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multivariable adjusted regression models  (STATA Corporation)


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    STATA Corporation multivariable adjusted regression models
    Fig. 3. Comparison of the <t>multivariable</t> linear regression between dihydrocaffeic acid and plasma glucose adjusted for (A): age, sex, smoking habit, educational level, BMI, physical activity, total energy intake, and hypercholesterolemia; and (B) further adjusted for the use of antidiabetic drugs.
    Multivariable Adjusted Regression Models, supplied by STATA Corporation, used in various techniques. Bioz Stars score: 99/100, based on 32737 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
    https://www.bioz.com/result/multivariable adjusted regression models/product/STATA Corporation
    Average 99 stars, based on 32737 article reviews
    multivariable adjusted regression models - by Bioz Stars, 2026-04
    99/100 stars

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    1) Product Images from "Urinary metabolomics of phenolic compounds reveals biomarkers of type-2 diabetes within the PREDIMED trial."

    Article Title: Urinary metabolomics of phenolic compounds reveals biomarkers of type-2 diabetes within the PREDIMED trial.

    Journal: Biomedicine & pharmacotherapy = Biomedecine & pharmacotherapie

    doi: 10.1016/j.biopha.2023.114703

    Fig. 3. Comparison of the multivariable linear regression between dihydrocaffeic acid and plasma glucose adjusted for (A): age, sex, smoking habit, educational level, BMI, physical activity, total energy intake, and hypercholesterolemia; and (B) further adjusted for the use of antidiabetic drugs.
    Figure Legend Snippet: Fig. 3. Comparison of the multivariable linear regression between dihydrocaffeic acid and plasma glucose adjusted for (A): age, sex, smoking habit, educational level, BMI, physical activity, total energy intake, and hypercholesterolemia; and (B) further adjusted for the use of antidiabetic drugs.

    Techniques Used: Comparison, Clinical Proteomics, Activity Assay



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    Fig. 3. Comparison of the <t>multivariable</t> linear regression between dihydrocaffeic acid and plasma glucose adjusted for (A): age, sex, smoking habit, educational level, BMI, physical activity, total energy intake, and hypercholesterolemia; and (B) further adjusted for the use of antidiabetic drugs.
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    Fig. 3. Comparison of the <t>multivariable</t> linear regression between dihydrocaffeic acid and plasma glucose adjusted for (A): age, sex, smoking habit, educational level, BMI, physical activity, total energy intake, and hypercholesterolemia; and (B) further adjusted for the use of antidiabetic drugs.
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    multivariable adjusted regression model  (STATA Corporation)
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    STATA Corporation multivariable adjusted regression model
    Fig. 3. Comparison of the <t>multivariable</t> linear regression between dihydrocaffeic acid and plasma glucose adjusted for (A): age, sex, smoking habit, educational level, BMI, physical activity, total energy intake, and hypercholesterolemia; and (B) further adjusted for the use of antidiabetic drugs.
    Multivariable Adjusted Regression Model, supplied by STATA Corporation, used in various techniques. Bioz Stars score: 99/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
    https://www.bioz.com/result/multivariable adjusted regression model/product/STATA Corporation
    Average 99 stars, based on 1 article reviews
    multivariable adjusted regression model - by Bioz Stars, 2026-04
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    Fig. 3. Comparison of the multivariable linear regression between dihydrocaffeic acid and plasma glucose adjusted for (A): age, sex, smoking habit, educational level, BMI, physical activity, total energy intake, and hypercholesterolemia; and (B) further adjusted for the use of antidiabetic drugs.

    Journal: Biomedicine & pharmacotherapy = Biomedecine & pharmacotherapie

    Article Title: Urinary metabolomics of phenolic compounds reveals biomarkers of type-2 diabetes within the PREDIMED trial.

    doi: 10.1016/j.biopha.2023.114703

    Figure Lengend Snippet: Fig. 3. Comparison of the multivariable linear regression between dihydrocaffeic acid and plasma glucose adjusted for (A): age, sex, smoking habit, educational level, BMI, physical activity, total energy intake, and hypercholesterolemia; and (B) further adjusted for the use of antidiabetic drugs.

    Article Snippet: Logistic and multivariable adjusted regression models were generated using Stata 16.0.

    Techniques: Comparison, Clinical Proteomics, Activity Assay