◍wovepaper
SearchResearchersInstitutions
Sign in
researcher

Richard D Riley

3 papers here

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • middle author3

Across the 3 of 3 papers where every author was matched, so the position is known.

fields
  • stat.ME3
ORCID 0000-0001-8699-0735

identity via Semantic Scholar / OpenAlex

activity
20222024
most citedMinimum Sample Size for Developing a Multivariable Prediction Model using Multinomial Logistic Regression

11 citations · 12 across the 3 of their papers we have counts for

collaborators

3 papers

stat.ME2024★ 1 cited

Extended sample size calculations for evaluation of prediction models using a threshold for classification

Rebecca Whittle, Joie Ensor, Lucinda Archer +10

When evaluating the performance of a model for individualised risk prediction, the sample size needs to be large enough to precisely estimate the performance measures of interest.…

stat.ME2023

Calibration plots for multistate risk predictions models: an overview and simulation comparing novel approaches

Alexander Pate, Matthew Sperrin, Richard D. Riley +9

Introduction. There is currently no guidance on how to assess the calibration of multistate models used for risk prediction. We introduce several techniques that can be used to pro…

stat.ME2022★ 11 cited

Minimum Sample Size for Developing a Multivariable Prediction Model using Multinomial Logistic Regression

Alexander Pate, Richard D Riley, Gary S Collins +4

Multinomial logistic regression models allow one to predict the risk of a categorical outcome with more than 2 categories. When developing such a model, researchers should ensure t…

◍wovepaper

Papers, researchers and institutions, woven together.

Explore
  • Search
  • Researchers
  • Institutions
Account
  • Library
  • Chat
Data
  • arXiv.org
  • Semantic Scholar
  • OpenAlex
  • Latest RSS
AboutContactPrivacyDevelopersllms.txtopenapi.json
Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.