Usage of "logistic model"

ruso

логит регрессия

portugués

regressão logística

español

regresión logistica

catalán

regressió logística

Statistical model.

Related terms

regression analysis

regresión logistica

Sinónimos

Examples for "logistic regression model"

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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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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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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Usage of logistic model in inglés

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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We calculated prevalence ratios by fitting a logistic model and estimating predicted probabilities using marginal standardization. 
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A multiple logistic model was used to measure the factors influencing men's involvement in antenatal care services. 
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Variables associated with a high BU likelihood in a multivariate logistic model were included in the Buruli score. 
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However, this association was no longer found to be significant after adjusting for lifestyle factors in the logistic model. 
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Adjusted risks of conversion and severe postoperative morbidity after laparoscopic resection were computed, according to a multivariate regression logistic model. 
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The selected variables were assigned an integer or half-integer risk score proportional to the estimated coefficient from the logistic model. 
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ARS was developed based on the weighting scores of the parameters of all the predicted variables in the logistic model. 
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The effects of different elements of exposure to hardwood (duration, level, period) were studied in detail with a logistic model. 
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The logistic model linking cumulative AUC with ACR20 adequately characterized the time course of clinical improvement in patients with rheumatoid arthritis receiving etanercept. 
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Results: Convenient expressions for D 50,i and γ 50,i were provided for the Poisson and the logistic model. 
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Results: The multiple logistic model revealed that the risk of morbidity was increased by longer operation time, major hepatic resection, and preoperative cardiovascular disease. 
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