This document discusses the benefits and challenges of integrating qualitative and quantitative research methods. It argues that keeping qualitative and quantitative research separate unnecessarily limits understanding of the social world. Both methods have strengths, and using them together can overcome their individual weaknesses. The document outlines differences in qualitative and quantitative research and provides an example study that combined the methods sequentially and concurrently to better understand long-term poverty impacts in Bangladesh.

1. Moving Beyond the Qual-Quant Divide
Peter Davis
Social Development Research Initiative
Agnes Quisumbing
IFPRI
A4NH Gender-Nutrition Methods Workshop II, December 2-4, 2014
Bioversity International - Rome, Italy

2. Introduction
• Qualitative and quantitative research in the social
sciences are too often conducted separately
• There are a number of reasons for the qual-quant
divide:
– Different philosophical underpinnings
– Different disciplinary traditions
– Different research concerns and subjects
– Different research contexts
– Different gauges and status markers for judging research

3. CG researchers may not make the most of qual
and quant approaches
• From the gender inventory, CGIAR researchers feel that gender
research is the monopoly of qualitative researchers, but at the
same time, is given lower priority or viewed as less legitimate:
“Data analysis is deemed a particularly weak point since analyzing the
gender data is not always prioritized, especially not from surveys. Another
challenge is that the results from the case studies are not always taken as
seriously as survey results but rather considered anecdotal.”

4. But quant methods are often viewed as
extractive
“There is an emphasis on deductive, quantitative methods – especially in the
baselines – even if researchers sometimes mix methods…Some gender data is
even completely neglected during the analysis phase.
The GFPs try add qualitative components to projects, but the need for more
FGDs, unstructured interviews and participatory methods was noted even if
they may be time consuming; both to facilitate the interpretation of
quantitative data and to allow the participants to analyze their own realities.
The latter was seen as important to mitigate power asymmetries between
the researchers and communities, for achieving bottom-up change, and to
address the problem in quantitative research of not always feeding back the
results to the communities.”

5. Moving beyond the divide makes research
better
What are the essential differences between
qualitative and quantitative research approaches?
For five minutes – discuss with your neighbor the
key differences between qualitative and quantitative
research

6. Inherent ambiguity in the subjective-objective distinction
(adapted from Searle 2010)
Ontological (about what exists) Epistemological (about claims to
knowledge)
Subjective • Individual observer dependent (pains,
aches, tickles)
• Collective observer dependence for the
most important aspects of their
existence (e.g. money, marriage,
property boundaries, declarations of
war). Much of the subject matter of the
social sciences.
Non-scientific claims that are
observer dependent. (e.g.
aesthetic claims or judgments
about art and literature - such as -
that Rembrandt was a better
painter than Rubens). Susceptible
to observer bias and idiosyncratic
tastes.
Objective Observer independent – things that exist
independently of the minds of observers
(e.g. mountains, molecules, tectonic
plates). Much of the subject matter of the
natural sciences.
Natural and social science
knowledge claims. Attempt to be
observer-independent and can be
based on either quantified or
non-quantified evidence, or both.

7. Implications
• There is no reason that objectively verifiable claims cannot be made
about ontologically subjective objects or states of affairs in the world
• But subjective claims are not scientific claims (social or otherwise). They
are opinions or tastes
• Claims based on qualitative or quantitative data can be objective
• The natural sciences use both without question
• The social world is challenging because much of it is ontologically
subjective and because states of affairs are causally and contextually
complex
• To restrict ourselves to either quantitative or qualitative data
unnecessarily hinders our ability to understand the social world

8. Page 8
Example of a Q-squared study:
The CPRC-DATA-IFPRI Longitudinal Study

9. The CPRC-DATA-IFPRI Bangladesh longitudinal
study
• The study combined three IFPRI
evaluations which started in 1994,
1996 and 2000/03, and used a mixture
of quantitative and qualitative
methods
• In 2006-7 we resurveyed the entire set
of these households (plus new
households created due to household
division) in three phases (qual-quant-qual)

10. The 2006-7 Study’s 3 Phases
3 phases of data collection:
• Summer 2006: focus group discussions
investigating causes of decline and improvement
and the long term impact of 3 interventions (116
FGDs in 11 districts)
• Winter 2006-7: quantitative resurvey of panel
households (1787 core + 365 splits in 14 districts)
• Spring-Summer 2007: life-history interviews and
village histories in 8 districts (161 households –
293 individuals)

11. Map of the Study Sites
Arrows show life-history
districts (number of
interviews)
Nilphamari (38)
Kurigram (39)
Tangail (39)
Mymensingh (18)
Kishoreganj (19)
Manikganj (72)
Jessore (36)
Cox’s Bazar (32)

12. What does qual research bring to quant?
• Challenges in researching the social world
– dealing with complexity
– intangibility
– ontological subjectivity
– morality and ethics
• Exploration of context (in space and time)
• A better qualitative understanding of social realities so that good
variables are chosen for quantitative measurement
• Better identification of complex processes and causal relationships –
which can then be more systematically investigated quantitatively (qual
work to inform formulation of hypotheses that can be tested
quantitatively)

13. What does quant research bring to qual?
• Larger numbers of randomly selected cases control bias and
increase representativeness of cases and therefore
generalizability of findings
• The ability to compare the effects of interventions without
being led astray by random variation or confounding causes
• Reduction in observer dependence due to larger numbers of
cases and more formal methods
• Systematic, transparent, repeatable methods (replicability)

14. Practical issues in combining qualitative and quantitative
research
1) Planning
• clarifying research questions
• piloting and field testing
• using flexible qual approaches in exploratory research
• identifying variables – drawing from qualitative research to
help design quant research instruments
• consider how to avoid qual findings being seen as anecdotal or
with questionable representativeness?
• hypothesis testing and comparing interventions

15. 2) Sampling
• What is the population?
• Are samples representative of the population?
• What is a case?
• Will qual cases be a subsample of quant sample? If
yes, should be linked using same IDs

16. 3) Fieldwork
Will the methods be sequential?
• quantqualquant
• qualquantqual
Parallel?
• quant and qual occurring at the same time but separately
Concurrent?
• quant and qual occurring at the same time in the same place
(integrated fieldwork)
Personnel
• Training, expertise, supervision, rapport

17. 4) Data analysis decisions
• Do analysts have the necessary skills to analyse both sets of data?
• Will quant data arise from qual interviews? Quantifying qual data – what
is lost in reduction to numbers too early?
• Can quant data be used in qual analysis?
5) Presentation of findings and user engagement
• Are findings presented separately?
• What happens when qual and quant findings disagree? Using
disagreements as opportunities for learning

18. 6) Ethical concerns
• Protection of research participants
– Is there more risk of harming participants?
– Maintenance of anonymity when ‘thick descriptions’
are part of the dataset
– Release of data to other users
• Is there greater potential to influence policy in a
positive direction? And less risk of misrepresenting
social, economic, political reality?

19. Useful publications and websites:
Journals
• Journal of mixed methods research http://mmr.sagepub.com
• International Journal of Multiple Research Approaches http://mra.e-contentmanagement.com
Books, papers and book chapters
• Bryman. A. Social research methods. Chapters 21 and 22
• Mayoux, L. “Quantitative, Qualitative or Participatory? Which Method, for What and When?”
Chapter 13 in Desai and Potter, Doing Development Research. Sage: London.
• Tashakkori, A. Handbook of mixed methods in social & behavioural research
• R. Kanbur (Ed.), Q-squared: Qualitative and quantitative methods of poverty appraisal. New
Delhi, India: Permanent Black
– Available from www.q-squared.ca/pdf/Q2_WP1_Kanbur.pdf
• McGee, R. Constructing Poverty Trends in Uganda: A Multidisciplinary Perspective.
Development and Change 35(3): 499–523 (2004).
Useful websites:
• www.q-squared.ca a research project looking at mixed methods approaches in poverty
research
• www.compasss.org linked to Charles Ragin’s Qualitative Comparative Analysis approach (QCA)