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

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Presentation transcript:

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) (2) Review the literature (3) Design study and develop method(s) (4) Write proposal (5) Address funding issues (6) Obtain approval (7) Collect data (8) Analyze and interpret data (9) Evaluate implications (10) Report and disseminate findings

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 –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 – 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 2: Inspect Step 3: Clean Step 4: Describe Step 5: Analyze

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 ) 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… –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)

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

QUESTIONS???

Reference A Clinician-Educator’s Roadmap to Choosing and Interpreting Statistical Tests. Windish and Diener-West, 2005 – –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