Exemple de utilizare a Logistic regression în Engleză și traducerile lor în Română
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Logistic regression models.
Based on a logistic regression.
A- Logistic regression model adjusted for randomisation stratification variables.
A values presented for GIOTRIF vs. erlotinib,p-value based on logistic regression.
The analysis was performed using a logistic regression model with treatment as the only factor.
In the next video we will start working out the details of the logistic regression algorithm.
A Primary endpoint from logistic regression adjusted for loading dose and patient status.
Odds ratio(lipegfilgrastim/ placebo), CI andp-value out of multivariate logistic regression analysis.
Logistic regression revealed a statistically significant association between nintedanib exposure and DCE-MRI response.
The focus is on t tests, ANOVA, and linear regression, andincludes a brief introduction to logistic regression.
Logistic regression revealed a statistically significant association of the anti-angiogenic effect to nintedanib exposure.
Wald p-values are quoted for the comparison of treatments using logistic regression with factors for treatment and region.
Logistic Regression is actually a classification algorithm that we apply to settings where the label Y is discreet valued.
AODE Bayesian spam filtering Bayesian network Random naive Bayes Linear classifier Logistic regression Perceptron Take-the-best heuristic.
In this case,Blumenstock used logistic regression, but he could have used a variety of other statistical or machine learning approaches.
Confidence interval around observed difference of response rates; P-value< 0.0001 from logistic regression model, including stratification factors.
We will develop an algorithm called logistic regression, which is one of the most popular and most widely used learning algorithms today.
Actinic keratosis lesions were cleared. c Median percent(%) reduction in actinic keratosis lesions compared to baseline. d p< 0.001;compared to vehicle by logistic regression with treatment, study and anatomical location.
The results of the logistic regression model of the relationship between the lots of independent variables and a dichotomous dependent variable(Table 2).
(2010) machine learning model were more complex than those in mytoy example- for example, she used features like“de Vaucouleurs fit axial ratio”- and her model was not logistic regression, it was an artificial neural network.
Odds ratio and p-value were obtained from a logistic regression model adjusted for baseline ECOG Performance Score(0 versus 1).
The features in Banerji and colleagues' machine learning model were more complex than those in my toy example- for example, she used features like“de Vaucouleurs fit axial ratio”- andher model was not logistic regression, it was an artificial neural network.
A values presented for GIOTRIF vs. chemotherapy,p-value based on logistic regression b p-value for time to deterioration based on stratified log-rank test.
In adition, binary logistic regression analysis(LR) showed that FENO can not be used as a reliable biomarker(p=0.169) for the estimation of the risk for obstructive dysfunction.
The presence of the combination of perinatal factors(prenatal ultrasound abnormalities) and some postnatal factors(initial EEG abnormalities, presence of status epilepticus inclinical manifestation of stroke) reports a logistic regression coeffi cients(2.861, 2.909, 3.377) which indicates a strong link between these factors.
In this case,Blumenstock used logistic regression with 10-fold cross-validation, but he could have used a variety of other statistical or machine learning approaches.
IMP24011: p-values compared efalizumab with placebo using logistic regression including baseline PASI score, prior treatment for psoriasis and geographical region as covariates.
Logistic regression modelling of the predictive value for genotype(adjusted for baseline plasma HIV-1RNA[vRNA], CD4+ cell count, number and duration of prior antiretroviral therapies) showed that the presence of 3 or more NRTI resistance-associated mutations was associated with reduced response at Week 4(p=0.015) or 4 or more mutations at median Week 24(p0.012).
So, I already ran a multivariable logistic regression analysis, and we can go a long way towards closing the gap on the risk level if Melissa loses 10% to 15% of her weight.
The object of this logistic regression analysis of various independent variables is to obtain a biologically reasonable answer to describe the binary(two) characteristics in question: credibility or deception.