Analysis
REGRESSION
Analysis included all participants with available DNAm data at trial baseline and at least one follow-up timepoint.We computed change scores for all aging measures by comparing values at the 12-month and 24-month follow-up assessments with baseline values (that is, 12-month change = 12-month value − baseline; 24-month change = 24-month value − baseline). We conducted analyses of these change scores to test the hypothesis that CR slows biological aging using two complementary approaches: (1) we conducted ITT analysis which compared change scores between participants randomized to CR intervention and the AL control group; (2) we conducted TOT analysis using IV methods to estimate the effect of CR on change scores.In ITT analysis, we tested the effect of randomization to CR versus AL on aging measure change scores using repeated-measures ANCOVA implemented under mixed models, following the approach used in past CALERIE analysisIn TOT analysis, we tested the effect of the CR intervention on aging measure change scores using IV regression implemented using a two-stage least squares approachIn ITT and TOT analyses, effect sizes were scaled in standardized units according to the distribution of the aging measures at pretreatment baseline. For the DNAm clocks, clock ages were differenced from chronological ages and standard deviations for these age-difference values were used for scaling. For DunedinPACE, the standard deviations of the original values were used for scaling. Treatment effects denominated in these standardized units are interpreted as Cohen’s 