Downloaded 23 times
Uploaded byAayam Gupta
Epidata Course 0 1-title
This document outlines the course content for a training course on using EpiData software for operations research in tuberculosis control. The course is divided into 5 parts that cover quality data capture and management using EpiData Manager and EpiData Entry, analysis using EpiData Analysis, operations research exercises, additional EpiData features, and introducing R software. Each part includes multiple exercises for participants to complete to learn how to use the various EpiData and R tools. The course content is periodically updated when new versions of EpiData software are released.
Epidata Course 0 1-title
- 1. EpiData Software forOperations Research in Tuberculosis Control A course developed by the EpiData Association Authors: Hans L Rieder, Kirchlindach, Switzerland Jens M Lauritsen, Odense, Denmark The input with major contributions to current content and recent revisions is greatly acknowledged: Nguyen Binh Hoa, Hanoi, Viet Nam Ajay M V Kumar, Bengaluru, India Zaw Myo Tun, Singapore
- 2. course_0-1_title Page 2 of3 Date last revised: July 21, 2015 Note on versions of EpiData software: Always use the most recent release version of EpiData software which can be obtained freely from the EpiData website http://www.epidata.dk. The course is updated at least whenever a new version requires adaptation or following an in-class course, whichever comes earlier.
- 3. course_0-1_title Page 3 of3 Course content Part A: Quality-assured data capture with EpiData Manager and EpiData EntryClient Exercise 1 A data documentation sheet for a simple questionnaire Exercise 2 Create a basic data entry form Exercise 3 Create a value-label pair from external data Exercise 4 Create a composite identifier Exercise 5 Data entry and validation Exercise 6 Upgrading an EpiData 3.1 REC/CHK file pair to an EPX file Exercise 7 Relational database Part B: EpiData Analysis Exercise 1 An introduction to EpiData Analysis Exercise 2 More on EpiData Analysis Exercise 3 Aggregating data and saving the summary data in a file Part C: Operations research Exercise 1: Creating a working dataset Exercise 2: Variability in serial smears Exercise 3: Incremental yield from serial smears Exercise 4: Confirmatory results in serial smears Part D: More on EpiData software Exercise 1: Relational database and aggregating vs from “Long-to-wide” Exercise 2: A statistical process control chart Exercise 3: A simplified survival analysis Exercise 4: Creating a menu for standard reports Exercise 5: Formatting standardized analysis output in a spreadsheet Part E: Beyond EpiData Analysis using R Exercise 1: Introduction to R software: basics Exercise 2: Introduction to R software: data bases and functions Exercise 3: Multivariable analysis in R part 1: A logistic regression Exercise 4: Multivariable analysis in R part 2: A Cox proportional hazard model