Advanced Methods in Social Research

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1 Advanced Methods in Social Research MA Social Research Spring term Department of Sociology University of York Module Leaders: Paul Drew and Laurie Hanquinet ( s: laurie.

2 Advanced Research Methods in Social Sciences Proposed Masters level module Paul Drew & Laurie Hanquinet This module aims to develop further the skills in research methods that students have acquired from the modules Qualitative Methods and Quantitative methods & Data Analysis. It will provide them training in more advanced research methods, both qualitative and quantitative. The four first sessions are used to introduce them to more advanced quantitative techniques that are often used in scientific articles, such as multinomial logistic regression and factor analysis (using SPSS). Specific attention will be also given to multiple correspondence analysis, given its increasing importance nowadays in social sciences (using SPAD). The last four sessions will focus on advanced qualitative methods. Two areas will be studied: 1) conversation analysis (in which York has an internationally recognised expertise) and 2) computer assisted qualitative data analysis. Module aims To provide students with a wide range of more advanced methods, both quantitative and qualitative To provide students with practical-based knowledge of methods in social sciences To explore different quantitative and qualitative software packages To make students able to critically engage with more advanced methods Module outcomes By the end of this module students will: be able to carry out more advanced quantitative and qualitative methods be able to use more extensively SPSS be able to use SPAD to conduct multiple correspondence analysis to perform computer assisted qualitative data analysis be able to use software packages for qualitative data analysis such as Atlas Ti to have a comprehensive and in-depth knowledge of conversational analysis be able to understand scientific articles based on these more advanced techniques and to critically engage with them A wider understanding of the methodological possibilities and the issues around them

3 Indicative module content (along with indicative key readings and student tasks) Week Lecture 2h + 2h workshop 2 Advanced Quants: multinomial logistic regression 3 Advanced Quants: factor analysis 4 Advanced Quants: MCA I 5 Advanced Quants: MCA II 6 Advanced Quals: Conversation analysis 7 Advanced Quals: CA 8 Advanced Quals: Computer Assisted qualitative data analysis 9 Advanced Quals: CAQDAS 10 Drop off session Quals Drop off session Quants Week 2. Multinomial logistic regression We examine how we might proceed if we have a dependent variable that has more than two answer categories (e.g. vote for political parties). Continuous variables are not used as dependents in logistic regression. Acton C. and Miller R. (with Maltby J. and Fullerton D.) (2009). SPSS for Social Scientists. Basingstoke: Palgrave MacMillan, 2 nd ed, Chap 10. Week 3. Factor analysis FA is a data reduction technique. It is used to unravel the latent structure (dimensions) of a set of variables by reducing a large number of variables to a smaller number of factors. These factors are often used as dependent variables in linear regressions. Acton C. and Miller R. (with Maltby J. and Fullerton D.) (2009). SPSS for Social Scientists. Basingstoke: Palgrave MacMillan, 2 nd ed, Chap 9. Pallant, J. (2010) SPSS Survival Manual. New York: Open University Press, 4 th ed, chap 15.

4 Week 4. MCA Multiple correspondence analysis (MCA) is a statistical technique that allows the visualisation of complex data sets. It became known in sociology through the work of the late Pierre Bourdieu ( ) as a means of mapping social spaces and fields (most famously in his book Distinction). The method is now becoming increasingly popular for types of 'cultural mapping' (for example, Bennett et al, Culture, Class Distinction) and continues to appeal to those with specific interests in Pierre Bourdieu's sociology. However, the method is also widely used in a variety of disciplines, for instance in psychology and political science, and is also relatively easy to use through using the SPAD package. Le Roux, Brigitte and Henry Rouanet (2010). Multiple Correspondence Analysis. Series: Quantitative Applications in the Social Sciences #163. Thousand Oaks: Sage Publications T Bennett, M. Savage, E.B. Silva, A.Warde, Modesto Gayo and D.Wright (2009), Culture, Class, Distinction, (London, Routledge). Weeks 5 and 6. Conversation Analysis In order to integrate this as far as possible with the quantitative focus of the first 4 weeks, and with the general aims of the course to advance students understanding of and ability in using social research methods, these sessions will develop students ability to apply CA to research in practical settings in the context of research that combines qualitative analysis with some degree of quantification. We ll use research into medical settings, and the project we conducted for the Department of Work & Pensions on interviews with claimants in Jobcentres, to illustrate and explore how CA can deliver distinctive and important findings about interactions in medical and social welfare settings. The sessions will include hands-on assignments involving the analysis of original data, which we will provide. We ll explore why and how quantification has begun to play a significant part in CA research in such areas (despite the way in which CA has developed as a largely qualitative method). Some attention will be given not only to the practical settings in which research is conducted, but to the applied nature of some CA research we ll consider how CA enables us to investigate the relative effectiveness of communication, and to make recommendations concerning improvements. Indicative Reading: Bryman, A. (2001) Social Research Methods. OUP: chapter 17 Language in qualitative research. Drew,P., Chatwin,J, & Collins,S. (2001) Conversation analysis: a method for research into interactions between patients and health-care professionals. Health Expectations, 4: Heritage.J. and Maynard,D. (eds.) Communication in Medical Care: Interaction between Primary Care Physicians and their Patients, Cambridge, Cambridge University Press, 2006: Heritage, J., Robinson, J. D., Elliott, M., Beckett, M., & Wilkes, M. (2007). Reducing Patients' Unmet Concerns: The difference one word can make. Journal of General Internal Medicine, 22, Drew, P., Toerien, M., Irvine, A and Sainsbury, R. (2010) A Study of Language and Communication Between Advisers and Claimants in Work Focused Interviews. Department of Work & Pensions

5 Research Report No This report can be downloaded from the DWP site - then scroll down to report no Drew, P. and Heritage, J. (eds.) Talk at Work: Social Interaction in Institutional Settings. Cambridge, Cambridge University Press, pp Heritage, J. & Clayman, S. (2011) Talk in Action: Interactions, Identities, and Institutions. Oxford, Blackwell. Silverman, D. (1997). Discourses of Counselling: HIV counselling as social interaction. London: Sage. Weeks 8 and 9. Computer assisted qualitative data analysis Atlas T/I and the analysis of interview data In these sessions we will demonstrate how to use the computer software Atlas T/i. using samples of interview data collected as part of an interview research design. Students will also be encouraged to reflect on the merits and demerits of using computers to analyse qualitative data. The general principles of CAQDAS will be introduced but the bulk of the sessions will be dedicated to a practical introduction to the use of one particular software package Atlas.ti. Atlas is a computer programme that can help to organise data in order to facilitate a thematic analysis. So the use of Atlas should be understood in conjunction with thematic analysis. An introduction to CAQDAS can be found at caqdas.soc.surrey.ac.uk. Atlas.ti will be taught by way of supervised PC-lab based sessions. A study guide to Atlas.ti will be provided. Sessions may include a researcher describing their recent experience of using Atlas, giving a realworld account of what it's really like to do this kind of research - rather than the air-brushed version to be found in a final report or journal article. Indicative Reading Coffey, A. Holbrook, B.and Atkinson, P. (1996) Qualitative data analysis: technologies and representations Sociological Research On-line Vol. 1, No.1. Crang, M.A. Hudson, A.C. Reimer, S.M. Hinchcliffe, S.J. (1997) Software for qualitative research: 1. Prospectus and overview. Environment and Planning A Vol 29: Crang, M.A. Hudson., A.C. Reimer., & S.M. Hinchcliffe, S.J. (1997) Software for qualitative research: 2. Some thoughts on aiding. Environment and Planning A Vol 29: Dey, I. (1993) Qualitative data analysis: a user-friendly guide. Routledge Fielding N., & Lee, R. (1998) Computer Analysis and Qualitative Research. London: Sage. Lewins, A. (2008) CAQDAS: Computer Assisted Qualitative Data Analysis. In N. Gilbert (ed.) Researching Social Life (3rd ed). London: Sage. Lewins, A., & Silver, C. (2007) Using Qualitative Software: A Step by Step Guide. London: Sage.

6 Lewis, B. (2004) NVivo 2.0 and Atlas.ti 5.0: A Comparative Review of Two Popular Qualitative Data- Analysis Programs, Field Methods 16(4): Silver, C., & Fielding, N. (2008) Using Computer Packages in Qualitative Research. In C. Willig & W. Stainton-Rogers (eds.) The Sage Handbook of Qualitative Research in Psychology. London: Sage. Tesch, R. (1990) Qualitative research: analysis types and software tools. Falmer. Assessment The student will have to choose either a qualitative method or a quantitative one for their assessment. Quantitative assessment: Students are required to write a report of words using multinomial logistic regression, factor analysis combined with regression, or multiple correspondence analysis.