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Use of EpiData (questionnaire design and entry). Jurgita Bagdonaite Jurmala, Latvia, 2006 Based on EPIET material. Introduction to EpiData. Data entry and documentation Free program Based on EpiInfo Windows format No limit on No of observation (tested with >100.000). EpiData (I).

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Use of EpiData (questionnaire design and entry)


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    1. Use of EpiData(questionnaire design and entry) Jurgita Bagdonaite Jurmala, Latvia, 2006 Based on EPIET material

    2. Introduction to EpiData • Data entry and documentation • Free program • Based on EpiInfo • Windows format • No limit on No of observation (tested with >100.000)

    3. EpiData (I) • Creating questionnaire • Controlled data entry • Documenting and printing data • Correction of questionnaires, records • Comparing of 2 data files • Importing and exporting data • Simple analysis

    4. EpiData (II) • Simple surveys – one questionnaire • Complicated surveys – few questionaires If there is ID – possible to merge data

    5. EpiData files • .QES file • Questionnaire • .REC file • Actual data • .CHK file • Any defined checks • Other notes or log files

    6. 1. Define Data 2. Make Data File 3. Set up Checks 4. Enter Data 5. Document 6. Export Data EpiData workflow

    7. Creating Questionnaire • Define Data • Can either open .QES file or create one

    8. New questionnaire • Type in window • Cut and paste from Word documents • Preview questionnaire • (click Make data file > preview data form)

    9. Structure of questionnaire Three sections: • Field name (variable) • Text describing field • Input definition (number/ letters/ date)

    10. Field name (variable) • No more than 10 characters • Begin with a letter • No spaces or punctuation marks

    11. Field Name (II) • First word • Uses first word of line • Automatic • EpiData generates field names based on question • Uses first 10 letters Childquest Child questionnaire <Y>

    12. Automatic field names • Text in curly brackets { } used in preference • Common words skipped (what, the, and, etc.) • If question starts with number, “N” is inserted before the number

    13. Automatic field names, examples Question: Field name: Did you {eat ice cream} EATICECREAM What is your name? ISYOURNAME 2. Age N2AGE

    14. Variable type • Define variables using “Pick List” or “Code writer” • Choose type of variable: • Numeric • Text • Date • Soundex • Boolean (Yes/No) • Autonumber

    15. Text variables • Information of text and/or numbers • Holding information (e.g. names, addresses) • UPPER CASE • Can only hold upper case (capital) letters • Lower case variable automatically converted into upper case text (ex: Egypt converted into EGYPT) • No mathematical operations • Length (How many characters) • <_>

    16. Numeric variables • Numerical information • Hold integers (whole numbers) or numbers with a decimal point • Length (digits, decimals after the comma) • <#>, <##.#>

    17. Other variables • Boolean variables (s. logical variables s. YES/NO variables) • only two possible answers: Yes or No • <Y> • Date variables: • Hold information on dates • Data in american <MM/DD/YYYY> • European <DD/MM/YYYY> • Soundex: • Coding of words (anonymous, eg. A-123) • Code to limit orthographic errors (eg. Rome and Roma) • <S >

    18. System variables • Values generated automatically • Today date: date of the data entry • <Today-dmy> • <Today-mdy> • Auto identification number: Counts the records entered • <IDNUM>

    19. Save Questionnaire • Preview data • Save questionnaire • Creates .QES file • Create Data file • Click Make Data file button > Make Data file • Creates .REC file • Questionnaire and Data file ready • But……

    20. Errors in data entry • Tranposition (ex: 39 becomes 93) • Copying errors (0 copy as an “o” letter) • Consistency errors: two or more responses are contradictory (sex: man, pregnancy=Yes) • Range errors: answers outside of probable or possible values (ex: heigh = 3 metres)

    21. Preventing errors • Standardised and previously tested questionnaire • Training the interviewers and data entry clerck • Checking and validating paper forms of the questionnaires • Checking during the data entry (Check module Epi-Data) • Validation: entering twice data by different operators • Checking after data entry (Analysis module Epi-Info)

    22. Checks (I) • Reduce errors in input • Checks help with data entry • Many different types • Examples: • Limit entry of numbers to specific range • Forcing entry to be made in field • Conditional jumps • Copying the data from the previous record • Help messages • Conditional operations (ex if….then operations)

    23. Checks (II) • Once Data file is created: • Click Checks button > choose .REC file

    24. Checks (III) • Range, legal: • 1-3, 9 • First range then individual numbers • Tallinn, Riga, Vilnius • Fixing only min or max value • -INF-5 (all numbers inferior or equal 5) • 0-INF (all positive numbers superior or equal to 0) • Jumps: • Field: AGEYEARS • 0>AGEMONTHS • 0>AGEMONTHS, 1>ADDRESS • 1>END • MustEnter: • Data must be entered in Field

    25. Checks (IV) • Repeat: • Show data from previous record • Value Label • Add text to explain values • Click + to add label • Format as shown • Press F9 during data entryto see labels

    26. Data Entry (I) • Click Enter data button > choose .REC file • Dates: • 15/5/2006 – type 150506 or 15/5/06 • Value Labels: • Press F9 to view

    27. Data Entry (II) • Record navigation: • Delete records: • Click cross to delete • Record marked for deletion, but can be recovered

    28. Document Tools • File Structure • Data entry notes ( .NOT file) • Use to write comments during data entry eg: difficult to read handwriting etc • View Data • List Data • Codebook • Basic descriptive statistics on all variables • Validate duplicate files • Check consistency after double entry

    29. Export to other programs • Click Export data button • Choose program • Including Excel, Stata, SPSS • For Epi-info open .REC file directly

    30. References • Lauritsen JM & Bruus M. EpiData (version 3.1). A comprehensive tool for validated entry and documentation of data. The EpiData Association, Odense Denmark, 2004. • Lauritsen JM, Bruus M. EpiTour - An introduction to validated dataentry and documentation of data by use of EpiData. The EpiData Association, Odense Denmark, 2005.

    31. www.epidata.dk