1. Interpreting published multivariate analyses
University of Warwick, Department of Sociology, 2014/15 SO 201: SSAASS (Surveys and Statistics) (Richard Lampard)
Interpreting published multivariate analyses
(Week 12)

2. Some questions to ask in relation to published multivariate analyses
What comparisons do the quantified effects for each explanatory variable relate to? (e.g. What categories or levels are being compared?)
What are the sizes/magnitudes of the effects? Are they statistically significant?
What other explanatory/control variables are being taken into account/controlled for? Are there any interactions between the effects of variables?
How are the results for the models presented? Are the results for a series of models presented; if so, what can be learned from them?
What other aspects of the study have some relevance to the value of the results? (e.g. how may sampling, the way in which concepts have been measured, etc., have impacted upon the validity, reliability and generalisability of the findings?)

3. More specific things to look at/for
Choice of technique
Operationalisation of concepts (in relation to theory and in terms of detail)
Inclusion of controls (including its value to the multivariate analysis) and omitted variables
Impact of data source on results (generalisability; impact of sample design)
Assumptions of technique (e.g. linearity): plausibility and evidence of checks
Presentation of results (Complete? Clarity?)
Interpretation of results (magnitude, statistical significance and meaning of effects (B’s/Exp(B)’s))
Choice of reference categories for categorical variables
Examination (or lack of examination) of interaction effects
Reasons for/value of presenting results from a series of models/regressions
Scope for Type I and/or Type II errors
Use of additional and/or more sophisticated techniques, and reasons for this…

4. Some articles utilising logistic regression
Chatzitheochari, S. and Arber, S ‘Lack of sleep, work and the long hours culture: evidence from the UK Time Use Survey’, Work, Employment and Society 23.1:
Weinberger, M.I., Hofstein, Y. and Krauss Whitbourne, S ‘Intimacy in young adulthood as a predictor of divorce in midlife’, Personal Relationships 15:
Pampel, F.C ‘The Persistence of Educational Disparities in Smoking’, Social Problems 56.3:
Lee, H.J., Elo, I.T., McCollum, K.F. and Culhane, J.F ‘Racial/Ethnic Differences in Breastfeeding Initiation and Duration Among Low-Income Inner-City Mothers’, Social Science Quarterly 90.5:

5. Some specific issues relating to each of the articles
Chatzitheochari and Arber: What can be learned from the series of models? Are the variables ideally operationalised? What does the interaction between class and gender show?
Weinberger et al.: Why are non-significant variables included in the models? How strong is the evidence for the central, interaction effect finding?
Pampel: What can be learned by comparing the models without and with controls? What are the pros and cons of the graphical displays of the trends for different educational levels within different ethnic groups?
Lee et al.: What can be learned from the series of models about the nature of the ethnic differences? What sort of data leads the authors to make use of a second, different form of statistical model?