dose-response

Name: dose-response
Availability: InStock
Author: olatechie

Perform dose-response meta-analyses with GLS trend estimation and restricted cubic splines.

Updated Feb 23, 2026

Search Tags:#meta-analysis #gls #prisma-2020 #dose-response #restricted-cubic-splines #dosresmeta #two-stage-pooling

Ready to run

npx skills add https://github.com/olaTechie/scientific-paper-writer --skill dose-response

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: dose-response
Source: https://github.com/olaTechie/scientific-paper-writer/tree/main/skills/study-types/dose-response
Command: npx skills add https://github.com/olaTechie/scientific-paper-writer --skill dose-response

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

Dose-response meta-analyses are complex and require structured guidance to ensure correct modelling, transparent reporting, and reproducibility across studies.

Core Features & Use Cases

GLS-based trend estimation for summarized dose-response data across studies.
Restricted cubic spline modelling to capture non-linear dose-response shapes with pre-specified knot placement.
Two-stage pooling of study-specific curves with multivariate random-effects models.
PRISMA 2020-aligned reporting and ready-to-use guidelines for dose-response contexts.

Quick Start

Follow this model to generate a dose-response meta-analysis manuscript following PRISMA 2020 extensions.

Frequently Asked Questions about dose-response

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

FAQPage Schema

How do I perform a dose-response meta-analysis using restricted cubic splines?▼

Dose-response meta-analysis using restricted cubic splines models non-linear relationships across studies by placing pre-specified knots, capturing complex curves that linear models miss. This approach fits summarized data and estimates trends using GLS.

What is two-stage pooling for dose-response data?▼

Two-stage pooling for dose-response data first estimates study-specific curves independently, then combines them using multivariate random-effects models. This method accounts for within- and between-study variance, yielding a pooled non-linear dose-response curve.

How do I report a dose-response meta-analysis to meet PRISMA 2020 guidelines?▼

To report a dose-response meta-analysis meeting PRISMA 2020 guidelines, document GLS trend estimation, spline knot placement, and pooling methods transparently. Include sensitivity analyses and follow structured reporting extensions for reproducibility.

When should I use GLS trend estimation for summarized dose-response data?▼

Use GLS trend estimation for summarized dose-response data when modeling trends across multiple studies with correlated estimates. It applies generalized least squares to account for within-study covariance, providing robust slope estimates for pooling.

Can I use dosresmeta for multivariate random-effects pooling in non-linear models?▼

Yes, you can use dosresmeta for multivariate random-effects pooling in non-linear models. It facilitates two-stage pooling of study-specific restricted cubic spline curves, combining them while accounting for heterogeneity across systematic reviews.

What are the limitations of restricted cubic splines in dose-response meta-analysis?▼

Limitations of restricted cubic splines in dose-response meta-analysis include sensitivity to knot placement and potential overfitting with sparse data. If dose ranges vary drastically across studies, accurately estimating non-linear shapes becomes difficult.