Chapter Sixteen Starting the Data Analysis Angel Gillis & Winston Jackson Research for Nurses: Research for Nurses: Methods and Interpretation

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

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. 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. 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. 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 v v5 20 v6 22 v8 23 v9.1 to v v10 to v v13 34 v16 35 v17 36 v18.1 to v 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 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…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 Approach Model >X >Y Measurement: Nominal, Ordinal, Ratio Method: –CROSSTABS – MEANS –CORRELATIONS