Search Results - "Riley, Richard D."

Random effects meta‐analysis: Coverage performance of 95% confidence and prediction intervals following REML estimation by Partlett, Christopher, Riley, Richard D.

“…A random effects meta‐analysis combines the results of several independent studies to summarise the evidence about a particular measure of interest, such as a…”
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PROBAST: A Tool to Assess Risk of Bias and Applicability of Prediction Model Studies: Explanation and Elaboration by Moons, Karel G M, Wolff, Robert F, Riley, Richard D, Whiting, Penny F, Westwood, Marie, Collins, Gary S, Reitsma, Johannes B, Kleijnen, Jos, Mallett, Sue

“…Prediction models in health care use predictors to estimate for an individual the probability that a condition or disease is already present (diagnostic model)…”
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Minimum sample size for developing a multivariable prediction model: PART II ‐ binary and time‐to‐event outcomes by Riley, Richard D, Snell, Kym IE, Ensor, Joie, Burke, Danielle L, Harrell Jr, Frank E, Moons, Karel GM, Collins, Gary S

“…When designing a study to develop a new prediction model with binary or time‐to‐event outcomes, researchers should ensure their sample size is adequate in…”
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PROBAST: A Tool to Assess the Risk of Bias and Applicability of Prediction Model Studies by Wolff, Robert F, Moons, Karel G M, Riley, Richard D, Whiting, Penny F, Westwood, Marie, Collins, Gary S, Reitsma, Johannes B, Kleijnen, Jos, Mallett, Sue

“…Clinical prediction models combine multiple predictors to estimate risk for the presence of a particular condition (diagnostic models) or the occurrence of a…”
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Prognosis Research Strategy (PROGRESS) 3: prognostic model research by Steyerberg, Ewout W, Moons, Karel G M, van der Windt, Danielle A, Hayden, Jill A, Perel, Pablo, Schroter, Sara, Riley, Richard D, Hemingway, Harry, Altman, Douglas G

“…Prognostic models are abundant in the medical literature yet their use in practice seems limited. In this article, the third in the PROGRESS series, the…”
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Protocol for development of a reporting guideline (TRIPOD-AI) and risk of bias tool (PROBAST-AI) for diagnostic and prognostic prediction model studies based on artificial intelligence by Collins, Gary S, Dhiman, Paula, Andaur Navarro, Constanza L, Ma, Jie, Hooft, Lotty, Reitsma, Johannes B, Logullo, Patricia, Beam, Andrew L, Peng, Lily, Van Calster, Ben, van Smeden, Maarten, Riley, Richard D, Moons, Karel GM

“…IntroductionThe Transparent Reporting of a multivariable prediction model of Individual Prognosis Or Diagnosis (TRIPOD) statement and the Prediction model Risk…”
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Multivariate and network meta-analysis of multiple outcomes and multiple treatments: rationale, concepts, and examples by Riley, Richard D, Jackson, Dan, Salanti, Georgia, Burke, Danielle L, Price, Malcolm, Kirkham, Jamie, White, Ian R

“…Organisations such as the National Institute for Health and Care Excellence require the synthesis of evidence from existing studies to inform their…”
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External validation of clinical prediction models using big datasets from e-health records or IPD meta-analysis: opportunities and challenges by Riley, Richard D, Ensor, Joie, Snell, Kym I E, Debray, Thomas P A, Altman, Doug G, Moons, Karel G M, Collins, Gary S

“…Access to big datasets from e-health records and individual participant data (IPD) meta-analysis is signalling a new advent of external validation studies for…”
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Prognosis Research Strategy (PROGRESS) 2: prognostic factor research by Riley, Richard D, Hayden, Jill A, Steyerberg, Ewout W, Moons, Karel G M, Abrams, Keith, Kyzas, Panayiotis A, Malats, Núria, Briggs, Andrew, Schroter, Sara, Altman, Douglas G, Hemingway, Harry

“…Prognostic factor research aims to identify factors associated with subsequent clinical outcome in people with a particular disease or health condition. In…”
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A guide to systematic review and meta-analysis of prediction model performance by Debray, Thomas P A, Damen, Johanna A A G, Snell, Kym I E, Ensor, Joie, Hooft, Lotty, Reitsma, Johannes B, Riley, Richard D, Moons, Karel G M

“…Validation of prediction models is highly recommended and increasingly common in the literature. A systematic review of validation studies is therefore…”
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Minimum sample size for developing a multivariable prediction model: Part I – Continuous outcomes by Riley, Richard D., Snell, Kym I.E., Ensor, Joie, Burke, Danielle L., Harrell, Frank E., Moons, Karel G.M., Collins, Gary S.

“…In the medical literature, hundreds of prediction models are being developed to predict health outcomes in individuals. For continuous outcomes, typically a…”
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Individual participant data meta‐analysis to examine interactions between treatment effect and participant‐level covariates: Statistical recommendations for conduct and planning by Riley, Richard D., Debray, Thomas P.A., Fisher, David, Hattle, Miriam, Marlin, Nadine, Hoogland, Jeroen, Gueyffier, Francois, Staessen, Jan A., Wang, Jiguang, Moons, Karel G.M., Reitsma, Johannes B., Ensor, Joie

“…Precision medicine research often searches for treatment‐covariate interactions, which refers to when a treatment effect (eg, measured as a mean difference,…”
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Persistent sex disparities in clinical outcomes with percutaneous coronary intervention: Insights from 6.6 million PCI procedures in the United States by Potts, Jessica, Sirker, Alex, Martinez, Sara C, Gulati, Martha, Alasnag, Mirvat, Rashid, Muhammad, Kwok, Chun Shing, Ensor, Joie, Burke, Danielle L, Riley, Richard D, Holmvang, Lene, Mamas, Mamas A

“…Prior studies have reported inconsistencies in the baseline risk profile, comorbidity burden and their association with clinical outcomes in women compared to…”
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Completeness of reporting of clinical prediction models developed using supervised machine learning: a systematic review by Andaur Navarro, Constanza L, Damen, Johanna A A, Takada, Toshihiko, Nijman, Steven W J, Dhiman, Paula, Ma, Jie, Collins, Gary S, Bajpai, Ram, Riley, Richard D, Moons, Karel G M, Hooft, Lotty

“…While many studies have consistently found incomplete reporting of regression-based prediction model studies, evidence is lacking for machine learning-based…”
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Multivariate meta-analysis: the effect of ignoring within-study correlation by Riley, Richard D.

“…Multivariate meta-analysis allows the joint synthesis of summary estimates from multiple end points and accounts for their within-study and between-study…”
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Clinical prediction models and the multiverse of madness by Riley, Richard D, Pate, Alexander, Dhiman, Paula, Archer, Lucinda, Martin, Glen P, Collins, Gary S

“…Each year, thousands of clinical prediction models are developed to make predictions (e.g. estimated risk) to inform individual diagnosis and prognosis in…”
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A refined method for multivariate meta-analysis and meta-regression by Jackson, Daniel, Riley, Richard D.

“…Making inferences about the average treatment effect using the random effects model for meta‐analysis is problematic in the common situation where there is a…”
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One‐stage individual participant data meta‐analysis models: estimation of treatment‐covariate interactions must avoid ecological bias by separating out within‐trial and across‐trial information by Hua, Hairui, Burke, Danielle L., Crowther, Michael J., Ensor, Joie, Tudur Smith, Catrin, Riley, Richard D.

“…Stratified medicine utilizes individual‐level covariates that are associated with a differential treatment effect, also known as treatment‐covariate…”
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Methodological conduct of prognostic prediction models developed using machine learning in oncology: a systematic review by Dhiman, Paula, Ma, Jie, Andaur Navarro, Constanza L, Speich, Benjamin, Bullock, Garrett, Damen, Johanna A A, Hooft, Lotty, Kirtley, Shona, Riley, Richard D, Van Calster, Ben, Moons, Karel G M, Collins, Gary S

“…Describe and evaluate the methodological conduct of prognostic prediction models developed using machine learning methods in oncology. We conducted a…”
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A multivariate meta-analysis approach for reducing the impact of outcome reporting bias in systematic reviews by Kirkham, Jamie J., Riley, Richard D., Williamson, Paula R.

“…Multivariate meta‐analysis allows the joint synthesis of multiple correlated outcomes from randomised trials, and is an alternative to a separate univariate…”
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