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You are here : Events : RSS online and virtual events : Journal Club

RSS Journal Club

Sponsored by Quintiles

Next event

Thursday 20 November 2014, 10:00am - 11:30am

The item count method for sensitive survey questions: Modelling criminal behaviour
The item count method is a way of asking sensitive survey questions which protects the anonymity of the respondents by randomization before the interview. It can be used to estimate the probability of sensitive behaviour and to model how it depends on explanatory variables. The results of the author’s analysis of criminal behaviour highlight the fact that careful design of the questions is crucial for the success of the item count method.
Speakers: Jouni Kuha and Jonathan Jackson

Which method predicts recidivism best? A comparison of statistical, machine learning and data mining prediction models
Risk assessment instruments are widely used in criminal justice settings all over the world. However, in recent times, different approaches to prediction have been developed. This paper investigates whether modern techniques in data mining and machine learning provide an improvement in predictive performance over classical statistical methods such as logistic regression and linear discriminant analysis. Using data from criminal conviction histories of offenders, these models are compared. Results indicate that in these data, classical methods tend to do equally well as or better than their modern counterparts.
Speakers: Nikolaj Tollenaar and Peter van der Heijden

Chair: Professor Chris Skinner, professor of statistics at the London School of Economics & Political Science.
 

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Additional information

Please remember, you are able to submit questions in advance of the session.  If you would like to do so, or for any further information, please email journalclub@rss.org.uk. Further details on QUINTILES, sponsor of RSS Journal Club can be found at www.quintiles.com.  For details of other RSS Events please view our events calendar, or for information on joining the RSS please see our Membership pages.

 

Previous events

1 April 2014
Combination Therapies (RSS and PSI joint event sponsored by Quintiles and Wiley)

Chair: James Carpenter, School of Hygiene and Tropical Medicine

A Bayesian dose finding design for oncology clinical trials of combinational biological agents - Download slides
Speaker: Ying Yuan, Department of Biostatistics, University of Texas

Co-authors: Chunyan Cai, Yuan Ji; Journal of the Royal Statistical Society: Series C (Applied Statistics), Volume 63, Issue 1, Pages 159–173, January 2014

Escalation strategies for combination therapy Phase I trials - Download slides
Speaker: Michael J Sweeting, Department of Public Health and Primary Care, University of Cambridge

Discussant: Tony Sabin, Amgen

Co-author: Adrian P Mander;
Pharmaceutical Statistics, Volume 11, Issue 3, Pages 258–266, May/June 2012



Point process modelling for directed interaction networks
10 December 2013

Audio: MP3, Slides: PDF

Speakers

Chair: John Aston (J.A.D.Aston@warwick.ac.uk)

Summary

Network data often take the form of repeated interactions between senders and receivers tabulated over time. A primary question to ask of such data is which traits and behaviours are predictive of interaction. To answer this question, a model is introduced for treating directed interactions as a multivariate point process: a Cox multiplicative intensity model using covariates that depend on the history of the process. Consistency and asymptotic normality are proved for the resulting partial-likelihood-based estimators under suitable regularity conditions, and an efficient fitting procedure is described. Multicast interactions—those involving a single sender but multiple receivers—are treated explicitly. The resulting inferential framework is then employed to model message sending behaviour in a corporate e-mail network. The analysis gives a precise quantification of which static shared traits and dynamic network effects are predictive of message recipient selection.

DOI: 10.1111/rssb.12013



A likelihood-based sensitivity analysis for publication bias in meta-analysis
30 September 2013

Speaker

Professor John B. Copas.
Webcast: Flash, Audio: MP3, Slides: PDF

John Copas is Emeritus Professor of Statistics at the University of Warwick.  He has published widely on the methodology of statistics, including a number of recent papers on meta-analysis and publication bias.  He has presented several RSS read papers with published discussions, and is a recipient of the Society’s Guy Medal in Silver.  John Copas has served on the Methodology Advisory Committee of the Office for National Statistics and has worked on many collaborative projects in medicine and the social sciences.


Chair: Professor James Carpenter, London School of Hygiene & Tropical Medicine

Summary

Publication bias, a serious threat to the validity of meta-analysis, is essentially a problem of non-random sampling.  If the research studies identified in a systematic review are thought of as a sample from the population of all studies which have been done in the area of interest, and if studies which report a statistically significant result are more likely to be published than studies whose results are inconclusive, than a meta-analysis of the studies selected in the review will be biased, giving over-estimated treatment effects and exaggerated assessments of significance.  This recent paper in Applied Statistics discusses a sample selection model for meta-analysis and suggests a sensitivity analysis which can be useful for assessing how large the effect of publication bias is likely to be.  Two examples are discussed in detail, including an example of a published meta-analysis whose conclusion was completely contradicted by evidence from a later large collaborative clinical trial.

 

Information quality
13 June 2013

 
Speakers

  • Ron S. Kenett (KPA, Raanana, Israel, University of Turin, Italy, and New York University–Poly, USA). Slides: PDF | PowerPoint
  • Galit Shmueli (Indian School of Business, Gachibowli, India). Webcast: YouTube video, Slides: PDF
Chair: Dr Shirley Coleman

Summary

We define the concept of information quality ‘InfoQ’ as the potential of a data set to achieve a specific (scientific or practical) goal by using a given empirical analysis method. InfoQ is different from data quality and analysis quality, but is dependent on these components and on the relationship between them. We survey statistical methods for increasing InfoQ at the study design and post-data-collection stages, and we consider them relatively to what we define as InfoQ.

We propose eight dimensions that help to assess InfoQ: data resolution, data structure, data integration, temporal relevance, generalizability, chronology of data and goal, construct operationalization and communication. We demonstrate the concept of InfoQ, its components (what it is) and assessment (how it is achieved) through three case-studies in on-line auctions research. We suggest that formalizing the concept of InfoQ can help to increase the value of statistical analysis, and data mining both methodologically and practically, thus contributing to a general theory of applied statistics.


On Survival  Analysis
16 April 2013


This joint session with PSI focused on topics in Survival Analysis. The session was chaired by James Carpenter, London School of Hygiene and Tropical Medicine.

Speakers Abdus S. Wahed (University of Pittsburgh and RSS) and Nicola Schmitt (AstraZeneca and PSI) presented their papers published in Applied Statistics and Pharmaceutical Statistics respectively. 


Webcast recordings

(with slides):  WMV (61,057 KB)  ¦  MP4 (141,031 KB).

(audio only):  MP3 (77,134 KB)

 

Royal Statistical Society (RSS)

Abdus S. Wahed, University of Pittsburgh

Evaluating joint effects of induction–salvage treatment regimes on overall survival in acute leukaemia

Co-author: Peter F. Thall

Journal of the Royal Statistical Society: Series C (Applied Statistics), Volume 62, Issue 1, Pages 67–83, January 2013

Links: Abstract| Article full text | Journal Club Presentation Slides+

 

Statisticians in the Pharmaceutical Industry (PSI)

Nicola Schmitt, AstraZeneca

Attenuation of treatment effect due to measurement variability in assessment of progression-free survival

Co-authors: S. Hong, A. Stone, J. Denne

Pharmaceutical Statistics, Volume 11, Issue 5, pages 394-402, September/October 2012

Links: Abstract| Article full text* | Journal Club Presentation Slides+


 

How does the Royal Statistical Society Journal Club work?

Journal Club meetings are held every few months and last approximately 1 hour but may run longer as there is usually a Q&A session at the end.

Two papers will be selected from the Journals of the RSS and authors will be invited to present their papers (20 mins) followed by discussion (25 mins) for each paper.

Attendees will dial into a Teleconference Call. Papers and slides will be available to download 2 weeks in advance or you can log into the conference system using your web browser and follow the presentation live online.

These sessions are open to RSS members and non-RSS members. No need to pre-register.

Audio recordings will be available for download shortly after the session.

Further information

You may require Adobe Reader and/or PowerPoint viewer to access journal club papers and slides.

For further information or to provide feedback on the Royal Statistical Society Journal Club, please contact journalclub@rss.org.uk
 

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