11 citations · 15 across the 6 of their papers we have counts for
7 papers
Sequential sample size calculations and learning curves safeguard the robust development of a clinical prediction model for individuals
Amardeep Legha, Joie Ensor, Rebecca Whittle +7
When prospectively developing a new clinical prediction model (CPM), fixed sample size calculations are typically conducted before data collection based on sensible assumptions. Bu…
A decomposition of Fisher's information to inform sample size for developing or updating fair and precise clinical prediction models -- Part 3: continuous outcomes
Rebecca Whittle, Richard D Riley, Lucinda Archer +4
Clinical prediction models enable healthcare professionals to estimate individual outcomes using patient characteristics. Current sample size guidelines for developing or updating…
A general sample size framework for developing or updating a clinical prediction model
Richard D Riley, Rebecca Whittle, Mohsen Sadatsafavi +4
Aims: To propose a general sample size framework for developing or updating a clinical prediction model using any statistical or machine learning method, based on drawing samples f…
A decomposition of Fisher's information to inform sample size for developing fair and precise clinical prediction models -- Part 2: time-to-event outcomes
Richard D Riley, Gary S Collins, Lucinda Archer +9
Background: When developing a clinical prediction model using time-to-event data, previous research focuses on the sample size to minimise overfitting and precisely estimate the ov…
A decomposition of Fisher's information to inform sample size for developing fair and precise clinical prediction models -- part 1: binary outcomes
Richard D Riley, Gary S Collins, Rebecca Whittle +11
When developing a clinical prediction model, the sample size of the development dataset is a key consideration. Small sample sizes lead to greater concerns of overfitting, instabil…
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.…
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…