Biostatistics

PHAR69931 Biostatistics 15 Semester 1 Postgraduate Taught Level 7 Leon Aarons Unit coordinator 1 FHEQ level (Framework for Higher Education Qualifications) ' Masters/Integrated Masters P4 ' European Credit Transfer & Accumulation System Rating : 7.5 This unit is designed to give the student an understanding of fundamental statistical concepts that are routinely used in designing clinical trials or interpreting trial results.Emphasis is given to the use of simple hands-on exercises to build confidence in the application of concepts and in the practical use of software for statistical problem solving.This unit is a prerequisite for the subsequent unit (PHAR69923) on advanced approaches to data analysis, including mixed effects models and population pharmacokinetics.Theoretical knowledge will be disseminated first by lecture, but the unit will emphasise the application of theory by solving problems in workshops and coursework assignments. Some of the assignments will be computer based, to ensure students are comfortable with basic software for data analysis and presentation before encountering more specialised software in subsequent units.    Students will complete exercises using Microsoft Excel and will also be introduced to more specialised software such as R. This unit is designed to give the student an understanding of fundamental statistical concepts that are routinely used in designing clinical trials or interpreting trial results.Emphasis is given to the use of simple hands-on exercises to build confidence in the application of concepts and in the practical use of software for statistical problem solving.This unit is a prerequisite for the subsequent unit (PHAR69923) on advanced approaches to data analysis, including mixed effects models and population pharmacokinetics.Theoretical knowledge will be disseminated first by lecture, but the unit will emphasise the application of theory by solving problems in workshops and coursework assignments. Some of the assignments will be computer based, to ensure students are comfortable with basic software for data analysis and presentation before encountering more specialised software in subsequent units.    Students will complete exercises using Microsoft Excel and will also be introduced to more specialised software such as R. The unit aims to:<ul> <li>introduce statistical concepts applied in the design of clinical trials and interpretation of clinical results in drug development</li> <li>provide practice in applying statistical methods to typical clinical trial data.</li></ul> Students should be able to: <ul> <li>define and apply the statistical terms relevant to clinical trial data collection and interpretation</li> <li>explain the crucial roles biostatistics in guiding the design and conduct of clinical trials.</li></ul> Students should be able to: <ul> <li>apply basic biostatistical concepts and interpret statistical information arising from clinical trials</li> <li>perform power calculations and apply them in the design of a clinical trial</li> <li>understand the statistical terms presented in clinical trial documents.</li></ul> Students should be able to: <ul> <li>use computer software such as Excel or R to perform basic computational tasks including file input/output, calculations, and production of effective graphs.</li></ul> <ul> <li>Independent learning.</li> <li>Mastering new software.</li></ul> Basic statistical concepts and definitions:<ul> <li>types of data</li> <li>probability concepts</li> <li>estimation</li> <li>confidence intervals</li> <li>hypothesis testing/ significance testing.</li></ul>Trial design:<ul> <li>choice of variables</li> <li>control groups</li> <li>randomisation</li> <li>blinding</li> <li>sample size and power.</li></ul>Statistical  analysis methods:<ul> <li>types of variables</li> <li>time to event data.</li></ul>Statistical analysis issues.The statistical analysis plan (SAP) in clinical research. <ul> <li>Lectures.</li> <li>Workshops, entailing guided sequences of analyses with interactive discussion with tutor.</li> <li>Directed reading.</li> <li>Formative-assessed calculation-based coursework (pass/fail).</li> <li>Summative-assessed calculation-based coursework.</li></ul> 0 Other 100% <figure class="table"><table style="width:500px;" border="1" cellpadding="1" cellspacing="1"><thead><tr><th scope="col">Assessment</th><th scope="col">Length</th><th scope="col">Feedback</th><th scope="col">Weighting</th></tr></thead><tbody><tr><td>Formative assessments x 4 </td><td>8 hours</td><td>Model answer presented in tutorial</td><td>N/A (just need to submit)</td></tr><tr><td>Biostatistics problems x 3 coursework</td><td>20 hours</td><td>Online feedback within standard time</td><td>100%</td></tr></tbody></table></figure> MSc MBDD (PT) MSc MBDD (PT) PGDT Taught Component Mandatory MSc MBDD MSc MBDD PGDT Taught Component Mandatory N <ul> <li>ICH E9 Statistical Principles for clinical trials.  ICH E9 Statistical Principles for clinical trials. </li> <li>Senn S. Statistical Issues in Drug Development. John Wiley & Sons. Chichester. 1997.</li> <li>Armitage P, Berry, G, Mathews JNS. Statistical Methods in Medical Research. Blackwell Publishing, Oxford. 2002.</li> <li>BMJ statistics notes. (Altman et al.).</li></ul> Lectures 10 Seminars 20 Tutorials 4 0 116