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Getting Started with IBM SPSS Stats 20

Join us for an insightful session on IBM SPSS Statistics 20, led by Rosey Zackula from the Center for Biostatistical Collaboration. This course aims to familiarize participants with the SPSS system, establish effective reporting methods, and explore dataset analysis steps. You'll engage in hands-on exercises and demonstrations, learning to generate reports, conduct descriptive and complex statistical analyses, and properly manage data preparation. Whether you're a beginner or looking to enhance your skills, this workshop is designed to elevate your SPSS proficiency.

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Getting Started with IBM SPSS Stats 20

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  1. Getting Started with IBM SPSS Stats 20 Presented by: Rosey Zackula Center for Biostatistical Collaboration Office of Research Tuesday, October 23, 2012

  2. http://www.rdinfo.org.uk/flowchart/Flowchart.html

  3. COURSE OBJECTIVES • Become familiar with the SPSS system • Establish methods for reporting results • Explore steps for analyzing a dataset • Demonstrate the analysis process* • Hands on exercise* * All examples are from Windish and Diener-West, 2005

  4. I. WHAT IS IBM SPSS STATS 20? • Comprehensive system for analyzing all types of data • Suite of software tools • Primary purpose • Generate tabulated reports • Produce charts • Plot distributions and trends • Conduct descriptive statistics • Perform complex statistical analyses

  5. IBM SPSS System • 16+ Analysis Tools • Statistics Base • Advanced Statistics • Bootstrapping • Categories • Complex Samples • Conjoint • Custom Tables • Data Preparation • Decision Trees • Cont’d • Direct Marketing • Exact Tests • Forecasting • Missing Values • Neural networks • Regression • Amos AND • SamplePower

  6. Manuals for SPSS

  7. SPSS Help and Support • Help features in SPSS • SPSS Manuals • S:\SPSS Manuals\SPSS 20 • IBM Corp. Web site • http://www.ibm.com/support • USENET discussion group • comp.soft-sys-stat.spss • Center for Biostatistical Collaboration 

  8. II. ESTABLISH METHODS FOR REPORTING RESULTS • What style is required? • Check target journal for manuscript • Example JGIM • Modify SPSS output • Edit > Options • Output labeling • Adjust fonts/formats • Table and Charts • Copy special formats (for copying into manuscript: Word, Excel, etc.)

  9. III. STEPS TO ANALYZE DATA

  10. Step 1: Set up data • Enter manually • Import • Database • Excel, Access, REDCap, Text • Read text • Copy and paste (not advised)

  11. Data considerations • SPSS Types • Numeric, comma, dot, scientific notation, date, dollar, custom currency, string, restricted numeric (non-negative integer with leading zeros, i.e. 000001) • Values • Example: categorical variables • 0 = No; 1 = Yes • Measures • Nominal, Ordinal, Scale (data that can be multiplied with meaningful results)

  12. Step 2: Inspect data • Role • Input, Target, Both, None, Partition, Split • Defining variable properties • Data attributes • Custom tables • Multiple response: define variable sets (surveys) • Utilities • Variable information • Data file comments • Define/use variables sets

  13. Step 3: Clean data • Data preparation • Validation • Identify missing information, unusual cases, etc. • Restructure data • Transform (recoding) • Visual Binning • Create new variables • Compute, recode, replace missing values • Remember to define any new variable properties and attributes

  14. Step 4: Describe data Summarizing categorical data • Tables • Dichotomous: proportions • Nominal: relative frequencies (percent of total) • Ordered: median (interquartile range) • Graphs • Bar and pie charts • Percentages vs. Counts

  15. Step 4: Describe data (cont’d) Summarizing continuous (scale) data • Tables • Parametric or normal distribution: Mean (standard deviation) • Test of normality • Kolmogorov-Smirnov “vodka test” • Nonparametric test: 1-Sample K-S • K-S Lilliefors (by group) • Explore: Plots • Nonparametric: Median (interquartile range) • Graphs • Histograms, line charts, scatter plots

  16. Step 5: Analyze the data • What is the study design? • What is(are) the research question(s)? • Hypothesis to be tested • What is the outcome? • What shape/type of distribution? • Are any groups being compared? • What are the variables of interest? • What shape/type of distribution? • Predictors or confounders?

  17. IV. DEMONSTRATION • Study design: randomized clinical trial to evaluate 1-month curriculum • Compare performance of two unpaired groups (intervention and control) • Outcome: composite number of maneuvers performed correctly • Hypothesis 1 • Ho: Participants and controls do not differ in mean number of correct maneuvers

  18. V. YOUR TURN • Open SPSS • File > Open Database > New Query… • Database Wizard: Excel Files > Next • Browse… • S:\Everyone\Intro_IBM SPSS_Oct 23 • Intro IBM SPSS_Test data_Windish article.xlsx • Retrieve all Fields > Next > Next • GENDER: Recode to Numeric • Minimize string widths > Finish

  19. Your turn (cont’d) • Establish output options per author instructions from target journal • Edit > Options • Define Variables • Data > Define Variable Properties • Variable View • Type, Width, Decimals, Labels, Values, etc. • Choose hypothesis to test • See article Windish and Diener-West, 2005 Hypothesis 2, 3 or 4 (data are not the same; therefore, results may differ)

  20. Statistical Results THE GRANDMA CLAUSE You do not really understand something unless you can explain it to your grandmother. Albert Einstein

  21. ? ? QUESTIONS??? ? ? ? ? ? ? ? ? ? ? ? ? ? ?

  22. Reference • A Clinician-Educator’s Roadmap to Choosing and Interpreting Statistical Tests. Windish and Diener-West, 2005 • http://www.ncbi.nlm.nih.gov/pmc/articles/PMC1924630/ • Important downloads from the article: • Table 1: Questions to Consider When Selecting the Appropriate Statistical Test • Appendix A: Diagrammatic Approach to Choosing Summary Measures, Statistical Tests and Methods • Appendix B: Glossary of terms

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