Data editing ( In research methodology )

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  • BY ALOYSIUS INSTITUTE OF MANAGEMENT AND TECHNOLOGY(AIMIT) MBA STUDENTS
  • BY ALOYSIUS INSTITUTE OF MANAGEMENT AND TECHNOLOGY(AIMIT) MBA STUDENTS
  • BY ALOYSIUS INSTITUTE OF MANAGEMENT AND TECHNOLOGY(AIMIT) MBA STUDENTS
  • BY ALOYSIUS INSTITUTE OF MANAGEMENT AND TECHNOLOGY(AIMIT) MBA STUDENTS
  • BY ALOYSIUS INSTITUTE OF MANAGEMENT AND TECHNOLOGY(AIMIT) MBA STUDENTS
  • BY ALOYSIUS INSTITUTE OF MANAGEMENT AND TECHNOLOGY(AIMIT) MBA STUDENTS
  • BY ALOYSIUS INSTITUTE OF MANAGEMENT AND TECHNOLOGY(AIMIT) MBA STUDENTS
  • BY ALOYSIUS INSTITUTE OF MANAGEMENT AND TECHNOLOGY(AIMIT) MBA STUDENTS
  • BY ALOYSIUS INSTITUTE OF MANAGEMENT AND TECHNOLOGY(AIMIT) MBA STUDENTS
  • BY ALOYSIUS INSTITUTE OF MANAGEMENT AND TECHNOLOGY(AIMIT) MBA STUDENTS
  • BY ALOYSIUS INSTITUTE OF MANAGEMENT AND TECHNOLOGY(AIMIT) MBA STUDENTS
  • Data editing ( In research methodology )

    1. 1. Data editingIN RESEARCH METHODOLOGY
    2. 2. Data editing
    3. 3. Data integrity refers to the notion that the data file actuallycontains the information that the researcherneeds to provide the decision maker data integrity extends to the fact that the datahave been edited and properly coded Any errors harm the integrity of the data.
    4. 4. Editing Fieldwork often produces data containingmistakes How long have you lived at your currentaddress? 48 What is your age? 32 years This answer contradicts the earlier response.If the respondent is 32 years of age, then howcould he or she have lived at the sameaddress for 48 years?
    5. 5.  Therefore, an adjustment should be made toaccommodate this information The most likely case is that this respondenthas lived at the current address for four years This example illustrates data editing
    6. 6.  Editing is the process of checking andadjusting data for omissions, consistency,and legibility So, the editor’s task is to check for errors andomissions on questionnaires or other datacollection forms. When the editor discovers a problem, he orshe adjusts the data to make them morecomplete, consistent, or readable.
    7. 7. Field Editing Field supervisors often are responsible forconducting preliminary field editing on thesame day as the interview USES 1.Identify technical omissions such as a blankpage on an interview form 2. Check legibility of handwriting for open-ended responses 3. Clarify responses that are logically orconceptually inconsistent.
    8. 8.  Field editing is particularly useful whenpersonal interviews have been used to gatherdata. A daily field edit allows supervisors to dealwith some questions by asking interviewers,who may still be able to remember theinterviews, about facts that may allow errorsto be identified and perhaps corrected A daily field edit allows fieldworkers to identifyrespondents who should be recontacted to fillin omissions in a timely fashion.
    9. 9.  For example, if an interviewer did notcorrectly follow skip patterns, training may beindicated. The supervisor may also notice that aninterviewer is not properlyprobing some open-ended responses. Defn:Preliminary editing by a field supervisoron the same day as the interview to catchtechnical omissions, check legibility ofhandwriting, and clarify responses that arelogically or conceptually inconsistent
    10. 10. In-House Editing In-house editing rigorously investigatesthe results of data collection The research supplier or researchdepartment normally has a centralized officestaff perform the editing and coding function
    11. 11.  Arbitron measures radio audiences by havingrespondents record their listening behavior—time, station, and place in diaries The diaries are returned by mail, in-houseeditors perform usability edits in which theycheck that the postmark is after the last dayof the survey week, verify the legibility ofstation call letters (station WKXY could looklike KWXY) If the respondent’s age or sex is notindicated, the respondent is called to ensurethat this information is included
    12. 12. INCONSISTENCY Consider a situation in which a telephoneinterviewer has been instructed to interviewonly registered voters in a state that requiresvoters to be at least 18 years old. If the editor’s review of a questionnaireindicates that the respondent was only 17years old The editor’s task is to correct this mistake bydeleting this response
    13. 13.  In which of the following cities have youshopped for clothing during the last year? • San Francisco • Sacramento • San José • Los Angeles • Other _________ Please list the clothing stores where you haveshopped during the last two months.
    14. 14.  Suppose a respondent checks Sacramentoand San Francisco to the first question If the same respondent lists a store that has alocation only in Los Angeles in the secondquestion, an error is indicated These answers are obviously inconsistent.
    15. 15. TAKING ACTION WHEN RESPONSE ISOBVIOUSLY AN ERROR If solid evidence exists that points to the factthat the respondent simply failed to check LosAngeles then the response to the first question can bechanged A change should only be made whenmultiple pieces of evidence exist thatsome response is in error and when thelikely true response is obvious
    16. 16.  Many surveys use filter or “skip” questionsmethod A survey might involve different questions fora home owner than for someone who doesnot own a home if someone indicated that he or she did notown a home, yet responses for the homequestions are provided, a problem isindicated In cases like this, the editor should adjustthese answers by considering all answers tothe irrelevant questions as “no response” or“not applicable
    17. 17. Editing Technology computer routines can check for inconsistenciesautomatically. Thus, for electronic questionnaires,rules can be entered which prevent inconsistentresponses from ever being stored in thefile used for data analysis. These rules should represent the conservativejudgment of a trained data analyst. Some online survey services can assist in providingthis service.In fact, the rules can even bepreprogrammed to prevent many inconsistent
    18. 18. For ex:- if a person fills up data; a pop-up windowcan appear requiring the respondent to go back andfix an earlier incorrect response. Electronic questionnaires can also prevent arespondent from being directed to the wrong set ofquestions based on a screening question response.
    19. 19. Editing for Completeness Item non response is the technical term foran unanswered question on an otherwisecomplete questionnaire.Missing data results from item nonresponsive. Inmany situations the decision rule is to do nothingwith the missing data and simply leave the itemblank.
    20. 20.  However, when the relationshipbetween two questions is important,such as that between a question aboutjob satisfaction and one’s pay, theeditor may be tempted to insert a plugvalue. The decision rule may be to plug inan average or neutral value in eachinstance of missing data.
    21. 21. Editing Questions Answered Outof Order Another task an editor may face isrearranging the answers given to open-endedquestions such asmay occur in a focus group interview. The respondent may have provided theanswer to a subsequent question in his or hercomments to an earlier open-ended question. Because the respondent already had clearlyidentified the answer, the interviewer may nothave asked the subsequent question.
    22. 22.  If the editor is asked to list answers to allquestions in a specific order, the editor may movecertain answers to the section related to theskipped question.
    23. 23. Facilitating the Coding Process While all of the previously described editingactivities will help coders, several editingproceduresare designed specifically to simplify the codingprocess. For example,Respondents are often asked to circleresponses. Some times , a respondent mayaccidentally draw a circle that overlaps twonumbers. Such ambiguity is impossible with anelectronic questionnaire.
    24. 24. EDITING AND TABULATING“DON’T KNOW” ANSWERS In some situations the editor can separatethe legitimate “don’t knows” (“no opinion”) fromthe other “don’t knows.” The editor may try to identify the meaning ofthe “don’t know” answer from other data providedon the questionnaire. For instance, the value of a home could bederived from knowledge of the zip code and theaverage value of homes within that area.
    25. 25.  A computerized questionnaire can be setup to require a response to every question.Here, if a “no opinion” or “don’t know” opinion isnot made available, the result is a forced choicedesign.
    26. 26. Pitfalls of Editing Subjectivity can enter into the editing process.Data editors should be intelligent, experienced, andobjective. A systematic procedure for assessing thequestionnaires should be developed by theresearch analyst so that the editor has clearlydefined decision rules to follow. Any inferences such as imputing missingvalues should be done in a manner that limits thechance for the data editor’s subjectivity to influencethe response.
    27. 27. Pre-testing Edit Editing questionnaires during the preteststage can prove very valuable. For example, if respondents’ answers to open-ended questions were longer than anticipated, thefieldworkers, respondents, and analysts wouldbenefit from a change to larger spaces for theanswers.the questionnaire.
    28. 28.  Answers will be more legible because thewriters have enough space, answers will bemore complete, and answers will be verbatimrather than summarized. Examining answers to pretests mayidentify poor instructions or inappropriatequestion wording on

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