*<p>p = ≤0.05.</p>**<p>p = ≤0.01.</p>***<p>p = ≤0.001.</p>1<p>Akaike Information Criterion.</p
<p>Selection of factors was based on Akaike Information Criterion (AIC) and statistical significance...
The Akaike information criterion (AIC) has been successfully used in the liter-ature in model select...
<p>Univariate and multivariate logistic regression analysis of the risk of having an Agatston score ...
*<p>p = ≤0.05.</p>**<p>p = ≤0.01.</p>***<p>p = ≤0.001.</p>1<p>Akaike Information Criterion.</p
<p>Akaike information criterion and log-likelihood values for the analysed variables.</p
*<p>p = ≤0.05.</p>**<p>p = ≤0.01.</p>***<p>p = ≤0.001.</p>1<p>Akaike Information Criterion.</p
<p>Univariate logistic regression analysis for the criterion “self-testing” and each single predicto...
Akaike information criteria (AIC) for multivariate regression and multiple linear regression models ...
<p>Logistic Regression Analysis of correlates of detectable viremia>50 copies/mL at T0, multivariabl...
Multivariate logistic regression to assess factors associated with trust in the information source.<...
In biostatistical practice, it is common to use information criteria as a guide for model selection....
<p>Multivariate logistic regression analysis of different parameters in the study subjects.</p
In biostatistical practice, it is common to use information criteria as a guide for model selection....
Bivariable and multivariable logistic regression analysis showing predictors of knowledge levels.</p
<p>Table of Akaike Information Criterion (AIC) and Adjusted R<sup>2</sup> values for the different p...
<p>Selection of factors was based on Akaike Information Criterion (AIC) and statistical significance...
The Akaike information criterion (AIC) has been successfully used in the liter-ature in model select...
<p>Univariate and multivariate logistic regression analysis of the risk of having an Agatston score ...
*<p>p = ≤0.05.</p>**<p>p = ≤0.01.</p>***<p>p = ≤0.001.</p>1<p>Akaike Information Criterion.</p
<p>Akaike information criterion and log-likelihood values for the analysed variables.</p
*<p>p = ≤0.05.</p>**<p>p = ≤0.01.</p>***<p>p = ≤0.001.</p>1<p>Akaike Information Criterion.</p
<p>Univariate logistic regression analysis for the criterion “self-testing” and each single predicto...
Akaike information criteria (AIC) for multivariate regression and multiple linear regression models ...
<p>Logistic Regression Analysis of correlates of detectable viremia>50 copies/mL at T0, multivariabl...
Multivariate logistic regression to assess factors associated with trust in the information source.<...
In biostatistical practice, it is common to use information criteria as a guide for model selection....
<p>Multivariate logistic regression analysis of different parameters in the study subjects.</p
In biostatistical practice, it is common to use information criteria as a guide for model selection....
Bivariable and multivariable logistic regression analysis showing predictors of knowledge levels.</p
<p>Table of Akaike Information Criterion (AIC) and Adjusted R<sup>2</sup> values for the different p...
<p>Selection of factors was based on Akaike Information Criterion (AIC) and statistical significance...
The Akaike information criterion (AIC) has been successfully used in the liter-ature in model select...
<p>Univariate and multivariate logistic regression analysis of the risk of having an Agatston score ...
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