Chapter SixteenChapter SixteenStarting the Data AnalysisStarting the Data Analysis

Angel Gillis & Winston Jackson

Research for Nurses:Research for Nurses:

Methods and InterpretationMethods and Interpretation

Rules for Data EntryRules 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

Rules for Data Entry…Cont.Rules for Data Entry…Cont.

• 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

Rules for Data Entry…Cont.Rules for Data Entry…Cont.

• 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.

Rules for Data Entry…Cont.Rules for Data Entry…Cont.

• 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.

Rules for Data Entry…Cont.Rules for Data Entry…Cont.

• 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.

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"• /v4 0 "Yes" 1 "No"• /v4.1 to v4.5 0 "No" 1 "Yes".• missing values v1, v2, v3, v4, v4.1 to v4.5, v5, v6, v8, v13 (9)• /v4.5, v4.6, v9.1 to v9.6, v10 to v12, v16, v17, v18.1 to v18.5 (0).• Frequencies var= v1.

Error CheckingError 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

Error Checking…ContError Checking…Cont

• 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

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

3 M Approach3 M Approach

• Model >X >Y

• Measurement: Nominal, Ordinal, Ratio

• Method: – CROSSTABS– MEANS– CORRELATIONS