Core B: Analytics Core

ANALYTICS CORE SUMMARY The Analytics Core will support all four research components of the TIME-AD program, ensuring coordinated statistical approaches and principled decisions on common challenges. The Analytics Core will (1) work with the Cognition, Exposure, and Covariates Core to ensure construction of analytic data sets is consistent with

each proposed study design for each research project; (2) partner with research project leads to develop and implement the analytic strategy for each research project, develop template analysis code for each method, and lead program-wide methodologic decisions; (3) guide investigative teams in each research project on

systematic evidence triangulation across study designs; (4) and provide ad hoc guidance on statistical problems that arise in each research project. The TIME-AD program proposes to implement combinations of multiple analyses of AD/ADRD risk factors, relying on different assumptions for causal identification. Methods

include doubly robust g-estimation methods using covariate adjustment; instrumental variables analyses drawing on policy or genetic instruments; bias-detecting Mendelian Randomization; and quantitative bias analysis. These approaches will be complemented by methods to quantify the total effect of interventions on

each risk factor on population incidence of AD/ADRD and inequalities in AD/ADRD. Population impact assessments will include population attributable fraction calculations and effect estimate transport methods that allow estimation of total effects in populations with different risk factor profiles. The team includes

researchers with expertise in each of these methods. The TIME-AD program uses data from multiple sources, including population-representative cohorts with regularly scheduled measurement waves (Health and Retirement Study, National Longitudinal Study of Youth 1979, Reasons for Geographic and Racial Disparities

in Stroke, National Health and Aging Trends Study) and cohorts relying on convenience (UK Biobank, All of US) or membership-based (Kaiser Permanente Northern California) based samples with electronic health record follow-ups. Together these data sets provide excellent statistical power to deliver precise estimates and

evaluate effects in racial/ethnic and socioeconomic subgroups. The different data sources best support different study designs, and each entails specific methodologic challenges. The Analytics Core will ensure a unified framework, foster reproducible research and high-quality implementation, and make it feasible to tackle

these multiple designs with multiple data sets in each study. The Analytics Core will also work closely with the Equity and Dissemination Core to ensure analytic decisions reflect the TIME-AD goal of delivering evidence with the best chance to reduce AD/ADRD inequities and identify drivers of AD/ADRD in communities

historically underrepresented in AD/ADRD research. The Analytics Core will guarantee integration of the projects and ensure success of the TIME-AD program.