1. Biostatistics in Research Practice Dr Victoria Allgar

2. Course structure Lecture of key concepts Lecture of key concepts Practical on SPSS for most sessions except: Practical on SPSS for most sessions except: –Multi-level modelling –Meta analysis Course material available from my web area: http://www-users.york.ac.uk/~va507/ Course material available from my web area: http://www-users.york.ac.uk/~va507/http://www-users.york.ac.uk/~va507/ Any questions or problems you can contact me on ext: 1384 or e-mail: victoria.allgar@hyms.ac.uk Any questions or problems you can contact me on ext: 1384 or e-mail: victoria.allgar@hyms.ac.uk

3. Lecturers Victoria Allgar - Senior Lecturer in Medical Statistics, HYMS/Health Sciences Victoria Allgar - Senior Lecturer in Medical Statistics, HYMS/Health Sciences Simon Crouch - Research Fellow, Eplidemiology and genetics unit Simon Crouch - Research Fellow, Eplidemiology and genetics unit Gill Worthy - Research Fellow, Centre for Reviews and Dissemination Gill Worthy - Research Fellow, Centre for Reviews and Dissemination Kate Pickett - Lecturer in Epidemiology, Health Sciences Kate Pickett - Lecturer in Epidemiology, Health Sciences Martin Bland - Professor of Health Statistics, Health Sciences Martin Bland - Professor of Health Statistics, Health Sciences

4. Recap of applied biostatistics Frequency distributions Frequency distributions Mean and standard deviation Mean and standard deviation Significance tests Significance tests Standard error and confidence intervals Standard error and confidence intervals Comparing means: t-tests Comparing means: t-tests Chi-square tests Chi-square tests Proportions, risk ratios and odds ratios Proportions, risk ratios and odds ratios Correlation and regression Correlation and regression Multiple regression Multiple regression

5. Biostatistics in Research Practice Week 2: Review of inferential statistics Week 2: Review of inferential statistics Week 3: Non-parametric tests Week 3: Non-parametric tests Week 4: Regression and multiple regression Week 4: Regression and multiple regression Week 5: More multiple regression Week 5: More multiple regression Week 6: Categorical data: logistic regression Week 6: Categorical data: logistic regression Week 7: Multi-level modelling Week 7: Multi-level modelling Week 8: Time related data: survival analysis and Cox’s regression Week 8: Time related data: survival analysis and Cox’s regression Week 9: Meta analysis Week 9: Meta analysis

6. Week 2: Review of inferential statistics Practical session on SPSS Practical session on SPSS Drawing on the Applied Biostatistics module Drawing on the Applied Biostatistics module Keel free to ask questions or ask for clarification. Keel free to ask questions or ask for clarification. 1.15 – 4.15: Coffee break? 1.15 – 4.15: Coffee break?