Getting Started with
IBM SPSS Stats 20
Presented by: Rosey Zackula
Center for Biostatistical Collaboration
Office of Research
Tuesday, October 23, 2012
THE
RESEARCH
PROCESS
(1)
Turn idea(s)
into research
question(s)
(3)
(4)
Design study
and develop
method(s)
Write proposal
(6)
(7)
Obtain approval
Collect data
(9)
Evaluate
implications
(10)
Report and
disseminate
findings
http://www.rdinfo.org.uk/flowchart/Flowchart.html
(2)
Review the
literature
(5)
Address
funding issues
(8)
Analyze and
interpret data
COURSE OBJECTIVES
I. Become familiar with the SPSS system
II. Establish methods for reporting results
III. Explore steps for analyzing a dataset
IV. Demonstrate the analysis process*
V. Hands on exercise*
* All examples are from Windish and Diener-West, 2005
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
IBM SPSS System
• 16+ Analysis Tools
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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
Manuals for SPSS
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 
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.)
III. STEPS TO ANALYZE DATA
Step 1:
Set up
Step 5:
Analyze
Step 4:
Describe
Step 2:
Inspect
Step 3:
Clean
Step 1: Set up data
• Enter manually
• Import
– Database
• Excel, Access, REDCap, Text
– Read text
• Copy and paste (not advised)
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)
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
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
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
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
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?
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
V. YOUR TURN
• Open SPSS
– File > Open Database > New Query…
• Database Wizard: Excel Files > Next
• Browse…
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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
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)
Statistical Results
THE GRANDMA CLAUSE
You do not really
understand something
unless you can explain it
to your grandmother.
Albert Einstein
QUESTIONS???
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