Webinar%204:%20Academic%20tools%20of%20data%20analysis:%20Comparing%20SPSS,%20Stata%20and%20R%20and%20engaging%20with%20Higher%20Education%20institutions - PowerPoint PPT Presentation

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Webinar%204:%20Academic%20tools%20of%20data%20analysis:%20Comparing%20SPSS,%20Stata%20and%20R%20and%20engaging%20with%20Higher%20Education%20institutions

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Webinar 4: Academic tools of data analysis: Comparing SPSS, Stata and R and engaging with Higher Education institutions Scottish Civil Society Data Partnership – PowerPoint PPT presentation

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Title: Webinar%204:%20Academic%20tools%20of%20data%20analysis:%20Comparing%20SPSS,%20Stata%20and%20R%20and%20engaging%20with%20Higher%20Education%20institutions


1
Webinar 4 Academic tools of data analysis
Comparing SPSS, Stata and R and engaging with
Higher Education institutions
Scottish Civil Society Data Partnership
2
Academic tools of data analysis Comparing SPSS,
Stata and R and engaging with Higher Education
Institutes
  • Paul Lambert, University of Stirling
  • Presentation to the Scottish Civil Society Data
    Partnership Project (S-CSDP), Webinar 4
  • www.thinkdata.org.uk, 11 Mar 2016

3
Webinar 4 Academic tools of data analysis
Comparing SPSS, Stata and R and engaging with
Higher Education institutions
  • Components
  • Academic research and statistical software
  • Examples in using SPSS for research
  • Examples in using Stata for research
  • Examples in using R for research
  • HE institutional access and the University of
    Stirling Affiliate Membership for Third Sector
    Researchers scheme

4
Webinar 4 Academic tools of data analysis
Comparing SPSS, Stata and R and engaging with
Higher Education institutions
Scottish Civil Society Data Partnership
5
1) Academic research and statistical software
  • Academic researchers use software designed
    specifically for the statistical analysis of
    survey and survey-like data since at least the
    mid 1960s
  • (Hundreds of options e.g. Lambert et al. 2015)
  • Distinction between general purpose and
    specialist statistical software
  • Theme of documentation for replication
    software is better when it can provide a
    replicable trail of data analysis and management
    activities

6
Understanding filestore and software Linking
things together
(i) Somewhere on your computer, you typically
have a copy of a data file ( its documentation)
(ii) Your next step ordinarily is to access a
software package that will be able to open and
then do things to the data
(iii) If you are good, you will use separately
saved command files to run processes through
the software on the data, generating subsequent
outputs
7
software wars in academic survey research
Statas origins are in economics but it has
spread to other disciplines. It supports a very
wide range of data management and analysis
functionality. It is popular in North American
and North and Central European academic survey
research.
R is a freeware with a wide range of
capabilities. It is mostly used by statisticians
and methodologists.
  • If working with microdata, we ordinarily use
    specialist statistical software for data
    management and analysis
  • People tend to get individually quite attached to
    their favourite(s)
  • See also Lambert et al. (2015) and see lab
    materials at www.staff.stir.ac.uk/paul.lambert/e
    ssex_summer_school/

SPSS used to be the leading social science
package for survey research in disciplines other
than economics. It is still widely available and
commonly taught and used.
MLwiN is an example of specialist software
designed for a certain analytical purpose
(fitting multilevel models).
8
Stat-JR offers dowloadable integration between
software, including freeware, through locally
installed copies (http//www.bristol.ac.uk/cmm/sof
tware/statjr/ )
9
Controlling software Using syntax
10
Documentation as replicable workflows
  • Reproducible (for self)
  • Replicable (for all)
  • Paper trail for whole lifecycle
  • Cf. Dale 2006 Freese 2007
  • In survey research, this means using clearly
    annotated syntax files
  • (e.g. Long 2009)
  • Syntax Examples
  • www.dames.org.uk/workshops
  • Modern computing / data
  • Theres no excuse for not documenting /
    replicating!
  • New opportunities for workflow modelling

11
The tension between simpler more complex
statistical analysis
  • Complex analytical methods
  • E.g. statistical models sampling weights and
    survey design factors sensitivity analysis for
    data permutations multivariate and
    multiprocess systems
  • Can be thought of as featuring a substantial
    element of control for other factors relevant
    to the social mechanisms, e.g. statistical
    models with many parameters expressing influences
    of background variables and complex data
    structures
  • Simpler analytical methods
  • E.g. univariate distributions, bivariate
    comparisons, accessible graphical summaries and
    headline percentages
  • Can be appealing to communicate and still have
    important strengths, e.g. statistically
    representative patterns
  • Introduce risks in summarising social mechanisms
    spurious and unduly simplified trends and
    associations (e.g. interactions) incorrect point
    estimates and/or incorrect representation of
    uncertainty encourages view that statistics
    equal lies

-gt Academic software tends to support complex
methods, whereas many accessible, e.g. online,
data analysis tools are using simpler methods
and moreover cannot readily be adapted to more
complex analytical methods
12
Webinar 4 Academic tools of data analysis
Comparing SPSS, Stata and R and engaging with
Higher Education institutions
Scottish Civil Society Data Partnership
13
2) Examples in using SPSS for research
  • Installation comments
  • SPSS Interface
  • Using command syntax
  • Applied example Volunteering in the BHPS
  • Sources of help
  • e.g. Field 2013 UCLA statistical software
    http//www.ats.ucla.edu/stat

Alternative paste to get syntax code
Syntax editor
14
Webinar 4 Academic tools of data analysis
Comparing SPSS, Stata and R and engaging with
Higher Education institutions
Scottish Civil Society Data Partnership
15
3) Examples in using Stata for research
  • Installation comments
  • Stata Interface
  • Using command syntax
  • Applied example volunteering in the ESS
  • Sources of help
  • e.g. Kohler Kreuter 2012 UCLA statistical
    software http//www.ats.ucla.edu/stat

Typical Stata output window (results)
Typical format of do file (command or
syntax file)
16
Webinar 4 Academic tools of data analysis
Comparing SPSS, Stata and R and engaging with
Higher Education institutions
Scottish Civil Society Data Partnership
17
4) Examples in using R for research
  • Installation comments
  • R Interface
  • Using command syntax
  • Example Sample from Lambert (2015)
  • Sources of help
  • e.g. Field et al. 2012 Quick-R
    http//www.statmethods.net/ UCLA statistical
    software http//www.ats.ucla.edu/stat

Standard R
RStudio
18
Webinar 4 Academic tools of data analysis
Comparing SPSS, Stata and R and engaging with
Higher Education institutions
Scottish Civil Society Data Partnership
19
5) HE institutional access and the University of
Stirling Affiliate Membership for Third Sector
Researchers scheme
  • RCUK funding opportunities
  • ESRC SDAI (explicitly promotes impact
    collaboration) (ESRC 2015)
  • Secondary analysis in general appeals to major
    funders
  • Comparative research opportunities
  • Other HE sector collaboration potential
  • Further funded project options
  • Unfunded research capacity
  • PhD studentship sponsorship/collaborative schemes
  • Training enrolments and taught course projects,
    e.g. MSc dissertation
    projects
  • What collaborative opportunities are out there?

20
Routes to HE institutional access?
  • Feedback at previous events highlights barriers
    to use of secondary surveys for research without
    HE Infrastructural support
  • Filestore
  • Software
  • Library resources
  • Consulting colleagues
  • Collaboration with HE staff is often a good
    solution
  • Friendly researcher/faculty
  • Funded post, e.g. a sponsored PhD
  • Please see www.thinkdata.org.uk for updates on a
    prospective new scheme that should help here, the
    University of Stirling Affiliate Membership
    scheme for Third Sector Researchers (AM-TSR)

21
References cited
  • Dale, A. (2006). Quality Issues with Survey
    Research. International Journal of Social
    Research Methodology, 9(2), 143-158.
  • Field, A. (2013). Discovering Statistics Using
    IBM SPSS Statistics, 4th Edition. London Sage.
  • Field, A., Miles, J., Field, Z. (2012).
    Discovering Statistics Using R. London Sage.
  • Freese, J. (2007). Replication Standards for
    Quantitative Social Science Why Not Sociology?
    Sociological Methods and Research, 36(2),
    153-171.
  • Kohler, H. P., Kreuter, F. (2012). Data
    Analysis using Stata, Third edition. College
    Station, Tx Stata Press.
  • Lambert, P. S. (2015). Advances in data
    management for social survey research. In R.
    Procter P. Halfpenny (Eds.), Innovations in
    Digital Research Methods (pp. 105-122). London
    Sage.
  • Lambert, P. S., Browne, W. J., Michaelides, D.
    T. (2015). Contemporary developments in
    statistical software for social scientists. In R.
    Procter P. Halfpenny (Eds.), Innovations in
    Digital Research Methods (pp. 143-160). London
    Sage.
  • Long, J. S. (2009). The Workflow of Data Analysis
    Using Stata. Boca Raton CRC Press.
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