table_surv: table_surv

In dayoonkwon/BioAge: Biological Age Calculations Using Several Biomarker Algorithms

table_surv

Description

Associations of biological aging measures with mortality.

Usage

table_surv(data, agevar, label)

Arguments

data	A dataset with projected biological aging measures for analysis.
agevar	A character vector indicating the names of the biological aging measures.
label	A character vector indicating the labels of the biological aging measures.

Details

BioAge coefficients in the table are hazard ratios estimated from Cox proportional hazard regressions. KDM Biological Age and Levine Phenotypic Age measures were differenced from chronological age for analysis (i.e. values = BA-CA). These differenced values were then standardized to have M=0, SD=1 separately for men and women within the analysis sample so that effect-sizes are denominated in terms of a sex-specific 1 SD unit increase in biological age advancement. Models included covariates for chronological age and sex.

Note

Chronological age, gender, and race/ethnicity variables need to be named "age", "gender", and "race".

Examples

table1 = table_surv(data,
                    agevar = c("kdm_advance0","phenoage_advance0",
                               "kdm_advance","phenoage_advance",
                               "hd","hd_log"),
                    label = c("KDM\nBiological Age\nAdvancement",
                    "Levine\nPhenotypic Age\nAdvancement",
                    "Modified-KDM\nBiological Age\nAdvancement",
                    "Modified-Levine\nPhenotypic Age\nAdvancement",
                    "Homeostatic\nDysregulation",
                    "Log\nHomeostatic\nDysregulation"))

table1

dayoonkwon/BioAge documentation built on Oct. 11, 2023, 1:33 a.m.