MLRA

(redirected from Multiple Logistic Regression Analysis)
AcronymDefinition
MLRAMajor Land Resource Area (USDA NRCS)
MLRAMultiple Linear Regression Analysis
MLRAMidwest Late Model Racing Association
MLRAMarine Living Resources Act of 1998 (South Africa)
MLRAMultiple Logistic Regression Analysis
MLRAMulti-layer Routing Area
References in periodicals archive ?
However, in multiple logistic regression analysis, no relationship was determined between admittance to ICU and depression (p=0.
Multiple logistic regression analysis to detect predictors of GERD in JHM patients revealed that patients with high total mobility score (7-9) had the highest risk for developing GERD [about 41 fold compared to those with normal mobility score (<4), p model <0.
Multiple logistic regression analysis and final model: Multiple logistic regression analysis demonstrated four final independent variables: FC, number of previous relapses (NPR), age, and Seo index were significantly associated with relapse.
The results of our multiple logistic regression analysis (Table 4) showed that patients with higher BMI, higher HbA1c at prediabetes diagnosis, and TRG > 250 mg/dL had statistically significant higher odds of being initiated on metformin therapy.
Multiple logistic regression analysis was performed on the relationships between the subjective symptoms and the different living environments.
Table 1 shows the odds ratios and 95% confidential intervals of each independent factor related to death among Sumo wrestlers using a multiple logistic regression analysis.
Multiple logistic regression analysis (Method: Backward-Wald; Hosmer & Lemeshow, 2000) was performed for the factors with p values of less than 0.
Predictors of blood pressure control were assessed using multiple logistic regression analysis.
In multiple logistic regression analysis, older age, longer diabetes duration, central adiposity, increasing height, higher fasting plasma glucose levels, higher systolic blood pressure, higher urinary albumin-to-creatinine ratios, and indigenous racial background were all independently associated with prevalent peripheral neuropathy.
The multiple logistic regression analysis was used for determining the correlation between the serum potassium and the patients' characteristics.
A forward, stepwise multiple logistic regression analysis was performed to determine the variables which best predicted employment status.
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