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логит регрессия Portuguese
regressão logística Spanish
regresión logistica Catalan
regressió logística Synonyms
Examples for "logistic regression model"
Examples for "logistic regression model"
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Correlation between response and variables was analyzed using the logistic regression model.
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Association analyses were conducted applying Fisher's exact test and logistic regression model.
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A multivariable logistic regression model was used to identify factors associated with CKD.
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Analyses of efficacy were carried out with multilevel mixed effect logistic regression model.
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Genetic risk factors for suicidality were examined in a multinomial logistic regression model.
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Study design: This is a cross-sectional survey study using multivariate ordered logit regression models.
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A stepwise logit regression procedure was performed in order to determine the subset of measures which best distinguish ARMS subjects from HC.
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HIV stigma was not found to be a significant predictor when binary logit regression was run with medication adherence at 1 year.
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Our findings are tempered by a small sample size and lack of a direct relationship between stigma and adherence on binary logit regression analysis.
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A logit regression was used to estimate the association between hospital characteristics (bed size, location, teaching status, ownership) and having any hospital-affiliated cessation program.
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A multivariate logistic model was used to identify predictors of fetal complications.
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Conclusion: The logistic model that we developed meets high standards for discrimination and calibration.
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The propensity score was used as a covariate in a logistic model for mortality.
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The model is a modification of the Olson conditional logistic model for affected relative pairs.
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We developed a multivariable logistic model to identify factors associated with candidaemia in patients with candiduria.
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Polytomous logistic regression was used to compare each case group with controls.
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Multivariate logistic regression analysis was used to define risk factors for infection.
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Multivariable logistic regression was used to investigate risk factors associated with ADRs.
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Independent risk factors for early mortality were calculated using multivariate logistic regression.
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Multivariable logistic regression was used to examine factors related to HIV infection.
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Two multivariable logistic models were evaluated to predict the likelihood of PSMs.
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Multivariable three-level logistic models with random intercepts were run separately by sex.
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Multivariable logistic models were used after adjusting for potentially confounding factors.
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Strength of associations was assessed using odds ratios derived from conditional logistic models.
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Results: Five logistic models were fitted for the resistance to each of the antibiotic drugs.
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Attributes were analyzed by conditional logit model to determine significant predictors of patient preferences.
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A multinomial logit and a latent class logit model was used for the data analyses.
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The analysis relies on a conditional logit model to identify the relationship between price and brand choice.
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An ordered logit model was used to assess the relationship between sociodemographic factors and the number of DAREs performed.
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The probability of having a pregnancy complicated by pre-eclampsia was also calculated by means of a multivariate logit model.
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Multivariate analysis of these data, using the logit model, confirmed the association with both previous primary cancer and previous radiation.
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We take a new approach by phrasing the problem as a discrete choice, using a nested multinomial logit model for the analyses.
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Analyses were conducted using a mixed logit model, and the trade-offs between different attributes that patients were willing to accept were quantified.
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An ordered logit model will be used to regress an ordinal active play outcome on built environment exposure variables while adjusting for potential confounders.
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After adjustment for patient characteristics, the logit model showed that prescription patterns for antibiotic were quite similar and associated with a diagnosis of acute tonsillitis.
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From the DCE data, a conditional logit model was estimated to calculate total scores that took into account the relative importance of the seven domains.
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Multivariate logit models evaluated in-hospital mortality, complications, and prolonged length of stay.
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Multinomial and mixed logit models were used to model preferences within 4 subgroups.
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Analyses used gender-stratified hierarchical logit models to assess program participation and other potential predictors.
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Methods: Partial proportional odds logit models were developed for probabilities of being in GOLD stages II, III and IV.
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Mixed logit models were used for analysis and to predict the uptake of rural posts under different incentive combinations.