University of Warwick, Department of Sociology, 2016/17
SO348: Multivariate Secondary Analysis of Social Data (Richard Lampard)
SO 348
MULTIVARIATE SECONDARY ANALYSIS
OF SOCIAL DATA
MODULE OUTLINE AND READING LIST
Overview: The main aims of this module are (i) to give students an understanding of, and practical experience of applying, various key multivariate analysis approaches relevant to the analysis of sociologically-relevant data from social surveys, and (ii) to give them experience of carrying out a secondary-analysis based piece of work on a substantive topic in that context.
Assessment: This takes a standard, fixed form, consisting of a two-hour examination and a secondary-analysis based project report (Length: 5,000 words) to be submitted by 2pm on the Tuesday of Week 3 in Term 3 (Tuesday 9 May 2017). (For a description of the consequences of exceeding the maximum word length of 5,000 + 10% = 5,500 words, see the Department’s Undergraduate Handbook.)
Projects should be submitted electronically by 2pm on the specified date. Late submission where no formal extension has been granted (via the relevant form located within the Undergraduate Study section of the Department’s web pages) will incur a penalty of 5 marks per day deduction from the mark awarded.
Lectures are on Monday at 12noon - 1pm
The ‘Seminar’ time is Wednesday at 11am - 1pm
The Lectures are all in Room R3.25 (Top Floor, Ramphal Building).
The ‘Seminars’ (Computer-based sessions) are held in R0.41 (a workarea, sometimes referred to as Computer Suite 1, which is on the Ground Floor of the Library, located off a lobby which is accessed via an external door just along the side of the building from the corner of the Library which is nearest to the Law School entrance) ,
Richard Lampard’s office is D0.11 on the Ground Floor of the Social Studies Building and his e-mail address is . His pigeonhole is in D0.25 on the Ground Floor of the Social Studies Building.
Surveys and Statistics module web (Moodle) page:
This can be accessed via: http://go.warwick.ac.uk/so348/, or via the University’s Moodle website. It will contain, in due course, some or all of the following:
· Material relevant to project work.
· Links to pertinent websites.
· Material (data files, etc.) for use in computing sessions.
· Any other material added as the academic year progresses.
MODULE SCHEDULE
(Note that the Wednesday session will often ‘echo’ the topic of the Monday lecture, but will sometimes also include other useful activities, e.g. focusing on particular features of SPSS, projects, etc.)
Week 1: Introduction to multivariate analysis
Week 2: Multiple regression I: Linear regression
Week 3: Multiple regression II: Logistic regression
Week 4: Multiple regression III: Interaction effects
Week 5: Issues in the secondary analysis of large and complex surveys/
Interpreting published articles based on multivariate analyses
Week 6: (Reading week)
Week 7: Concept operationalisation and index construction
Week 8: Hierarchical log-linear models I
Week 9: Hierarchical log-linear models II/
Links to logistic regression
Week 10: Event history modelling: Cox’s proportional hazard model
Learning outcomes
By the end of the module students should be able to...
· Understand the value of, and apply, a number of key multivariate statistical analysis techniques.
· Carry out a competent secondary analysis of survey data on a substantive topic, and demonstrate an enhanced ability to evaluate the merits, limitations and specificities of existing surveys as sources of data.
· Demonstrate a heightened awareness of both the technical and theoretical/conceptual dimensions of quantitative data analysis.
· Apply statistical software to manipulate survey data and analyse it using multivariate techniques.
· Present and interpret the results of multivariate statistical analyses appropriately
Learning and teaching methods which enable students to achieve the module's learning outcomes
(a) 9 lectures, including formal coverage of statistical analysis topics
(b) 9 (two hour) computer-based sessions, in which students (a) apply statistical techniques, as covered by some of the lectures, to data from existing social surveys, (b) consider or discuss other data collection and/or analysis topics, sometimes with reference to preparatory reading, and/or (c) discuss the project component of the course assessment.
(c) Students produce one piece of classwork, in relation to which they receive both qualitative feedback and a quantitative mark, but which is not formally assessed and which do not contribute (directly) to the final module mark.
(d) Students access learning materials in the library and on the module web-site.
(e) With regard to project work, students are provided with a CD containing data from an existing social survey (or download such data), and have access to statistical computing software via the University computer network (and can download a copy under licence)
(f) Individual advice, tuition and project-related support are available during the tutors’ office hours or by appointment (and also via e-mail).
Assessment methods designed to measure the achievement of the module's learning outcomes
Students are assessed via the following: a project report (length 5,000 words), corresponding to the secondary analysis of data from an existing survey.
Assessment of the project report is based on the following criteria:
· Presentation of written work, including spelling and grammar
· Structure of written work, and its fluency, clarity and maturity
· Quality and soundness of argument
· Competence in the application of statistical techniques
· Competence in interpretation of quantitative research findings
· Quality and sophistication of linkages between data and substantive/theoretical ideas
· Breadth and accuracy of knowledge with respect to research methods issues
· Independence of thought and critical awareness within analyses
The learning outcomes for this module are reflected in the learning and teaching methods employed, and the assessment methods measure the students’ achievements across the range of learning outcomes.
Seminar performance/transferable skills
Students’ attendance at the computer-based sessions is monitored as part of the Department’s student progress procedures. Aspects of student performance relevant to most or all modules include: writing skills (measured via the assessment of classwork), oral skills (measured with respect to participation in taught sessions), time management skills (measured with regard to attendance and preparation), and research skills (measured with regard to use of the library and of IT resources). With regard to this specific module, students are expected to enhance all or most of the transferable skills listed above. However, performance in the context of computer-based sessions relates primarily to attendance, willingness to engage actively with the material covered in sessions, and willingness to develop data analysis skills. Students who do not miss any sessions without appropriate explanation, participate actively within sessions as and when required, and carry out set tasks outside the scheduled sessions adequately (including project work) will be viewed, at the very least, as making satisfactory progress.
Reading list
The sections that follow list reasonably good texts relating to different aspects of the module. No one text covers all the material contained within the module (and the module’s set of Library course extracts may be collectively more useful):
Statistical computing
(Note that texts which are not tied to specific software packages may be a better bet if you're interested in the statistical techniques rather than the computing per se).
The following texts are linked to SPSS for Windows, the software used in the module, although most will not cover all of the techniques that we will apply using SPSS. Note that there are subtle variations between versions of SPSS for Windows {e.g. between Versions 6.1, 8.0, 9, 10, 11 and 12, and between 15.0 and 16}; we will use Version 23 or 24 on the University’s PC network; for those of you who have your own laptops or PCs, a licensed copy of the software is available for download via IT Services
(see: http://www2.warwick.ac.uk/services/its/servicessupport/software/list/spss)
*MARSH, C. and ELLIOTT, J. 2009. Exploring Data: An Introduction to Data Analysis for Social Scientists (2nd edition). Cambridge: Polity Press. [Covers much of the statistical analysis/data analysis side of the module, and contains some material on SPSS].
FIELDING, J. and GILBERT, N. 2006. Understanding Social Statistics. (2nd edition) London: Sage. [First edition (2000) still useful. Covers SPSS for Windows and a fair amount of statistical testing material].
ACTON, C. and MILLER, R., with FULLERTON, D. and MALTBY, J. 2009. SPSS for Social Scientists (2nd edition). Basingstoke: Palgrave Macmillan.
KINNEAR, P.R. and GRAY, C.D. 2010. IBM SPSS Statistics 18 Made Simple. Hove: Psychology Press. [A good, straightforward, but broad text (& relatively cheap!); the 2008, 2006, 2000, 1997 and 1994 editions are also still of relevance; there is also a 2011 edition.]
PALLANT, J. 2007. SPSS Survival Manual (3rd edition): A Step-By-Step Guide to Data Analysis Using SPSS (Version 15). Maidenhead: Open University Press. [Leans towards psychology (affecting the balance of the statistical content); 2010/earlier edition are useful].
BRYMAN, A. and CRAMER, D. 2001. Quantitative Data Analysis with SPSS Release 10 for Windows. London: Routledge. [The 1999 edition using Version 8 is also still of relevance, and the 1997 version is still of some use; there is a more up-to-date 2011 edition].
GEORGE, D. and MALLERY, P. 2002. SPSS for Windows Step-by-Step: A Simple Guide and Reference, 11.0 Update (4th edition). Allyn & Bacon. [Detailed, fairly recent text].
HO, R. 2006. Handbook of Univariate and Multivariate Data Analysis and Interpretation with SPSS. London: Chapman & Hall/CRC. [Also available as an e-book!!]
COLMAN, A. and PULFORD, B. 2006. A Crash Course in SPSS for Windows (3rd edition). Oxford: Blackwell. [Fairly technical/orientated towards psychology; previous editions by Corston and Colman still useful].
BURTON, D. (ed.) 2000. Research Training for Social Scientists: A Handbook for Postgraduate Researchers. London: Sage. [Chapters by Gayle].
FIELD, A. 2009. Discovering Statistics Using SPSS (3rd edition). London: Sage. [2013 4th edition now available too!]
ARGYROUS, G. 2005. Statistics for Research with a Guide to SPSS (2nd ed.). London: Sage.
[2011 3rd edition also now available].
CONNOLLY, P. 2007. Quantitative Data Analysis in Education: A critical introduction using SPSS. London: Routledge. [Esp. Chapter 6].
HINTON, P.R., BROWNLOW, C., McMURRAY, I. and COZENS, B. 2004. SPSS Explained. Hove: Psychology Press.
SARANTAKOS, S. 2007. A Tool Kit for Quantitative Data Analysis. Basingstoke: Palgrave.
BABBIE, E.R., HALLEY, F. and ZAINO, J. 2000. Adventures in Social Research: Data Analysis Using SPSS for Windows 95/98 (4th Edition). London: Sage (Pine Forge Press). [Don’t confuse this with the SPSS-PC+-related edition (1993/4); the 1995 edition (Babbie & Halley) is, however, still of relevance/value, and is used for reference purposes below].
FOSTER, J.J., BARKUS, E. and YAVORSKY, C. 2005. Understanding and Using Advanced Statistics: A Practical Guide for Students. London: Sage.
LANDAU, S. and EVERITT, B.S. 2004. A Handbook of Statistical Analyses using SPSS. Boca Raton: Chapman and Hall/CRC. [Available online].
BOSLAUGH, S. 2005. An Intermediate Guide to SPSS Programming: Using Syntax for Data Management. London: Sage. [May be useful for doing things with syntax windows].
COLLIER, J. 2010. Using SPSS Syntax: A Beginner’s Guide. London: Sage.
ROSE, D. and SULLIVAN, O. 1996. Introducing Data Analysis for Social Scientists (2nd revised edition). Buckingham: Open University Press.
DAVID, M. and SUTTON, C.D. 2004. Social Research: The Basics. London: Sage. [Part III on Data Analysis contains some useful material on SPSS].
MUIJS, D. 2004. Doing Quantitative Research in Education with SPSS. London: Sage.
HOWITT, D. and CRAMER, D. 2002. A Guide to Computing Statistics with SPSS 11 for Windows (Revised Edition). Harlow: Pearson Education.
CRAMER, D. 1998. Fundamental Statistics for Social Research: Step-by-step calculations and computer techniques using SPSS for Windows. London: Routledge.
EINSPRUCH, E.L. 1998. An Introductory Guide to SPSS for Windows. London: Sage.
HEALEY, J., BABBIE, E. and HALLEY, F. 1997. Exploring Social Issues Using SPSS for Windows. Thousand Oaks: Pine Forge Press.
FRANKFORT-NACHMIAS, C. 1997. Social Statistics for a Diverse Society. London: Pine Forge (Sage). [2011 edition now available].
VOELKL, K. and GERBER, S. 1999. Using SPSS for Windows: Data Analysis and Graphics. London: Springer-Verlag. [Covers statistical testing/using SPSS; fairly technical].
There may also still be (tatty) copies of some manuals for SPSS for Windows in the Library. Though a little dated, these may be as useful as some of the above texts, and are not necessarily less accessibly written either!
e.g. NORUSIS, M.J. 1993c. SPSS Professional Statistics 6.0. Chicago: SPSS Inc.
See also: NORUSIS, M. 1997. SPSS 7.5 Guide to Data Analysis. Upper Saddle River, NJ: Prentice Hall.
Social statistics
Various books cover at least some of the statistical techniques covered by this module, though they tend to approach the material in different ways. Some of the items listed may be useful for basic social statistics but less useful for multivariate techniques than other material later in this reading list…
LINNEMAN T.J. 2014. Social Statistics: Managing Data, Conducting Analyses, Presenting Results (Second Edition). London: Routledge.
AGRESTI, A. and FINLAY, B. 2013. Statistical Methods for the Social Sciences (4th edition). Harlow: Pearson Education.
GARNER, R. 2005. The Joy of Stats: A Short Guide to Introductory Statistics in the Social Sciences. London: Broadview Press.
REID, S. 1987. Working With Statistics: An Introduction to Quantitative Methods for Social Scientists. Cambridge: Polity Press. [Readable basic social statistics text, but possibly a bit statistically lightweight as a consequence!]
DIAMOND, I. and JEFFERIES, J. 2000. Beginning Statistics: An Introduction for Social Scientists. London: Sage. [Useful and accessible introductory text].
WALSH, A. 1990. Statistics for the Social Sciences. New York: Harper and Row. [More comprehensive but quite technical].
HINTON, P. 1995. Statistics Explained. London: Routledge. [Seems fairly user-friendly; see also 2014 edition (e-book)]
HEALEY, J. 1993. Statistics: A Tool for Social Research (3rd edition). Wadsworth.
MARSH, C. 1988. Exploring Data. Cambridge: Polity Press. [No material on statistical testing; useful material on describing data, looking at tables, etc. Contains potted descriptions of some important data sources. Useful practical aid to data analysis/presentation?]
WRIGHT, D.B. 2002. First Steps in Statistics. London: Sage.
KENT, R. 2001. Data Construction and Data Analysis for Survey Research. Basingstoke: Palgrave. [Data analysis text that may be useful with regard to project work].