1. Entering Data for Analysis Annie Herbert Medical Statistician Research & Development Support Unit Salford Royal (Hope) Hospitals NHS Foundation Trust annie.herbert@manchester.ac.uk 0161 20 64567 Sept 2009 (v.2)

2. Timetable TimeTask 60 mins Presentation (Trust Library Meeting Room) 20 minsCoffee Break 90 mins Practical Tasks (Trust Library IT Room)

3. Outline ENTERING DATA: Data Format Missing Data Anonymity STATSDIRECT: Layout Re-coding Variables Transforming Variables Categorising Variables

4. Spreadsheets

5. Things to remember: Variable names: Keep short SPSS : No spaces, may use underscore, e.g. ‘dose_1’ Categories: Give each category a numerical code e.g. medical = 1, surgical = 2, other = 3

6. Format No mixture of variables per column e.g. blood pressure, rather than 180/60 have a column for diastolic and a column for systolic Format columns for dates, money, etc. e.g. two decimal places for money Make sure that the program recognises whether the variables are continuous or categorical

7. Units Do not enter with data May put in variable name e.g. ‘weight_kg’ No mixtures of units per column e.g. in 100’s and then switch to in 1000’s

8. Group Identifiers

9. Missing Data StatsDirect : use ‘*’ SPSS : use invalid value, e.g. ‘999’ for age If not using ‘*’, make sure that the package identifies such values as missing and not a real observation

10. Anonymity Each patient/unit in the study should be given a unique ID code Nobody outside the care-team should be able to identify the patient (e.g. statistician) Violation of Data Protection Act if carrying identifiable data on disc/CD/laptop

11. Transforming Data Definition: Making a new variable by applying a formula to one (or more) existing variables. Uses: Calculating a new variable, e.g. the difference between pain at 6 months and pain at baseline. Changing units, e.g. turning days into weeks. Taking natural logarithms in attempting to make data symmetric.

12. Recoding Data Definition: Changing existing numbers into different ones Uses: Changing text to numbers, e.g., Female = 0, Male = 1 Changing a coding system, e.g., Female = 1 -> 0, Male = 2 -> 1 Combining categories, e.g., Strongly Disagree = 0 & Disagree = 1 ->Negative Response = 0 Agree = 2 & Strongly Agree = 3 ->Positive Response = 1

13. Categorising Data Definition: Converting a continuous variable to a categorical one. E.g., Less than 30 years = 1 30-50 years = 2 51 years and over = 3

14. Special Types of Study Questionnaires: One row per questionnaire One or many columns per question, depending on number of answer options Repeated Measures: One row per person One column per measure Seek statistical advice

15. Available Packages PackageAdvantagesDisadvantages SPSS Journal-quality graphs Difficult to use at first Expensive Need license StatsDirect Easy to use Cheap Need license Excel Comes with Microsoft Office Good for data entry Not good for statistical analyses

16. StatsDirect

17. Data can be entered and stored in a ‘Workbook’:

18. Plots, tables and analyses can be shown in a ‘Report’:

19. You can work between many workbooks and reports at a time:

20. Analyses are carried out using the menu headings:

21. A prompt will appear at each stage:

22. You’ll be asked to select the relevant data:

23. Transforming Variables (1): 1) 2) 3) 4)

24. Transforming Variables (2): 5) 6)

25. Recoding Variables (1): 1) 2) 3)

26. Recoding Variables (2): 4) 5)6)

27. Categorising Variables (1): 1) 2) 3)

28. Categorising Variables (2): 4)i. 5) 4)ii. 4)iii.