Discussion meetings

Discussion Meetings are events where articles ('papers for reading') appearing in the Journal of the Royal Statistical Society are presented and discussed. The discussion and authors' replies are then published in the relevant Journal series. About half of the meetings are organised by the Society's Research Section and the events are often preceded by an informal session on the issues raised by the papers. See our guidelines for papers for discussion.

Preprints of journal papers are available to download to encourage discussion at our Discussion Meetings before publication in one of our journals. Other papers, such as Presidential addresses, are also available to download. All preprints available here are provisional and subject to later amendment by the authors.

Contact Judith Shorten if you would like to make a written contribution to a discussion meeting or receive a preprint for each meeting by email.

Click here to watch videos from past discussion meetings.

Preprint discussion papers

2018

Social Statistics Section Discussion Meeting, Wednesday, 17 October 2018 - 05.30pm
Location: The Barbican, London EC2Y 8DS

‘A comparison of sample survey measures of earnings of English graduates with administrative data’
Jack Britton, Neil Shephard and Anna Vignoles
Details

Extended Discussion Meeting, Wednesday, 5 September 2018, at the Royal Statistical Society’s annual conference in Cardiff

Three papers on ‘Data visualization’:
‘Visualizing spatiotemporal models with virtual reality: from fully immersive environments to applications in stereoscopic view’ (S. Castruccio, M. G. Genton and Y. Sun);
‘Visualization in Bayesian workflow’ (J. Gabry, D. Simpson, A. Vehtari, M. Betancourt and A. Gelman);
'Graphics for uncertainty’ (A. W. Bowman)

Official Statistics Section Discussion Meeting, Wednesday, 9 May 2018

‘From start to finish: a framework for the production of small area official statistics’
Nikos Tzavidis, Li-Chun Zhang, Angela Luna, Timo Schmid and Natalia Rojas-Perilla
Details

Discussion Meeting, Wednesday, 18 April 2018

‘The statistical analysis of acoustic phonetic data: exploring differences between spoken Romance languages’
Davide Pigoli, Pantelis Z Hadjipantelis, John S Coleman and John A D Aston
Details

 

Preprints

2018

Social Statistics Section Discussion Meeting, Wednesday, 17 October 2018 - 05:30pm
Location: The Barbican, London EC2Y 8DS

Jack Britton (Institute for Fiscal Studies, London), Neil Shephard (Harvard University, Cambridge) and Anna Vignoles (University of Cambridge)
‘A comparison of sample survey measures of earnings of English graduates with administrative data’

Administrative data sets are increasingly used in research because of their excellent coverage and large scale. However, in the UK the use of administrative data on individuals’ earnings, and particularly graduates’ earnings, is novel. Understanding the strengths and weaknesses of such data is important as they are set to be used extensively for research and to inform policy. Here we compare survey-based labour earnings data from the UK’s Labour Force Survey (LFS) with UK Government administrative sources of individual level earnings data, focusing separately on young (up to age 32 years) graduates and non-graduates. This type of administrative data set has few sample selection issues and is longitudinal and its large samples mean that the earnings of subpopulations can potentially be studied with low error. Overall we find a similar share of individuals with zero earnings in the LFS and administrative data, but a considerably higher share (conditionally on working) earning below £8000 in the administrative data. The LFS has generally higher earnings right through the distribution, though above the median a large share of the differences can potentially be explained by employee pension contributions. We also find considerably larger gender difference in the survey data. The findings hold for both graduates and non-graduates. These differences are substantively important and suggest different conclusions about the gender wage gap, the graduate earnings premium and the extent of earnings inequality.

To be published in Series A; for more information go to the Wiley Online Library.

The preprint is available to download.
'A comparison of sample survey measures of earnings of English graduates with administrative data’ (PDF)
Supporting information (PDF)
Data and computer code (.zip)


Extended Discussion Meeting on ‘Data visualization’, Wednesday, 5 September 2018

Stefano Castruccio (University of Notre Dame, USA) and Marc G. Genton and Ying Sun (King Abdullah University of Science and Technology, Thuwal)

‘Visualizing spatiotemporal models with virtual reality: from fully immersive environments to applications in stereoscopic view’

Recent advances in computing hardware and software present an unprecedented opportunity for statisticians who work with data indexed in space and time to visualize, explore and assess the structure of the data and to improve resulting statistical models. We present results of a 3-year collaboration with a team of visualization experts on the use of stereoscopic view and virtual reality (VR) to visualize spatiotemporal data with animations on non-trivial manifolds. We first present our experience with fully immersive VR with motion tracking devices that enable users to explore global three-dimensional time–temperature fields on a spherical shell interactively. We then introduce a suite of applications with VR mode, freely available for smartphones, to port a visualization experience to any interested people. We also discuss recent work with head-mounted devices such as a VR headset with motion tracking sensors.

To be published in Series A; for more information go to the Wiley Online Library.

The preprint is available to download.
‘Visualizing spatiotemporal models with virtual reality: from fully immersive environments to applications in stereoscopic view’ (PDF)
View animation (.zip)
Supporting information (PDF)

Jonah Gabry (Columbia University, New York), Daniel Simpson (University of Toronto), Aki Vehtari (Aalto University, Espoo), Michael Betancourt (Columbia University, New York, and Symplectomorphic, New York) and Andrew Gelman (Columbia University, New York)

‘Visualization in Bayesian workflow’

Bayesian data analysis is about more than just computing a posterior distribution, and Bayesian visualization is about more than trace plots of Markov chains. Practical Bayesian data analysis, like all data analysis, is an iterative process of model building, inference, model checking and evaluation, and model expansion. Visualization is helpful in each of these stages of the Bayesian workflow and it is indispensable when drawing inferences from the types of modern, high dimensional models that are used by applied researchers.

To be published in Series A; for more information go to the Wiley Online Library.

The preprint is available to download.
‘Visualization in Bayesian workflow’ (PDF)
Supporting information (PDF)

Adrian W. Bowman (University of Glasgow)

'Graphics for uncertainty’

Graphical methods such as colour shading and animation, which are widely available, can be very effective in communicating uncertainty. In particular, the idea of a ‘density strip’ provides a conceptually simple representation of a distribution and this is explored in a variety of settings, including a comparison of means, regression and models for contingency tables. Animation is also a very useful device for exploring uncertainty and this is explored particularly in the context of flexible models, expressed in curves and surfaces whose structure is of particular interest. Animation can further provide a helpful mechanism for exploring data in several dimensions. This is explored in the simple but very important setting of spatiotemporal data.

To be published in Series A; for more information go to the Wiley Online Library.

The preprint is available to download.
‘Graphics for uncertainty’ (PDF)
View animations (zip)

This meeting forms part of the RSS 2018 Conference and anyone registered for that day can automatically attend the meeting. If you are not able to attend the conference but wish to just attend the discussion meeting session please contact the conference office.


Official Statistics Section Discussion Meeting, Wednesday, 9 May 2018

Nikos Tzavidis, Li-Chun Zhang and Angela Luna (University of Southampton) and Timo Schmid and Natalia Rojas-Perilla (Free University, Berlin)

‘From start to finish: a framework for the production of small area official statistics’

Small area estimation is a research area in official and survey statistics of great practical relevance for national statistical institutes and related organizations. Despite rapid developments in methodology and software, researchers and users would benefit from having practical guidelines for the process of small area estimation. We propose a general framework for the production of small area statistics that is governed by the principle of parsimony and is based on three broadly defined stages, namely specification, analysis and adaptation, and evaluation. Emphasis is given to the interaction between a user of small area statistics and the statistician in specifying the target geography and parameters in the light of the available data. Model-free and model-dependent methods are described with a focus on model selection and testing, model diagnostics and adaptations such as use of data transformations. Uncertainty measures and the use of model and design-based simulations for method evaluation are also at the centre of the paper. We illustrate the application of the proposed framework by using real data for the estimation of non-linear deprivation indicators. Linear statistics, e.g. averages, are included as special cases of the general framework.

To be published in Series A; for more information go to the Wiley Online Library.

The preprint is available to download.
‘From start to finish: a framework for the production of small area official statistics’ (PDF)
Data and computer code (.zip)


Discussion Meeting, Wednesday, 18 April 2018

Davide Pigoli, Pantelis Z Hadjipantelis, John S Coleman and John A D Aston

'The statistical analysis of acoustic phonetic data: exploring differences between spoken Romance languages’

The historical and geographical spread from older to more modern languages has long been studied by examining textual changes and in terms of changes in phonetic transcriptions. However, it is more difficult to analyse language change from an acoustic point of view, although this is usually the dominant mode of transmission. We propose a novel analysis approach for acoustic phonetic data, where the aim will be to model the acoustic properties of spoken words statistically. We explore phonetic variation and change by using a time–frequency representation, namely the log-spectrograms of speech recordings. We identify time and frequency covariance functions as a feature of the language; in contrast, mean spectrograms depend mostly on the particular word that has been uttered. We build models for the mean and covariances (taking into account the restrictions placed on the statistical analysis of such objects) and use these to define a phonetic transformation that models how an individual speaker would sound in a different language, allowing the exploration of phonetic differences between languages. Finally, we map back these transformations to the domain of sound recordings, enabling us to listen to the output of the statistical analysis. The approach proposed is demonstrated by using recordings of the words corresponding to the numbers from 1 to 10 as pronounced by speakers from five different Romance languages.

To be published in Series C; for more information go to the Wiley Online Library.

The preprint is available to download.
The statistical analysis of acoustic phonetic data: exploring differences between spoken Romance languages’ (PDF)
Supporting information (PDF)