Rajeswaran, Jeevanantham Blackstone, Eugene H Barnard, John
Published in
Statistical methods in medical research
In many longitudinal follow-up studies, we observe more than one longitudinal outcome. Impaired renal and liver functions are indicators of poor clinical outcomes for patients who are on mechanical circulatory support and awaiting heart transplant. Hence, monitoring organ functions while waiting for heart transplant is an integral part of patient m...
Ma, Junsheng Hobbs, Brian P Stingo, Francesco C
Published in
Statistical methods in medical research
Over the past decade, a tremendous amount of resources have been dedicated to the pursuit of developing genomic signatures that effectively match patients with targeted therapies. Although dozens of therapies that target DNA mutations have been developed, the practice of studying single candidate genes has limited our understanding of cancer. Moreo...
Goldsmith, K A Chalder, T White, P D Sharpe, M Pickles, A
Published in
Statistical methods in medical research
Clinical trials are expensive and time-consuming and so should also be used to study how treatments work, allowing for the evaluation of theoretical treatment models and refinement and improvement of treatments. These treatment processes can be studied using mediation analysis. Randomised treatment makes some of the assumptions of mediation models ...
Resche-Rigon, Matthieu White, Ian R
Published in
Statistical methods in medical research
In multilevel settings such as individual participant data meta-analysis, a variable is 'systematically missing' if it is wholly missing in some clusters and 'sporadically missing' if it is partly missing in some clusters. Previously proposed methods to impute incomplete multilevel data handle either systematically or sporadically missing data, but...
Seaman, Shaun R Hughes, Rachael A
Published in
Statistical methods in medical research
Estimating the parameters of a regression model of interest is complicated by missing data on the variables in that model. Multiple imputation is commonly used to handle these missing data. Joint model multiple imputation and full-conditional specification multiple imputation are known to yield imputed data with the same asymptotic distribution whe...
Petit, Caroline Samson, Adeline Morita, Satoshi Ursino, Moreno Jullien, Vincent Comets, Emmanuelle Zohar, Sarah
The number of trials conducted and the number of patients per trial are typically small in paediatric clinical studies. This is due to ethical constraints and the complexity of the medical process for treating children. While incorporating prior knowledge from adults may be extremely valuable, this must be done carefully. In this paper, we propose ...
Chen, Weijie Sahiner, Berkman Samuelson, Frank Pezeshk, Aria Petrick, Nicholas
Published in
Statistical methods in medical research
Scores produced by statistical classifiers in many clinical decision support systems and other medical diagnostic devices are generally on an arbitrary scale, so the clinical meaning of these scores is unclear. Calibration of classifier scores to a meaningful scale such as the probability of disease is potentially useful when such scores are used b...
Hernández-González, Jerónimo Inza, Iñaki Crisol-Ortíz, Lorena Guembe, María A Iñarra, María J Lozano, Jose A
Published in
Statistical methods in medical research
Machine learning techniques have been previously used to assist clinicians to select embryos for human-assisted reproduction. This work aims to show how an appropriate modeling of the problem can contribute to improve machine learning techniques for embryo selection. In this study, a dataset of 330 consecutive cycles (and associated embryos) carrie...
Liu, Wei Ding, Jinhui
Published in
Statistical methods in medical research
The application of the principle of the intention-to-treat (ITT) to the analysis of clinical trials is challenged in the presence of missing outcome data. The consequences of stopping an assigned treatment in a withdrawn subject are unknown. It is difficult to make a single assumption about missing mechanisms for all clinical trials because there a...
Zhu, Huirong DeSantis, Stacia M Luo, Sheng
Published in
Statistical methods in medical research
Longitudinal zero-inflated count data are encountered frequently in substance-use research when assessing the effects of covariates and risk factors on outcomes. Often, both the time to a terminal event such as death or dropout and repeated measure count responses are collected for each subject. In this setting, the longitudinal counts are censored...
