Andrew Pickles - Curriculum Vitae#

Andrew is remarkable for an eclectic education and career spanning natural, social and psychological science, and as a biostatistician who has combined methodological innovation together with a large portfolio of influential and informative clinical studies.

Education:

• University of Cambridge 71-74 BA(MA) (Hons.) Natural Science Tripos 2:i.
  
• UWIST, Cardiff 74-76 MSc Town Planning
  
• University of Wales 77-82 PhD (Applications of Stochastic Process Methods to Residential Mobility)

Publications: 496 peer-reviewed papers. Google Scholar h-index ~140; >92k citations (mental health, neuroscience, biostatistics, and social science).

Investigator applicant on more the 100 research grants, including theme lead in NIHR Maudsley Biomedical Research Centre (2012-2022)

Director of UKCRC Registered King's Clinical Trials Unit (2010-2019), expanding from mental health to all disease and becoming the UK's largest CTU (by # of trials).

Significant academic contributions:

Statistical Modelling: Developed the program gllamm for Generalized Linear Latent and Mixed Models, Combining random effects, latent variable and latent class models this transformed the field enabling the conceptualization and estimation of a much expanded range of models. Papers describing it and its numerical methods are now very highly cited, used in >1500 applied papers (see www.gllamm.org) and various versions of the framework are now incorporated into statistical packages such as Mplus, Latent Gold, Stata and R.

Mechanism: Primarily in the context of RCTs, designed studies to better understand the mechanism of change and therapeutic response - e.g. HTA Report https://njladmin.nihr.ac.uk/document/download/2002779.

Autism and Language: The key statistical contributor to the gold-standard measures of autism, percentile charts for language, the largest RCTs in autism, several of the largest or longest cohort studies in autism and language, neurophysiological studies from infancy, language regression in autism, and autism vaccine risk.

Time trends: Developed methods to better characterize trends in child mental health when different measures have been used and to account for recall errors.

Training: Extensive UK and international training record.