-left, then top-right, bottom-left, and bottom-right.</p
Users of logistic regression models often need to describe the overall predictive strength, or effec...
This paper considers the role of covariates when using predicted probabilities to interpret main eff...
Due to the large data set, all factors are significant. However, we made an arbitrary cut-off at the...
Graphical representation of the effects arising from the logistic mixed-effect mode fitted consideri...
Graphical representation of the effects highlighted by the logistic mixed-effect models which includ...
Logistic mixed-effect model considering all predictors—Numeric overlap distance.</p
Effects of the logistic mixed-effect models which included a single predictor (inputted in the model...
<p>(i.e. Dnight or the linear intercept parameter respectively, if a diel pattern was or was not obs...
A well-established approach to modeling clustered data introduces random effects in the model of int...
Logistic mixed-effect models including all predictors (escluding function words).</p
Logistic mixed-effect models for single predictors (excluding function words).</p
We propose a Multivariate Logistic Distance (MLD) model for the analysis of multiple binary response...
Mixed-effect modeling is recommended for data with repeated measures, as often encountered in design...
Users of logistic regression models often need to describe the overall predictive strength, or effec...
In this paper we show that the recent notion of regression depth can be used as a data-analytic tool...
Users of logistic regression models often need to describe the overall predictive strength, or effec...
This paper considers the role of covariates when using predicted probabilities to interpret main eff...
Due to the large data set, all factors are significant. However, we made an arbitrary cut-off at the...
Graphical representation of the effects arising from the logistic mixed-effect mode fitted consideri...
Graphical representation of the effects highlighted by the logistic mixed-effect models which includ...
Logistic mixed-effect model considering all predictors—Numeric overlap distance.</p
Effects of the logistic mixed-effect models which included a single predictor (inputted in the model...
<p>(i.e. Dnight or the linear intercept parameter respectively, if a diel pattern was or was not obs...
A well-established approach to modeling clustered data introduces random effects in the model of int...
Logistic mixed-effect models including all predictors (escluding function words).</p
Logistic mixed-effect models for single predictors (excluding function words).</p
We propose a Multivariate Logistic Distance (MLD) model for the analysis of multiple binary response...
Mixed-effect modeling is recommended for data with repeated measures, as often encountered in design...
Users of logistic regression models often need to describe the overall predictive strength, or effec...
In this paper we show that the recent notion of regression depth can be used as a data-analytic tool...
Users of logistic regression models often need to describe the overall predictive strength, or effec...
This paper considers the role of covariates when using predicted probabilities to interpret main eff...
Due to the large data set, all factors are significant. However, we made an arbitrary cut-off at the...