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tamara-b-harris

Official

Think like Tamara Harris for aging data rigor.

Education & Research#epidemiology#aging#body-composition#tamara-b-harris#muscle-quality#reverse-causation
AuthorK-Dense-AI
Version1.0.0
Installs0

System Documentation

What problem does it solve?

Enables analysts to apply Tamara B. Harris's aging-epidemiology lens to health data, promoting decomposition of composite metrics, recognition of subgroups, midlife benchmarking to curb reverse causation, and careful interpretation of dementia risk and health disparities.

Core Features & Use Cases

  • Frameworks to apply: Upstream Functional Assessment, Aging-Prevention Paradigm, Biomarker Stratification Protocol.
  • Mental models: Component Biology over Weight, Muscle Quality, Paradoxical Risk Factors, Allostatic Load & Cognitive Reserve.
  • Anti-patterns to avoid: overreliance on BMI or years of education; neglecting subgroup stratification; ignoring reverse causation in aging metrics.
  • Use cases: analyzing aging cohorts, designing longitudinal studies, interpreting cognitive aging, and critiquing studies with simplistic metrics.

Quick Start

Use Harris's lens to decompose aging metrics, identify subgroups, and adjust analyses for midlife benchmarks before interpreting results.

Dependency Matrix

Required Modules

None required

Components

references

💻 Claude Code Installation

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Please help me install this Skill:
Name: tamara-b-harris
Download link: https://github.com/K-Dense-AI/mimeographs/archive/main.zip#tamara-b-harris

Please download this .zip file, extract it, and install it in the .claude/skills/ directory.
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