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1 training programme in pharmaceutical medicine Clinical Data Management and Analysis may 2011

2 Clinical Data Management and Analysis MAY 2011 LocaL: University of Aveiro, Campus Universitário de Santiago curricular unit Leaders: Vera afreixo, Phd Pedro sá couto, Msc Lecturers: Vera Afreixo, Luís Almeida, Pedro Sá Couto, Pedro Noronha, Rui Sousa organisation: Mestrado em Biomedicina Farmacêutica (Masters in Pharmaceutical Biomedicine) curso de especialização em Medicina Farmacêutica de Longa duração (Post-Graduate Course in Pharmaceutical Medicine) Director: Luis Almeida, MD, PhD, FFPM Deputy Director: Bruno Gago, PharmD, PhD ua.pt) address: Secção Autónoma de Ciências da Saúde (SACS) Universidade de Aveiro Campus Universitário de Santiago Edifício III Aveiro Portugal Tel Fax

3 DAY MAy time Programe Lecturer 0. introduction 10h00-10h Reasons for studying clinical data management and analysis (biostatistics).0.2. Objectives and outcomes. 1. Basic Principles of epidemiology Vera Afreixo, 10h30-12h Introduction to epidemiological thinking Measuring health and disease Initial steps in designing a biomedical study Common types of epidemiological studies Rating studies by the level of evidence. Rui Sousa (BIAL) 12h00-12h45 12h45-14h00 14h00-16h00 2. Population and samples 2.1. Types of samples Methods of selecting simple random samples Application of sampling methods in biomedical studies. (Lunch) 3. data Management 3.1. Decide what data you need Options for data collection (manual and electronic) Case report form (CRF) design and review Creation, maintenance and security of database, software validation, and archiving From source documents to CRF completion, CRF review and corrections, data entry, query generation and resolution, coding of adverse events, database lock Data standards (CDISC) and data quality. 4. Frequency tables and graphs Rui Sousa (BIAL) Pedro Noronha (Eurotrials) 16h15-17h Numerical methods of organizing data Graph types. Vera Afreixo (UA) 5. Measures of location and variability 17h00-18h The arithmetic mean, median and other measures of variability The variance, standard deviation and other measures of variability Sampling properties of the mean and variance Selecting appropriate statistics Graphical methods of displaying statistics. Vera Afreixo (UA)

4 DAY MAy time Programe Lecturer 6. the normal distribution 09h00-10h00 10h00-11h15 11h30-13h00 13h00-14h Properties and importance of normal distribution Examining data for normality Transformations. 7. estimation of population means: confidence intervals 7.1. Confidence intervals: definition, choice of confidence level Sample size needed The t distribution and confidence interval for the mean Estimating the difference between two means: unpaired data and paired data. 8. test of hypothesis on population means 8.1. Test of hypothesis for a single mean Tests for equality of two means: unpaired data and paired data Sample size needed The t distribution and confidence interval for the mean Estimating the difference between two means: unpaired and paired data Concepts used in statistical testing Sample size Confidence intervals versus tests Correcting for multiple testing Reporting the results (Lunch) 9. Variances: estimation and tests 14h30-15h Point estimates and standard deviations Testing. Vera Afreixo (UA) 10. categorical data: proportions 15h30-16h45 17h00-18h Single population proportion Samples from categorical data The normal approximation to the binomial Confidence intervals for a single population proportion and for the difference in two proportions Tests of hypothesis Sample size. 11. categorical data: analysis of two-way frequency tables Different types of tables Relative risk and odds ratio Chi-square tests. Vera Afreixo (UA) Vera Afreixo (UA)

5 DAY MAy time Programe Lecturer 12. regression and correlation 09h00-10h Scatter diagram Linear regression Correlation coefficient. Pedro Sá Couto (UA) 10h45-12h30 12h30-14h00 14h00-15h nonparametric statistics Sign test Wilcoxon signed ranks test Wilcoxon-Mann- Whitney test Spearman s rank correlation. (Lunch) 14. survival analysis Survival analysis data Survival functions Computing estimates (clinical life tables and Kaplan-Meier estimate) Comparison of clinical life tables and the Kaplan-Meier method Other analysis using survival data. 15. study reporting Pedro Sá Couto (UA) Vera Afreixo (UA) 15h45-17h Report planning Report writing Luis Almeida (UA)

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