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28th July 2023, 2.00 - 4.00pm:


APBG mid-year meeting - Pharmacokinetics and Statistics: When two become one (an untold love story?)

North Sydney and online

FREE event! Please RSVP to

This year we will delve into the fascinating realm where Statistics and Pharmacokinetics intersect, with an exclusive presentation from renowned statistician and pharmacokineticist Glynn Morrish, Owner and Director of Remedy Research. 


All members are warmly invited to join us in person for refreshments and networking. For added convenience, the event will also be accessible online. Please RSVP to for address and the online link. We look forward to seeing you there!



2pm Tea, coffee and networking
2.30pm Presentation by Glynn Morrish – Pharmacokinetics and Statistics: When two become one (an untold love story?)
4pm Afternoon tea and networking
4.30pm Meeting Close

Abstract for Pharmacokinetics and Statistics: When two become one (an untold love story?)

A key objective throughout the drug development process is to understand exposure of the investigational product, how exposure relates to efficacy and safety, and how exposure may change with different populations and administration regimens. Pharmacokinetics is the study of how the body interacts with administered products and determines exposure. In the analysis of pharmacokinetic data, rigorous and robust statistical methodology must be applied to ensure appropriate outcomes and accurate reporting are achieved.  Further to this, the recent and future advancement of the pharmacometrics domain heavily relies on the application of advanced statistical concepts. This presentation will provide an introduction to clinical pharmacokinetics, describe non-compartmental and model-based pharmacokinetic analysis methods, and discuss the statistical methodology and techniques that are applied to various drug development objectives.

Biography of Speaker Glynn Morrish

Glynn Morrish is the Director of Remedy Research, a consultancy organization providing pharmacokinetic and statistical analysis services to the drug/device development industry. Glynn has over 20 years' experience in clinical research and data analysis, both in industry and academic settings. He has a deep passion for biostatistical and pharmacometric analysis and its application to the drug/device development process; demonstrated by his contribution to the development of over 100 pharmaceutical products, authoring of peer-reviewed publications, conduct of non-for-profit and commercial courses in clinical data modelling and simulation, and the supervision of post-graduate research students.


19th May 2023, 2.30 - 5.00pm:

Estimands in Practice 

Macquarie University Sydney City Campus and online

FREE event! Please RSVP to

The estimand framework was published as ICH E9 (R1) in 2019, however since that time there has been some uncertainty about how to implement the framework in practice. At this face-to-face meeting, you will have the opportunity to view the PSI's Expert Interest Working Group's webinar on Estimands in Oncology - How and Why while participating in live polling and discussion.



2.30pm Tea, coffee and networking

2.45pm Screening of PSI EIWG Webinar (Part 1)
3.30pm Afternoon tea and networking
3.50pm Screening of PSI EIWG Webinar (Part 2)
4.35pm General Discussion

5.00pm Close

Abstract for PSI EIWG Webinar - Estimands in Oncology - How and Why
During this webinar, you will be guided through a case study (CheckMate 037) and interactively deepen the knowledge to gain hands-on experience in developing estimands. You will be introduced to the background and disease context of the case study, the concept of an estimand, and important clinical events (increased dropout rate and crossover therapy) that occurred in the trial and affected interpretation of the results. Using non-technical language and clear grap
hical presentation of the concepts, you will experience how the estimand framework provides a common language to describe the diversity of patient journeys and why it is important to address the right question in clinical trials. Target audience (no prior knowledge in oncology or of estimands required): Clinicians, Investigators, Regulatory Experts, Medical Writers, Ethics Committees, Statisticians.

The targeted learning outcomes are as follows: - Recognize the benefits of following the estimand framework (ICH E9 (R1) addendum) in the context of a clinical trial, in order to: - have a common language to describe the diversity of patient journeys - address the right question in clinical trials - Be able to construct an estimand, including identification of relevant intercurrent events and application of relevant strategies to address them - Gain insights from a cross-industry international working group on estimands in oncology Presented by members of the Estimands in Oncology special interest group

2nd December 2022, 1.30 - 4.30pm:

APBG AGM and End of Year Meeting 

The George Institute, The HUB, Level 5, 1 King St, Newtown

FREE event! Please RSVP to

All members and guests are invited to join us in person for refreshments and networking. The event will also be available to join online.
2nd December 2022, 1.30-4.30pm

The George Institute, The HUB, Level 5, 1 King St, Newtown

1.30pm Tea, coffee and networking
3pm Afternoon tea and networking
3.30pm Dr William Reece – Early Phase Oncology Trials
4.30pm Meeting Close

Early Phase Oncology Trials

Speaker:  Dr William Reece (Labcorp)

Abstract: Despite its well-publicised shortcomings, the development of Oncology therapies has frequently relied on the 3+3 design to determine the Maximum Tolerated Dose (MTD) and Recommended Phase 2 Dose (RP2D) for further development.  To improve on this design, multiple alternative strategies have begun to find favor, being used globally, including the Continuous Reassessment Method (CRM), Bayesian Logistic Regression Method (BLRM), modified Toxicity Probability Interval, Bayesian Optimal Interval, i3+3, etc..  The performance of these model-based and rule-based designs depends much on arbitrary choices for target toxicity rates, maximum numbers of patients to be enrolled, and the uncontrollable effect of non-random patient selection.  I’ll be presenting my perspective on choices of some of these parameters, the relative merits of some of these designs, considering their application in practice, and some considerations around how to optimally incorporate them into a development program.  Furthermore, regulators are now beginning to require consideration of an Optimal Biological Dose, including randomization between doses, and an overview of efficacy, safety and PK/PD parameters.  I’ll be presenting some proposals around how this might be addressed in the context of an oncology program where risk exposure of patients to a novel compound needs to be balanced against a requirement to give patients doses that can reasonably be expected to be therapeutic.


Biography: William is a Director of Biostatistics for Labcorp.  He has a degree in Biochemistry, a PhD in Immunology and a Master’s in Biostatistics.  He has held roles across academia and industry, including as a research immunologist, statistician for Eli Lilly, and heading up the Asia Pacific Statistics and Programming teams for Covance prior to taking on his current dual role of statistical consulting and director of commercial support for Data Management and Statistics.  Throughout his statistical career, he has had a particular focus on oncology design, and regularly consults to biotech and pharmaceutical companies on the optimal design of early phase studies, assisting in protocol writing and NDA submissions.

20-21 October 2022,  2-Day workshop:

Estimands, Estimators and Estimates: Aligning target of estimation, method of estimation, and sensitivity analysis  

Presented by Dr Frank Bretz at the Macquarie University Sydney City Campus

Register now at: 


Description: The ICH E9(R1) Addendum on 'Estimands and Sensitivity Analysis in Clinical Trials' introduced a framework to align planning, design, conduct, analysis, and interpretation of clinical trials. When defining the clinical question of interest, clarity is needed about 'intercurrent events' that affect either the interpretation or the existence of the measurements associated with the clinical question of interest, such as discontinuation of assigned treatment, use of an additional or alternative treatment and terminal events such as death. The description of an estimand should reflect the clinical question of interest in respect of these intercurrent events, and the Addendum introduces strategies to reflect different questions of interest that might be posed. 

This two-day course will introduce the estimand framework according to the ICH E9(R1) Addendum. Using a generic example to illustrate the thinking process that aligns estimands and sensitivity analyses with trial objectives, we will provide an in-depth description of intercurrent events and various strategies for addressing them when defining the clinical question of interest. The choice of strategies can influence how more conventional attributes of a trial are reflected when describing the clinical question, for example the treatments, population or the variable (endpoint) of interest. For a given estimand, an aligned method of analysis, or estimator, should be implemented that is able to provide an estimate on which reliable interpretation can be based and which includes the handling of intercurrent events, missing data and sensitivity analyses. We will therefore also discuss how to identify and implement analyses approaches as well as sensitivity analyses that are aligned with a chosen estimand for different types of endpoints in longitudinal clinical trial settings.

About the Instructor: Dr. Frank Bretz is a Distinguished Quantitative Research Scientist at Novartis. He has supported the methodological development in various areas of pharmaceutical statistics, including dose finding, multiple comparisons, estimands, and adaptive designs. Frank is an Adjunct Professor at the Hannover Medical School (Germany) and the Medical University of Vienna (Austria). He was a member of the ICH E9(R1) Expert Working Group on 'Estimands and sensitivity analysis in clinical trials' and currently serves on the ICH E20 Expert Working Group on 'Adaptive clinical trials'. Frank is a Fellow of the American Statistical Association.

Outline: This two-day short course will include eight lectures (one hour and 30 minutes for each), with four lectures on Day 1 (October 20) and four on Day 2 (October 21).

Day 1: 
•    Introduction, motivation and scope of the ICH E9(R1) Addendum
•    A framework to align planning, design, conduct, analysis and interpretation of clinical trials
•    Description, strategies and construction of estimands
•    Generic example to illustrate the thinking process that aligns estimands and sensitivity 
Day 2: 
•    Gentle introduction to causal inference
•    Intercurrent events and missing data
•    Main analyses targeting estimands for different types of endpoints and strategies
•    Sensitivity and supplementary analysis in light of the estimand framework


Learning Objectives: This course will focus on estimands and related statistical methodologies that are commonly used in clinical trials. We will share our experiences and try to provide some guidance on their use in clinical trial practice. The target audience includes statisticians working in industry (pharmaceutical companies), academia (universities, medical centers, or research hospitals), or government (AIHW or TGA), and also graduate students who are interested in clinical trial methods. The difficulty level of the course is intermediate, at a second-year graduate course level. The learning objectives are three-fold: (1) to understand the fundamentals of the estimand framework and be able to apply it in clinical trials; (2) to identify an appropriate primary analysis method that targets the estimand of interest, fully aligned with the ICH E9(R1) Addendum; and (3) to implement appropriate main and sensitivity analyses.  


29th July 2022, 1.30 - 4.30pm:

APBG Mid Year Meeting 

The George Institute, The HUB, Level 5, 1 King St, Newtown

FREE event! Please RSVP to

All members and guests are invited to join us in person for refreshments and networking. The event will also be available to join online.

29th July 2022, 1.30-4.30pm

The George Institute, The HUB, Level 5, 1 King St, Newtown

1.30pm Tea, coffee and networking
2pm Dr Elisa Young – Getting to the CORE of CDISC
3pm Afternoon tea and networking
3.30pm Dr Helen Ogden – Flexible Models for Clustered Data
4.30pm Meeting Close

Getting to the CORE of CDISC

Speaker: Dr Elisa Young (Accelegan)

Abstract: The impact of CDISC standards, guidelines and initiatives on statistical programming over the last decade has been nothing short of revolutionary, stretching across clinical, non-clinical and observation science.  CDISC is on a continuous journey of change, with the aim of delivering new sources of data and technology platforms.  These objectives are being realised through organisational collaborations and, most importantly, a global network of volunteers.  During this presentation I’ll be discussing my experience as a volunteer on the CDISC CORE initiative, including a demonstration of the conformance validator.  I’ll also provide an update on other key CDISC initiatives.


Biography: Elisa is the Head of Biostatistics at Accelagen.  Elisa earned a PhD in Pharmacology, followed by a Masters’ in Applied Statistics, and worked in various roles within the biotech/pharma industry, from laboratory management, bench-top science, project management and data management, before settling on a career in statistics and statistical programming.  With a keen interest in CDISC, Elisa was the first Australian to obtain CDISC Tabulate Certification and is currently volunteering on the CDISC Core Project.

Flexible models for clustered data

Speaker: Dr Helen Ogden (University of Southampton)

Abstract: A wide variety of approaches are available for modelling clustered data: from assuming a single shared model for all clusters to fitting entirely separate models for each cluster. Random effects models lie between these two extremes, allowing simple variation in the model for each cluster, such as shifting a global response curve up or down by a constant (random intercept) or straight line (random slope). When the global response curve is not a straight line, these simple models sometimes fail to capture the variation in the shape of the cluster-specific response curves. I will give examples of this problem, and describe an extension to the simple random effects model which is designed to capture other types of variation.

Biography: Helen Ogden is a Lecturer in Statistics at the University of Southampton and a Fellow of the Alan Turing Institute for Data Science and Artificial Intelligence. Before that, she was a Research Fellow at the University of Warwick. Her research interests are in statistical modelling, theory and computation, with particular interest in mixed-effects models, models for count data, and conducting inference when the likelihood function is intractable.

4-5th November 2019,  2-Day workshop:

Network meta-analysis and population adjustment for decision-making 

Presented by David Phillippo at the Macquarie University Sydney Campus


Day 1:

  • Day 1 of this course is aimed at statisticians, health economists, decision-makers, and systematic reviewers who are already familiar with pairwise meta-analysis, and who want to extend their knowledge to NMA and population adjustment methods. Participants will develop an understanding of these methods and the required assumptions and learn to assess and critique these types of analyses.

Day 2:

  • Day 2 is aimed at those with technical experience of meta-analysis who want to apply the knowledge learned on Day 1 to hands-on practical examples. Participants will gain experience implementing NMA and population-adjusted analyses in an R package based on the Bayesian modelling language Stan.

Network meta-analysis (NMA) is a method for combining evidence from several studies on multiple treatments of interest to provide a consistent set of relative effect estimates and is widely used for healthcare decision-making and guideline development. More recently, population adjustment methods have been proposed that use individual patient data from one or more studies to relax the assumptions of NMA and adjust for differences in effect modifying variables between populations, or even to incorporate disconnected networks and single-arm studies. The methods are becoming increasingly common in technology appraisal submissions to reimbursement agencies and raise new questions and challenges for analysts anddecision-makers.

Our workshop presenter is David Phillippo, a Senior Research Associate in Statistics at the University of Bristol, UK. His research focuses on methodology for evidence synthesis, Bayesian Network Meta-Analysis (NMA), population adjustment methods for indirect comparisons, and accounting for bias in clinical guidelines. He is the lead author of a recent Technical Support Document published by the NICE Decision Support Unit on population-adjusted indirect comparisons, and has developed new methods extending the NMA framework to incorporate population adjustment combining individual patient data and published summary data.

For more information and to register, please click

15th August:FREE Statistics Mid-Year seminar - Hurry Places are limited

When: 15 August 2019, presentations go from 1pm-4pm

Where: Eli Lilly and Company, 112 Wharf Road, West Ryde



1. Reflections of a statistician on health economic modelling in the Australian context. 

Manjula Schou (Biostatistician /Research Fellow, Janssen-Cilag/Department of Mathematics and Statistics at Macquarie University, Sydney)

Manjula Schou has over 20 years of experience working as a statistician, predominantly in the pharmaceutical industry. She currently splits her time between Janssen-Cilag where she works within the Health Economics, Outcomes Research and Pricing team as a health economic modeller and company wide statistician, and the Department of Mathematics and Statistics at Macquarie University as a Research Fellow. In her later capacity Manjula's research interests are mainly focused on clinical trials methodology and statistical methods for health economic modelling. 

2. The application of machine learning to personalise the care and treatment of substance use disorders.

Chrianna Bharat (Biostatistician, PhD Candidate ,National Drug & Alcohol Research Centre, Sydney)

Chrianna Bharat is a PhD Candidate at the National Drug and Alcohol Research Centre, UNSW Sydney. Chrianna’s research project focuses on the use of routinely collected data to develop predictive models to optimise treatment outcomes among people with alcohol and drug problems. After receiving her bachelor’s degree with Honours in applied statistics from the University of Western Australia, Chrianna worked as a statistical consultant for the Centre of Applied Statistics. For the past three years, Chrianna’s role as biostatistician for the Substance Use Disorder (SUD) Workgroup of the World Mental Health Survey Initiative has seen her analysing complex survey data to determine the prevalence, risk factors and treatment needs for SUDs. 

Substance use disorders (SUDs) are a major contributor to the global burden of disease. Recently, the United Nations marked strengthening the prevention and treatment of SUDs as a public health priority. With machine learning methods increasingly being applied to healthcare data to support the delivery of personalised medicine, there exists the potential to use these methods to improve the processes of detecting, classifying and treating SUDs. The development of machine learning algorithms to predict SUD onset and treatment outcomes could facilitate the implementation of targeted prevention, increase SUD treatment coverage and personalise treatment allocation.

This presentation will provide a brief overview of machine learning applications in the field of alcohol and drug use disorders and describe the application of a machine learning algorithm for predicting individuals at high risk of developing an alcohol use disorder.

3. Some insights on state of the art of evidence synthesis.(Advances in meta-analysis) 

Gian Luca Di Tanna (Head of Statistics Australia at the George Institute for Global Health, Sydney)

Dr Gian Luca Di Tanna is currently the Head of Statistics Australia at the George Institute for Global Health in Sydney. He has an Honours in Statistics along with a Post-graduate specialization in Medical Statistics and has obtained an MSc in Data Intelligence & Decision Making and a PhD in Health economics (Catholic University of the Sacred Heart, Italy). His Academic positions include the Sapienza University of Rome, London School of Hygiene and Tropical Medicine and the Queen Mary University of London. Dr Gian Luca Di Tanna has worked until March 2019 as a Global Health Economics Senior Manager at the Economic Modelling Centre for Excellence for Amgen, Switzerland and is affiliated with the Riskcentre - Dept. of Econometrics, Statistics and Applied Economics at the University of Barcelona, Spain. He is on the Editorial Board of the journal PharmacoEconomics, Statistical Editor of the Consumers and Communication Cochrane group and member of the Cochrane Methods Group in Systematic Reviews and Meta Analysis.

I take the opportunity of this talk to comment on the current trends in systematic reviews and highlight “established” statistical methods for meta analysis with a particular focus on some issues/assumptions that go commonly overlooked. I will illustrate the various types of meta analysis (aggregate and individual patient data, head-to-head and network meta analysis), how to deal with different study designs and discuss potential misconceptions and warnings.

Please RSVP if you plan to attend for catering purposes & entry to the building – by 26 July to myself at

>  2015. DMC Workshop.
Presenter: Dr Simon Day

Location:  CBD , Sydney. TBD

Date:  26-27th February 2015


Course Description: The course is relevant to all those (statisticians and non-statisticians) who need to set up DMCs and work with them throughout the course of a clinical trial.  It is also relevant to those who may serve as members of DMCs. It will focus on practical issues around the workings of data monitoring committees (DMCs) including a review of group sequential methods and FDA and CHMP guidance on DMCs. Throughout the course, mock DMC sessions will be convened where various scenarios will be considered and discussed, and decisions have to be made.

>  2015. The use of modern causal inference methods in analysing RCTs Workshop.

Presenter: Dr Richard Emsley (Centre for Biostatistics, Institute of Public Health,
University of Manchester, UK)


Location:  MGSM conference centre at 37 Pitt St in the CBD in Sydney

Date:  6th December 2015

Time: TBD


This talk will be from 4:30pm to 5:30pm, at the MGSM conference centre at 37 Pitt St in the CBD in Sydney. We will be heading to dinner afterwards with the speaker if you would like to join also (at your own expense).

Prior to the talk we will be holding our AGM (from 3:30, afternoon tea from 3pm). If you are, or would like to become an APBG member, we would love for you to attend this also.  APBG members must work in the regulated healthcare area in statistics or a related field – please let us know if you would like to join.

Please RSVP to myself indicating if you will be attending the talk, the AGM or both.

For more information on the APBG (including the slides from the event you attended) please visit our website

>  2014. APBG AGM

Location: Room 23, Level 4, Building 2, UTS - Room 2.4.23. 15 Broadway, Ultimo, NSW, 2007

Date: Tuesday 28 October 2014

Time: 5pm-6pm then

Talk by Professor John Carlin, Murdoch Children’s Research Institute & The University of Melbourne

Talk Topic : Assessing the risk of a rare adverse outcome following rotavirus vaccination: a case study in biostatistical methods and collaborative engagement


Location: Room 6, Level 4, Building 2, UTS Tower building- Room 2.4.6. 15 Broadway, Ultimo, NSW, 2007

Date: Tuesday 28 October 2014

Time: 6:30pm-7.30pm (Refreshments from 6pm)


>  2014 Do pharmacological interventions reduce drugs-related deaths ?

Speaker, Professor Sheila M Bird. MRC Biostatistics Unit, Institute of Public Health, Cambridge, UK


Date: 2nd July 2014

Time: 6-7.30pm

Venue: The Sebel Hotel. 28 Albion St Sydney 2012



>  2012.  Mixed Treatment Comparisons

Date: 4th 5th June 2012

Venue:MGSM Executive Hotel and Conference Centre. 99 Talavera Rd, Macquarie Park 2113 Tel. 02 9850 9082

Details: This workshop on Mixed Treatment Comparisons (MTC) is proudly supported by the Australian Pharmaceutical Biostatistics Group (APBG) and the Statistical Society of Australia (SSAI).
The workshop utilises the expertise of Professor George Wells form the Department of Epidemiology and Community Medicine Director, University of Ottawa Heart Institute.

Day 1 will be a high level overview on MTCs and their applications. There will be demonstrations of worked examples using SAS and Win BUGs. A brief outline includes: Introduction to indirect treatment comparisons Network meta-analysis methods

     Part 1: Bucher approach and the Frequentist network meta-analysis - general linear mixed models Network meta-analysis methods

     Part 2: Bayesian network meta-analysis - mixed treatment comparisons Worked example - Bayesian network meta-analysis Worked example -  
    Frequentist network meta-analysis

Day 2: will be more practical hands on session with applications of what was taught in Day 1.
There will be several breakout sessions where groups will work through examples and present back.
The day will conclude with limitations and future research.

Programs: Detailed Program Registrations: Register from SSAI Website



> 2011.  Adaptive Designs for clinical trials

Date: 6-7th April 2011

Venue: MGSM Executive Hotel and Conference Centre. 99 Talavera Rd, Macquarie Park 2113 Tel. 02 9850 9082


Details: This workshop on adaptive design is proudly supported by the Australian Pharmaceutical Biostatistics Group (APBG), the Statistical Society of Australia (SSAI) and the George Institute.This workshop takes advantage of Dr Brenda Gaydos’ visit to Australia. Brenda is the Eli-Lilly specialist in adaptive designs, has a wealth of experience to share and has written several papers including one on Good Clinical Practice in this area. She will team-up with two leading researchers in adaptive designs, Dr Patrick Kelly of Sydney University, and Dr Frank Bretz of Novartis, Switzerland. Frank is an adjunct professor of the University of Hannover (Germany), and has published more than 100 papers and two books on multiplicity issues.


Programs: Detailed Program Registrations: Register from SSAI Website



> 2009.  Challenges of running oncology clinical trials

Date: Thursday, 26 November 2009

Venue: Coles Theatre, School of Business, University of Melbourne, Australia

Details: This workshop is your opportunity to share your experiences and challenges of working on clinical trials in oncology. The workshop aims to take you through some of the stages during the execution of a clinical trial in oncology. It will start with discussions around developing concept outlines and protocols for oncology studies, the designs of oncology clinical trials and the subsequent logistics from a statistical, monitoring and data management perspective. From there the focus will move to safety reporting and the use of data safety monitoring boards, the differences between MedDRA and CTC coding dictionaries and why you would use one rather than the other followed by how the TGA reviews oncology studies. After lunch the discussions will become more specific around the types of measures and the corresponding analyses and the benefits and pitfalls of using the RECIST criteria. The day will finish with some ideas on how to undertake a critical appraisal of the oncology literature and a look into the future promises and challenges of oncology studies with the exciting novel therapies.


Programs: Detailed Programs Registrations: Register from SSAI Website



> 2009.  ARCS 18th Annual Scientific Congress: Education into Practice

Date: 1-3 June 2009

Venue: Sydney Convention and Exhibition Centre, Australia

Details: The ARCS ASC is the premier Australian event for those involved in the development of therapeutic goods. With the theme "Education Into Practice" the 2009 ASC is focused on ensuring the transfer of knowledge into practice, with tangible take-home messages to improve professional performance.


>2008.  Statistical estimates of benefits and hazards of Hormonal Therapy post-menopause: reconciling observational and trial data

Date: Wednesday, 22 October 2008

Venue: Lecture Room 2.4.11, Building 2, University of Technology Sydney, Broadway, Sydney



> 2008.  Australian Statistical Conference 2008

Date: 30 June - 3 July 2008

Venue: Sofitel Melbourne, Melbourne




>2008.  From randomised trials to national policy decisions via cost-effectiveness analysis

Date: 8 July 2008

Venue: Pfizer Auditorium, 38-42 Wharf Rd, West Ryde, Sydney



> 2008.  Bayesian Methods in Health Economics

Date: 14 - 16 July 2008

Venue: TBC, Sydney



> 2008.  Workshop on integrating statistical ideas into mathematics

Date: 6 August 2008

Venue: Macquarie Graduate School of Management Conference Centre NSW

Details: SSAI Flyer Indirect Comparison Workshop [2007] The notes for the workshop can be downloaded here. 9.00 am

Session 1: Introduction to Indirect Comparisons - Philip McCloud 10.30 am

Session 2: Design and Interpretation Issues - Philip McCloud 11.00 am

Session 3: The use of Indirect comparisons to compliment RCT evidence – Bill Montgomery & Kristina Coleman 11.30 am

Session 4: Are all comparators Identical? - Philippa Clarke 1.00 pm

Session 5: Sources of Variation: fixed or random? - Philip McCloud 1.30 pm

Session 6: Random effects and Bayesian Methods – Patrick Fitzgerald 3.00 pm
Session 7: Double Comparators: twice the fun? - Annie Solterbeck


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