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Key Details

Date: 2nd March 2020 – 6th March 2020
Time: 09:00-17:30
Venue: Computer Room B / IoPPN Boardroom, Main Building, Institute of Psychiatry, Psychology and Neuroscience (IoPPN), King's College London. View Map.


Course Aim

This is a four day course, followed by one day workshop with invited speakers, and is aimed at PhD students and researchers working in applied psychometrics. The course provides a comprehensive introduction to the fundamental ideas of psychometric theory and their implementation.

Starting from the scale construction and gradually moving to the most recent statistical methods employed in measurement, the course provides a complete methodological framework for applied researchers. While the classical test theory ideas on reliability and validity, often used in the literature, are presented, the more methodologically sound item response theory counterparts are explained (difficulty and discrimination, item and total characteristic and information curves).

For the measurement of the latent variable(s) the course presents exploratory and confirmatory factor analysis (EFA and CFA) for numerical data. For categorical data, both the item response theory approach (IRT; 2-parameter logistic, grated response and partial credit models) as well as the item factor analysis model (IFA; both with regard to EFA and CFA). The course also presents the methods to explore measurement differences (measurement invariance) between groups (MG CFA), measurement differences due to covariates (MIMIC models), and measurement differences between raters or time points (longitudinal IFA), for all types of data.

Lectures and lab sessions will be based on the use of the STATA software.

The course will be of interest to statisticians, researchers and PhD students of Psychology and Psychiatry, and mental health professionals, who wish to acquire and/or consolidate the knowledge and skills necessary for mental health research.

Potential students should already be familiar with and have a good understanding of regression and factor analysis. While no prior knowledge of STATA will be assumed, this will not be a formal STATA course.
Learning Outcomes

Subject Specific: Knowledge, Understanding and Skills

On successful completion of this module the student should be able to:

  • develop a psychometric tool, for a characteristic of interest (latent variable)
  • apply classical test theory methods in psychometrics to test the reliability and the validity of a scale
  • apply item response theory methods in psychometrics
  • apply exploratory and confirmatory factor analysis for binary, categorical, and numerical data
  • understand the concept of measurement invariance and be able to apply the corresponding methods across groups
  • to choose the appropriate model for each type of data
  • to understand the links between different schools of thought in psychometrics, their similarities and their differences
  • to critically evaluate the quality of published psychometric assessments
  • understand and explain the concept of latent constructs and their measurement

General: Knowledge, Understanding and Skills

On successful completion of this module the student should be able to:

  • Interact effectively in a research team (group activities)
  • Communicate ideas effectively and professionally by written, oral and visual means
  • Select and properly manage information drawn from books, journals, and the internet
  • Be able to report the results of their study in the form of a scientific paper
  • Study autonomously and undertake activities/projects with minimum guidance
  • Show confidence in the use of STATA to implement psychometric models for real life applications

Cost and Booking

  • External Early bird: £855 (till 02/01/20, price thereafter £950)
  • KCL Staff Early bird: £641.25 (till 02/01/20, price thereafter £712.5)
  • KCL Student Early bird: £427.5 (till 02/01/20, price thereafter £475)
  • Other student Early bird: £641.25 (till 02/01/20, price thereafter £712.5)
  • King's Health Partners Early bird: £641.25 (till 02/01/20, price thereafter £712.5)

That is, 50% discount to King's College London PhD students, 25% discount to other students and staff at King's College London and King's Health Partners.

Booking / Application

Booking for this course is open

To apply please email with the following details:

Subject: Application for Contemporary Applied Psychometrics 2020


Email Address:

Contact Phone Number:

  1. Are you affiliated with KCL and/or King's Health Partners?
    1. If Yes, indicate how you are affiliated with KCL and/or King's Health Partners
    2. Indicate your education/employee status: KCL PhD, KCL student, KCL staff, King's Health Partners affiliate, External Student or External
  2. In 100 words, state why you wish to enrol/participate in this course:
  3. In 100 words, state which skills you hope to acquire:

Once your application has been approved, you will be sent a link to payment and a discount code if one is to be applied.

A 10% early bird discount will be available until 2 January 2020 and booking will close on 24th February 2020

Course Team

Professor Andrew Pickles (Academic Lead)

AndrewPicklesFrom an early background in natural sciences, urban planning and geography Andrew joined the MRC Child Psychiatry Unit as statistician in 1986, moved to the Dept of Biostatistics in Manchester in 1998, returning to the IoPPN in 2010.  

His principal interests have been in multivariate longitudinal data, with most applications being in what is now called life-course analysis. These studies have involved genomic, physiological, psychological and social measures and processes and have spanned neonates to geriatrics. A good part of this work has focussed on autism, with recent work highlighting intervention studies and longer term outcomes. 

Equally rewarding have been the impact on statistical modelling and software (e.g. structural equation modelling in Stata) and the clinical impact on patient care (e.g. NICE guidelines).

Research portal

See Andrew's research portal here.

Dr Silia Vitoratou (Academic Lead)

SiliaVitoratouSilia is a Lecturer in Psychometrics and Measurement and leads the Psychometrics and Measurement Lab (PML). Silia holds a BS degree in Mathematics, a Msc degree in Biostatistics (thesis in applied psychometrics) and a PhD in Bayesian model comparison for IRT models.

Research interests

Applied research: Psychometrics (IRT, EFA, CFE, SEM); Biostatistics.

Methodological research: Latent variable models; Bayesian model comparison & MCMC; Thermodynamics.

Research portal

See Silia's research portal here.


Your place will not be confirmed until payment has been made. Failure to cancel without sufficient notice will forfeit your course fee and access to future courses. If you would like to pay by internal transfer, please contact

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