Martin Lindquist is Professor of Biostatistics at Johns Hopkins University. His research focuses on mathematical and statistical problems relating to functional magnetic resonance imaging (fMRI). Dr Lindquist is actively involved in developing new analysis methods to enhance our ability to understand brain function using human neuroimaging. He has published > 100 articles, and serves on the editorial boards of several scientific journals both in statistics and neuroimaging. He is a fellow of the American Statistical Association. In 2018 he was awarded the Organization for Human Brain Mapping’s ‘Education in Neuroimaging Award’ for teaching statistical issues to the neuroimaging community and the development of online classes that have taught fMRI methods to > 80,000 students world-wide.
Malcolm Macleod is Professor of Neurology and Translational Neurosciences at the University of Edinburgh, Honorary Consultant Neurologist at NHS Forth Valley, and an affiliate member of the Meta-Research Innovation Center (METRICS) at Stanford University. He serves as a member of the UK Home Office Animals in Science Committee and a Commissioner at the UK MHRA Commission for Human Medicines. He was cofounding coordinator of the Collaborative Approach to Meta-Analysis and Review of Animal Data from Experimental Studies (CAMARADES, www.camarades.info). His research focuses on the development of novel treatments for neurological diseases. This work includes: 1) clinical trials in stroke; 2) application of systematic review and meta-analysis of preclinical data to selecting drugs to take forward to clinical trial in stroke, multiple sclerosis, spinal cord injury and ALS; 3) the development of novel interventions to improve the rigor of published preclinical research. He has a long-standing interest in factors influencing the robustness of scientific findings, focused on the impact of risks of bias such as the failure to randomize treatment allocations, blind animal handling and outcome assessment, or report outcome in animals excluded from analysis.
Stan Lazic is Co-founder and Chief Scientific Officer at Prioris.ai Inc. – a company building probabilistic machine learning models in the pharmaceutical, life science, and healthcare sectors. Previously, he was Associate Director in Statistics and Machine Learning at AstraZeneca and spent ten years in the pharmaceutical industry. He has a PhD in Neuroscience and Master’s in Computational Biology from the University of Cambridge and has written a book on experimental design for biologists. He is on the Advisory Board of the UK Reproducibility Network and his research interests include the design and analysis of biological experiments, improving the reproducibility of biomedical research, and novel applications of Bayesian methods.
Eric-Jan Wagenmakers is Professor at the Psychological Methods Unit at the University of Amsterdam. He has promoted the preregistration of analysis plans in order to separate what is pre-planned from what is post-hoc, as well as the use of replication studies, sometimes in the form of adversarial collaborations. He has outlined the limitations of traditional inference methods (i.e., p-values and confidence intervals) and developed and promoted Bayesian inference procedures as a useful alternative. These are described in a coursebook (Bayesian Cognitive Modeling: A Practical Course, Lee & Wagenmakers, 2013) and form an integral part of JASP, an open source statistical software package that allows users to execute Bayesian hypothesis tests with ease (“SPSS done right“). He is a past president for the Society of Mathematical Psychology and has published over 290 articles in international peer-reviewed journals.
William Browne has been Professor of Statistics within the School of Education at the University of Bristol since 2014. Prior to that he was Professor of Biostatistics in the School of Veterinary Sciences. He was the first director of the Jean Golding Institute for Data Intensive research from 2016-2017 and now co-directs the Centre for Multilevel Modelling. His research focuses on statistical methods and software development, in particular random effect (multilevel) modelling and Monte Carlo Markov chain methods, along with application of such methods in diverse fields, including education, veterinary science, animal behavior and ecology. He has written software (MLPowSim) for sample size calculations in random effect models and was an author of the ARRIVE guidelines for reporting the results of animal experiments. His methodology/software development research has been funded by the UK’s ESRC including work on reproducibility of statistical analyses. His applied collaborative work has been funded by BBSRC, EPSRC, RSPCA and Welcome Trust.
Marcus Munafò is Professor of Biological Psychology in the School of Psychological Science at the University of Bristol, Co-Director of the Tobacco and Alcohol Research Group, and an affiliate member of the Meta-Research Innovation Center (METRICS) at Stanford University. He is Programme Lead within the Medical Research Council Integrative Epidemiology Unit at the University of Bristol, and Chair of the UK Reproducibility Network Steering group. His research focuses on understanding pathways into, and the consequences of, health behaviors and mental health. This work includes: 1) observational and genetic epidemiology; 2) the laboratory study of cognitive and neurobiological mechanistic pathways; and 3) the development of novel individual- and population-level interventions that target these mechanisms. He has a long-standing interest in factors influencing the robustness of scientific findings, with a particular focus on the impact of low statistical power, and the incentive structures that shape the behavior of scientists. Marcus is Chair of the ISSC.
Glyn Lewis is Professor of Psychiatric Epidemiology at University College London Division of Psychiatry. His main research interests are in the public health and epidemiology of psychiatric disorder. He trained in psychiatry at the Maudsley Hospital and Institute of Psychiatry, UK and in epidemiology at the London School of Hygiene and Tropical Medicine. His research involves identifying factors that are possible causal factors for depression, anxiety and schizophrenia. He also carries out randomized controlled trials concerned with the management of depression in primary care, investigating both psychological and pharmacological treatments. He has an interest in how research findings can be applied to clinical practice and in teaching clinicians about critical appraisal of the scientific literature.
Independent Statistical Standing Committee
The Independent Statistical Standing Committee (ISSC) is an external body intended to provide independent, unbiased evaluation and expert advice regarding all aspects of experimental design and statistics. Its overarching aim is to help improve the rigor and reproducibility of scientific research and, as such, CHDI makes this resource available to the Huntington’s disease research community on a priority basis. The ISSC is comprised of individuals from a diverse range of disciplines with specific expertise in research design and statistics. Importantly, committee members are not themselves engaged in Huntington’s disease research, mitigating any potential biases.
Services:
The ISSC provides a number of services, including:
Assistance with experimental design
Sample size/power calculations
Advice on statistical methods
Methodological evaluation of published research
Educational resource development.
Committee members:
There are currently seven members of the ISSC, each with a special interest in scientific rigor and study reproducibility. New members may be invited onto the ISSC to cover new methodologies, or affiliates consulted for specific projects.