Amardeep Legha
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View article: A decomposition of Fisher’s information to inform sample size for developing or updating fair and precise clinical prediction models — part 2: time-to-event outcomes
A decomposition of Fisher’s information to inform sample size for developing or updating fair and precise clinical prediction models — part 2: time-to-event outcomes Open
Background When developing a clinical prediction model using time-to-event data (i.e. with censoring and different lengths of follow-up), previous research focuses on the sample size needed to minimise overfitting and precisely estimating …
View article: Sequential sample size calculations and learning curves safeguard the robust development of a clinical prediction model for individuals
Sequential sample size calculations and learning curves safeguard the robust development of a clinical prediction model for individuals Open
View article: Trajectories of Work Absence in England due to a Musculoskeletal or Mental Health Condition: An Electronic Health Record Cohort Study
Trajectories of Work Absence in England due to a Musculoskeletal or Mental Health Condition: An Electronic Health Record Cohort Study Open
Purpose To derive common patterns (trajectories) of work absence over time due to a musculoskeletal (MSK) or mental health (MH) condition in an English population and determine associations of these absence trajectories with health and soc…
View article: Sequential sample size calculations and learning curves safeguard the robust development of a clinical prediction model for individuals
Sequential sample size calculations and learning curves safeguard the robust development of a clinical prediction model for individuals Open
When prospectively developing a new clinical prediction model (CPM), fixed sample size calculations are typically conducted before data collection based on sensible assumptions. But if the assumptions are inaccurate the actual sample size …
View article: A decomposition of Fisher's information to inform sample size for developing or updating fair and precise clinical prediction models -- Part 3: continuous outcomes
A decomposition of Fisher's information to inform sample size for developing or updating fair and precise clinical prediction models -- Part 3: continuous outcomes Open
Clinical prediction models enable healthcare professionals to estimate individual outcomes using patient characteristics. Current sample size guidelines for developing or updating models with continuous outcomes aim to minimise overfitting…
View article: A decomposition of Fisher’s information to inform sample size for developing or updating fair and precise clinical prediction models for individual risk—part 1: binary outcomes
A decomposition of Fisher’s information to inform sample size for developing or updating fair and precise clinical prediction models for individual risk—part 1: binary outcomes Open
View article: Extended sample size calculations for evaluation of prediction models using a threshold for classification
Extended sample size calculations for evaluation of prediction models using a threshold for classification Open
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. Current sample size guidance is based on precisely estimati…
View article: Trajectories of work absence in England due to a musculoskeletal or mental health condition: an electronic health record cohort study
Trajectories of work absence in England due to a musculoskeletal or mental health condition: an electronic health record cohort study Open
Purpose To derive common patterns (trajectories) of work absence over time due to a musculoskeletal (MSK) or mental health (MH) condition in an English population and determine associations of these absence trajectories with health and soc…
View article: A decomposition of Fisher's information to inform sample size for developing fair and precise clinical prediction models -- Part 2: time-to-event outcomes
A decomposition of Fisher's information to inform sample size for developing fair and precise clinical prediction models -- Part 2: time-to-event outcomes Open
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 overall risk. However, instability of individual-level risk e…
View article: A decomposition of Fisher's information to inform sample size for developing fair and precise clinical prediction models -- part 1: binary outcomes
A decomposition of Fisher's information to inform sample size for developing fair and precise clinical prediction models -- part 1: binary outcomes Open
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, instability, poor performance and lack of fairness. Previous resear…
View article: Extended sample size calculations for evaluation of prediction models using a threshold for classification
Extended sample size calculations for evaluation of prediction models using a threshold for classification Open
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. Current sample size guidance is based on precisely estimati…
View article: Prognostic Factors and Models for Predicting Work Absence in Adults with Musculoskeletal Conditions Consulting a Healthcare Practitioner: A Systematic Review
Prognostic Factors and Models for Predicting Work Absence in Adults with Musculoskeletal Conditions Consulting a Healthcare Practitioner: A Systematic Review Open
View article: Moderators of the effect of therapeutic exercise for knee and hip osteoarthritis: a systematic review and individual participant data meta-analysis
Moderators of the effect of therapeutic exercise for knee and hip osteoarthritis: a systematic review and individual participant data meta-analysis Open
Chartered Society of Physiotherapy Charitable Trust and the National Institute for Health and Care Research.
View article: One‐stage individual participant data meta‐analysis models for continuous and binary outcomes: Comparison of treatment coding options and estimation methods
One‐stage individual participant data meta‐analysis models for continuous and binary outcomes: Comparison of treatment coding options and estimation methods Open
A one‐stage individual participant data (IPD) meta‐analysis synthesizes IPD from multiple studies using a general or generalized linear mixed model. This produces summary results (eg, about treatment effect) in a single step, whilst accoun…
View article: Individual participant data meta‐analysis of continuous outcomes: A comparison of approaches for specifying and estimating one‐stage models
Individual participant data meta‐analysis of continuous outcomes: A comparison of approaches for specifying and estimating one‐stage models Open
One‐stage individual participant data meta‐analysis models should account for within‐trial clustering, but it is currently debated how to do this. For continuous outcomes modeled using a linear regression framework, two competing approache…
View article: Comparative effectiveness of treatment options for plantar heel pain: a systematic review with network meta-analysis
Comparative effectiveness of treatment options for plantar heel pain: a systematic review with network meta-analysis Open
Objective To evaluate the comparative effectiveness of current treatment options for plantar heel pain (PHP). Design Systematic review and network meta-analysis (NMA). Data sources Medline, EMBASE, CINAHL, AMED, PEDro, Cochrane Database, W…
View article: Subgrouping and TargetEd Exercise pRogrammes for knee and hip OsteoArthritis (STEER OA): a systematic review update and individual participant data meta-analysis protocol
Subgrouping and TargetEd Exercise pRogrammes for knee and hip OsteoArthritis (STEER OA): a systematic review update and individual participant data meta-analysis protocol Open
Introduction Knee and hip osteoarthritis (OA) is a leading cause of disability worldwide. Therapeutic exercise is a recommended core treatment for people with knee and hip OA, however, the observed effect sizes for reducing pain and improv…