Dr. Michael R. Hyman, NMSU

Data Preparation

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File, Record, and Field

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Data Matrix

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Data Entry

Process of transforming data from research projects to computers

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(1) Validation(2) Editing(3) Coding(4) Data entry/transcription(5) Machine cleaning of data

Five Steps for Data Preparation

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Check that interviews conducted as specified• Ensure respondent qualified• Interviewer looked/acted professionally• Interview conducted in proper environment• All appropriate questions asked

Validation

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Check for:• Omissions• Ambiguities• Inconsistencies• Proper skip patterns • Properly recorded answers, especially

to open-ended questions

Editing: Personal Interviews

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Check for:• All questionnaire sections and key

questions answered• Respondents understood instructions

and took task seriously• No missing pages• Questionnaire returned before cutoff

date

Editing: Self-Administered Questionnaires

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Solutions for Editing Problems

• Re-contact respondent

• Discard questionnaire

• Use only good items

– Data analysis implications (beyond scope of class)

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Coding

• Process of grouping and assigning numeric codes to different question responses

• Closed-ended questions easier because pre-coded

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Pre-coding Example

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Coding an Open-Ended Question

• Generate list of responses

• Consolidate responses (subjective judgment)

• Set response category codes

• Assign independent response category and record associated numeric code

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Portion of Travel Study Code Book

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• Validated, edited, and coded questionnaires given to data entry operator

• More accurate and efficient to go directly from questionnaire to data entry device and storage medium

• Skip coding sheets

Data Entry Process

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Data Transcription

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• Checking entered data for internal logic by either the data entry device or another connected device

• Excel/Quattro and SPSS rely on dumb data entry• Require data cleaning

Intelligent Data Entry

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Machine Cleaning of Data

• Computerized error check– Identifies and suggests fixes for logical

errors• Marginal report

– Computer-generated table of response frequencies for questions

– Monitor entry of valid codes and skip patterns

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Machine Cleaning Instructions

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Recoding Data

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Recoding Data

• Using computers to convert original codes used for raw data into codes that are more suitable for analysis

• Var1 = 8 - Var1

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Collapsing a Five-Point Likert Scale

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Coping with Missing Data

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Item Non-response to Questions of Fact

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Ways to Handle Missing Responses

• Leave blank

• Case-wise deletion

• Pair-wise deletion

• Mean response

• Imputed response