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RStudio software r studio version 4.2.3
Software R Studio Version 4.2.3, supplied by RStudio, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/product/r+studio+4%2E2%2E3+software/rstudio+version+1+3+1093/10__1016_slash_j__jfoodeng__2024__112442-102-26-9
Average 90 stars, based on 1 article reviews
software r studio version 4.2.3 - by Bioz Stars, 2026-10
90/100 stars

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Software:

Article Title: Association between dietary vitamin A intake and risk of cardiometabolic multimorbidity.
Article Snippet: Missing covariates were imputed using the MICE package in R Studio 4.2.3 software26, employing the Predictive Mean Matching (PMM) imputation method with five iterations to generate datasets for education (0.9%), individual income level (4.8%), body mass index (0.3%), and physical activity (0.3%).


Article Title: Association between dietary vitamin A intake and risk of cardiometabolic multimorbidity
Article Snippet: Missing covariates were imputed using the MICE package in R Studio 4.2.3 software , employing the Predictive Mean Matching (PMM) imputation method with five iterations to generate datasets for education (0.9%), individual income level (4.8%), body mass index (0.3%), and physical activity (0.3%).


Activity Assay:

Article Title: Association between dietary vitamin A intake and risk of cardiometabolic multimorbidity.
Article Snippet: Missing covariates were imputed using the MICE package in R Studio 4.2.3 software26, employing the Predictive Mean Matching (PMM) imputation method with five iterations to generate datasets for education (0.9%), individual income level (4.8%), body mass index (0.3%), and physical activity (0.3%).


Article Title: Association between dietary vitamin A intake and risk of cardiometabolic multimorbidity
Article Snippet: Missing covariates were imputed using the MICE package in R Studio 4.2.3 software , employing the Predictive Mean Matching (PMM) imputation method with five iterations to generate datasets for education (0.9%), individual income level (4.8%), body mass index (0.3%), and physical activity (0.3%).




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