Mixed models analysis of medical data using SAS 2019 Topics covered include: Day 1 General concepts and underlying statistical theory Use and interpretation of PROC MIXED Application in multi-centre trials Application in crossover trials Consideration of issues such as biased standard errors, significance testing and negative variance components Day 2 Application in repeated measures trials Random coefficients/slopes models Generalised linear mixed models (GLMMs) and PROC GLIMMIX Mixed models for ordinal data (overview) Use of mixed models for highly structured data Note the practical sessions will focus on constructing models and interpreting results from SAS output and will not involve "hands on" computer work. Who should attend? This course is directed at medical statisticians who wish to understand the statistical background to mixed models and to carry out analyses using SAS. Why attend? Conventionally, clinical data is analysed using fixed effects models. However, benefits can often be gained by using a mixed model. For example: in repeated measures trials full allowance can be made for the correlation occurring between the repeated observations even if data are missing; in multi-centre trials treatment standard errors are more appropriately based on between centre variation (fixed effects standard errors are based on within centre variation); in crossover trials more accurate treatment means are often achieved by combining within and between patient estimates. Suitable procedures are readily available for fitting these models well known packages such as SAS. This has led widespread application and knowledge of mixed models becoming essential for medical statisticians. As with any statistical technique a firm understanding of the theoretical background is essential to allow its effective application and to obtain a clear interpretation of results. Course fees Standard rate £650 Non-profit making institutions £450 Fees include daily morning coffee, lunch, afternoon tea, dinner on the first day, course notes and a copy of the text book "Applied Mixed Models in Medicine" (third edition, 2015) by Helen Brown and Robin Prescott. Members of the International Society for Clinical Biostatistics (ISCB) are entitled to a £25 reduction in the course fee. The speaker Helen Brown is the Senior Statistician at The Roslin Institute, University of Edinburgh, and has a research interest in mixed models. She has over thirty years of practical experience as a statistician mainly in medicine and the biosciences. Most of her career has been within academia but she also has experience within the pharmaceutical industry and the health service. She has co-authored three editions of the text book ‘Applied Mixed Models in Medicine’ and taught many short courses on mixed models both in Edinburgh and for external institutions. Venue The course will be held in the Holiday Inn, Edinburgh-West, one mile from the city centre and easily accessible from the main railway station and airport. Accomodation Course participants have the opportunity to stay at the Holiday Inn, Edinburgh-West at a discounted rate of £78 per night. To book at this rate please call the Holiday Inn Events Department on 0131 311 4903 and quote code U97 or email events@hiedinburgchitywest.com. Alternatively there are several other hotels and guest houses within walking distance of the Holiday Inn. Further information Email: mixed.models@ed.ac.uk Phone: 0131 651 2189 (option 2) Oct 30 2019 00.00 - Oct 31 2019 23.59 Mixed models analysis of medical data using SAS 2019 This course will cover the statistical background to the mixed model and will emphasise its practical application in medical data with particular reference to clinical trials. All analyses will be illustrated using SAS and lectures will be combined with practical sessions in order to reinforce concepts. Holiday Inn, Edinburgh-West Mixed Models Course website
Mixed models analysis of medical data using SAS 2019 Topics covered include: Day 1 General concepts and underlying statistical theory Use and interpretation of PROC MIXED Application in multi-centre trials Application in crossover trials Consideration of issues such as biased standard errors, significance testing and negative variance components Day 2 Application in repeated measures trials Random coefficients/slopes models Generalised linear mixed models (GLMMs) and PROC GLIMMIX Mixed models for ordinal data (overview) Use of mixed models for highly structured data Note the practical sessions will focus on constructing models and interpreting results from SAS output and will not involve "hands on" computer work. Who should attend? This course is directed at medical statisticians who wish to understand the statistical background to mixed models and to carry out analyses using SAS. Why attend? Conventionally, clinical data is analysed using fixed effects models. However, benefits can often be gained by using a mixed model. For example: in repeated measures trials full allowance can be made for the correlation occurring between the repeated observations even if data are missing; in multi-centre trials treatment standard errors are more appropriately based on between centre variation (fixed effects standard errors are based on within centre variation); in crossover trials more accurate treatment means are often achieved by combining within and between patient estimates. Suitable procedures are readily available for fitting these models well known packages such as SAS. This has led widespread application and knowledge of mixed models becoming essential for medical statisticians. As with any statistical technique a firm understanding of the theoretical background is essential to allow its effective application and to obtain a clear interpretation of results. Course fees Standard rate £650 Non-profit making institutions £450 Fees include daily morning coffee, lunch, afternoon tea, dinner on the first day, course notes and a copy of the text book "Applied Mixed Models in Medicine" (third edition, 2015) by Helen Brown and Robin Prescott. Members of the International Society for Clinical Biostatistics (ISCB) are entitled to a £25 reduction in the course fee. The speaker Helen Brown is the Senior Statistician at The Roslin Institute, University of Edinburgh, and has a research interest in mixed models. She has over thirty years of practical experience as a statistician mainly in medicine and the biosciences. Most of her career has been within academia but she also has experience within the pharmaceutical industry and the health service. She has co-authored three editions of the text book ‘Applied Mixed Models in Medicine’ and taught many short courses on mixed models both in Edinburgh and for external institutions. Venue The course will be held in the Holiday Inn, Edinburgh-West, one mile from the city centre and easily accessible from the main railway station and airport. Accomodation Course participants have the opportunity to stay at the Holiday Inn, Edinburgh-West at a discounted rate of £78 per night. To book at this rate please call the Holiday Inn Events Department on 0131 311 4903 and quote code U97 or email events@hiedinburgchitywest.com. Alternatively there are several other hotels and guest houses within walking distance of the Holiday Inn. Further information Email: mixed.models@ed.ac.uk Phone: 0131 651 2189 (option 2) Oct 30 2019 00.00 - Oct 31 2019 23.59 Mixed models analysis of medical data using SAS 2019 This course will cover the statistical background to the mixed model and will emphasise its practical application in medical data with particular reference to clinical trials. All analyses will be illustrated using SAS and lectures will be combined with practical sessions in order to reinforce concepts. Holiday Inn, Edinburgh-West Mixed Models Course website
Oct 30 2019 00.00 - Oct 31 2019 23.59 Mixed models analysis of medical data using SAS 2019 This course will cover the statistical background to the mixed model and will emphasise its practical application in medical data with particular reference to clinical trials. All analyses will be illustrated using SAS and lectures will be combined with practical sessions in order to reinforce concepts.
