Chapter Sixteen Starting the Data Analysis

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Chapter SixteenStarting the Data Analysis

• Angel Gillis Winston Jackson
• Research for Nurses
• Methods and Interpretation

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Rules for Data Entry

• Number questionnaires, starting with 001 note
  that numbers can be missing. The number is used
  to link questionnaire with data in case errors
  are found.
• Code Uncoded Questions. Any open-ended questions
  or occupational prestige scores that need to be
  looked up should be assigned values

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Rules for Data EntryCont.

• Do a Column Count. This will identify position
  where each variable will be entered
• Enter Data with a Patner. To reduce error it is
  best to have one person call out the number, the
  other person entering the data.
• New Page Blanks. As you turn a page, leave one
  blank column--this will enable you to spot errors
  immediately

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Rules for Data EntryCont.

• Simplify Missing Value Codes. Where possible use
  a 9, 99, or 999 to indicate situations where a
  respondent refused to answer a question. When
  something is left out but it means zero, use a
  zero. In 9-point Likert scales use the 0 to
  indicate a missing question.

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Rules for Data EntryCont.

• Document Research Decisions. If a response is in
  doubt (two numbers circled, two answers when only
  one was asked for), flip a coin to determine
  which response will be taken circle in red and
  write your initials next the decision.

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Rules for Data EntryCont.

• Code for Information not on Questionnaire. In
  group projects it is a good idea to enter a code
  for each data entry person in interviews code
  the interviewers. If systematic differences occur
  one can then quickly identify whose
  questionnaires belong to which person.
• Use Double Data Entry. Feasibility issue.

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Syntax Commands for Creating SPSS System File

• Title system file creation, Nursing Faculty
  Review, Winston.
• Data list file 'C\oia\nursing\nursedat.sps' /
  id 1-5 v1 8 v2 9
• v3 10 v4 12 v4.1 to v4.7 13-19 v5 20 v6 22 v8 23
  v9.1 to v9.6 24-29
• v10 to v12 30-32 v13 34 v16 35 v17 36 v18.1 to
  v18.5 37-41.
• variable labels id "identification number"
• /v1 "Year of Graduation"
• /v2 "Program"
• /v3 "Honors Thesis"
• /v4 "Further Education"
• /v5 "Current Employment"
• /v6 "Employed in Field of Choice"
• /v8 "Different Field of Study"
• /v9.1 "Quality of Content for Nursing"
• /v9.2 "Quality of Instruction for Nursing"
• /v18.4 "Audio-Visual Aids"
• /v18.5 "Quiet Study Space".
• value labels /v1 0 "1995 or earlier" 1 "1996" 2
  "1997"
• 3 "1998" 4 "1999" 5 "2000" 6 "2001" 7 "2002" 8
  "2003"
• /v2 1 "Major" 2 "Advanced Major" 3 "Honors"

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Error Checking

• Sort by ID number all questionnaires required
• Sort File by line
• List files on computer to spot ragged edges
• Check for Non-numerics
• Check for out-of-range numbers
• Locate cases with errors in them

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Error CheckingCont

• Make Corrections in data
• Merge files together
• Resubmit Lab 10 to create SPSS .sav file
• Run Frequencies, Descriptives as appropriate to
  complete final error checking

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Steps in Analyzing Data for a Project

• Run FREQUENCIES (nominal ordinal variables)
• Run DESCRIPTIVES (ratio variables)
• Create any indexes by testing them using the
  RELIABILITY procedure use COMPUTE to create
  final index
• Test any Causal Models
• Create Summary Tables

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3 M Approach

• Model gtX gtY
• Measurement Nominal, Ordinal, Ratio
• Method
• CROSSTABS
• MEANS
• CORRELATIONS