stc-methodology

Applies STC methodology to adjust IPD and AgD covariate differences in ITC analyses.

Updated Dec 8, 2025

Search Tags:#ipd #indirect-comparison #stc #covariate-centering #effect-modifiers #bayesian-analysis #dsu-guidance

Ready to run

npx skills add https://github.com/choxos/ITC-agents --skill stc-methodology

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Please help me install this Agent Skill.
Skill: stc-methodology
Source: https://github.com/choxos/ITC-agents/tree/main/plugins/itc-modelling/skills/stc-methodology
Command: npx skills add https://github.com/choxos/ITC-agents --skill stc-methodology

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

STC methodology provides a structured approach to transport trial results across populations by adjusting IPD-based estimates for differences in covariates with aggregate data, enabling valid indirect comparisons in ITC analyses.

Core Features & Use Cases

Guidance on choosing between anchored and unanchored STC and when to use each approach
Support for effect modifier identification, covariate centering, and interpretation of treatment effects at external population values
Instructions for both frequentist and Bayesian STC implementations, including model diagnostics and reporting
Use Case: Apply STC to compare treatments across trials with different covariate distributions while documenting assumptions and sensitivity analyses

Quick Start

Run an anchored STC analysis with IPD and aggregate-data covariates to estimate the external-population treatment effect.

Frequently Asked Questions about stc-methodology

High-intent search queries and answers about installing and using this skill.

FAQPage Schema

What is STC methodology and when should I use it for indirect treatment comparisons?▼

STC methodology transports trial results across populations by adjusting IPD-based estimates for covariate differences with aggregate data. It is needed when comparing treatments across trials with different covariate distributions in ITC analyses.

How do I decide between anchored and unanchored STC for an indirect comparison?▼

Choosing between anchored and unanchored STC depends on whether a common comparator exists across trials. Anchored STC uses linked treatment networks, while unanchored STC transports effects without a common comparator across populations.

How do I select effect modifiers and center covariates in a Bayesian STC analysis?▼

Select effect modifiers based on clinical relevance and statistical significance, then center covariates at external population values to estimate treatment effects. Bayesian STC implementation requires clear model specification and appropriate covariate centering.

Does STC methodology align with NICE DSU guidance for indirect comparisons?▼

STC methodology aligns with NICE DSU guidance by requiring clear model specification, appropriate covariate centering, documentation of all assumptions, and sensitivity analyses. This ensures valid indirect comparisons between IPD and aggregate data.

Can I run both frequentist and Bayesian STC implementations for population-adjusted indirect comparisons?▼

Both frequentist and Bayesian STC implementations are supported for population-adjusted indirect comparisons. They include model diagnostics and reporting instructions to estimate external-population treatment effects from IPD and aggregate-data covariates.