Week 5 Assignment 1
Mixing Qualitative and Quantitative Research in Developmental Science: Uses and Methodological Choices

Hirokazu Yoshikawa Harvard Graduate School of Education

Thomas S. Weisner University of California, Los Angeles

Ariel Kalil University of Chicago

Niobe Way New York University

Multiple methods are vital to understanding development as a dynamic, transactional process. This article focuses on the ways in which quantitative and qualitative meth- odologies can be combined to enrich developmental science and the study of human development, focusing on the practical questions of “when” and “how.” Research situations that may be especially suited to mixing qualitative and quantitative ap- proaches are described. The authors also discuss potential choices for using mixed quantitative– qualitative approaches in study design, sampling, construction of mea- sures or interview protocols, collaborations, and data analysis relevant to developmen- tal science. Finally, they discuss some common pitfalls that occur in mixing these methods and include suggestions for surmounting them.

Keywords: mixed methods, quantitative, qualitative

How does knowledge gleaned from words complement knowledge gleaned from numbers,

and vice versa? How and when does the com- bination of quantitative and qualitative data col- lection and analytic methods enrich develop- mental science? Our science increasingly relies on multimethod approaches to examining de- velopmental processes (Garcia Coll, 2005; So- ciety for Research in Child Development, 2005; Weisner, 2005). As a consequence, develop- mental scholars have broken new ground over the past decade in understanding the cognitive, linguistic, social, cultural, and biological pro- cesses related to human development and fam- ily life. In this article, we focus on the many productive ways in which quantitative and qual- itative methods can be combined to study hu- man development.

Several summaries and handbooks focusing on integrating qualitative and quantitative data collection and analysis methods in the social sciences have been published recently (Axinn & Pearce, 2006; Bernard, 1995, 1998; Creswell & Plano Clark, in press; Greene & Caracelli, 1997; Tashakkori & Teddlie, 1998, 2003). Onwueg- buzie and Leech (2005) argue for combining the contrasting “Qs” (polarized quantitative and qualitative methods tracks and courses) into, for example, integrated bilingual, pragmatic re- search methods courses in education. In this article, we focus specifically on the uses of

Hirokazu Yoshikawa, Harvard Graduate School of Edu- cation, Harvard University; Thomas S. Weisner, Depart- ments of Psychiatry and Anthropology, University of Cali- fornia, Los Angeles; Ariel Kalil, Harris School of Public Policy, University of Chicago; Niobe Way, Department of Applied Psychology, New York University.

This article was partially based on a conference, “Mixed Meth- ods Research on Economic Conditions, Public Policy, and Child and Family Well-Being,” sponsored by the National Poverty Center, University of Michigan, in June of 2005. Additional support for that conference was provided by the American Psy- chological Association and the National Institute of Child Health and Human Development to Ariel Kalil and Hirokazu Yo- shikawa. Work on this article by Thomas S. Weisner was sup- ported by the University of California, Los Angeles Field Work Training and Qualitative Data Lab, National Institute of Child Health and Human Development 5 P30 HD004612 and Semel Institute, Center for Culture & Health. Work on this article by Hirokazu Yoshikawa and Niobe Way was supported by National Science Foundation Behavioral and Cognitive Sciences Grant 021589 to the New York University Center for Research on Culture, Development, and Education. Work on the article by Hirokazu Yoshikawa and Ariel Kalil was also supported by Scholars grants from the William T. Grant Foundation.

Correspondence concerning this article should be ad- dressed to Hirokazu Yoshikawa, Harvard Graduate School of Education, 14 Appian Way, Room 704, Cambridge, MA 02138. E-mail: hiro_yoshikawa@harvard.edu

This article is reprinted from Developmental Psychology, 2008, Vol. 44, No. 2, 344 –354.

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Qualitative Psychology © 2013 American Psychological Association 2013, Vol. 1(S), 3–18 2326-3598/13/$12.00 DOI: 10.1037/2326-3598.1.S.3

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mixed methods for developmental science. We answer practical questions of when and how: When might mixing qualitative and quantitative approaches be useful in a developmental study? What are the methodological choices involved in qualitative and quantitative inquiry in studies of human development?

By quantitative research, we mean methods of inquiry that analyze numeric representations of the world. Survey and questionnaire data as well as biological or physiological data are of- ten analyzed in quantitative units. Inquiry that relies on qualitative methods collects and ana- lyzes non-numeric representations of the world—words, texts, narratives, pictures, and/or observations. The epistemological as- sumption underlying our discussion of mixed methods is that in scientific endeavors, the world can be represented through both numbers and words and that numbers and words should be given equal status in developmental science. Developmental science is a holistic enterprise including the social, neurological, and biologi- cal sciences. Although particular disciplines may emphasize particular methods of data col- lection and analysis, this is no reason to limit a particular program of research in developmental science to a single method.

In this article, we make the distinction be- tween qualitative and quantitative data and qualitative and quantitative data analysis (Ax- inn & Pearce, 2006). The world is not inherently qualitative or quantitative; it is the act of human representation through numbers or non-numeric signifiers like words that make aspects of the scientific enterprise qualitative or quantitative. Behaviors or contexts relevant to human devel- opment are not inherently qualitative or quanti- tative, but the methods of representation through which behaviors or contexts are re- corded in research are. In this article, we define qualitative data as information that has been collected not in numeric form but in texts, nar- ratives, or observations (including pictures and video). We define quantitative data as informa- tion that has been collected in numeric form (e.g., counts, levels, or Likert-format re- sponses). We define qualitative data analyses, similarly, as forms of analysis that do not rely on numeric representation and quantitative data analyses as forms that do. Qualitative ap- proaches cover a wide range of methods, just as there is a wide range of quantitative methods.

An important corollary to this distinction between qualitative and quantitative data and data analysis is that all four combinations of these two categorizations are possible. That is, qualitative data can be analyzed through either qualitative or quantitative data analysis techniques, as can quantitative data. Interview transcripts can be reliably coded for the fre- quency of mention of themes, the numbers of words or keywords, or the complexity of vo- cabulary and statistically analyzed. Ethno- graphic data from the world’s cultures have been coded for quantitative analysis (Rogoff, Sellers, Pirotta, Fox, & White, 1975). Con- versely, individuals above or below a cut-off on a Likert scale or continuous dimension can be analyzed and characterized qualitatively, without further numeric representation.

Before turning to our primary questions, we begin with three general beliefs that guide our discussion of mixing qualitative– quantitative methods in studies of human development. First, integrating these approaches can bring us closer to understanding a developmental pro- cess than either set of methods can on its own. This belief goes beyond the commonly stated value of triangulation across methods, a strategy that focuses on convergence across methods on a particular finding, or separating out methods variance. Rather, our belief is that the combina- tion of words and numbers can bring us closer to the complexity of developmental change by providing divergent as well as convergent data. Divergent data across methods can spur further inquiry and refinement of theory rather than simply representing disconfirming information (Sieber, 1973). Integrated methods can also make a study more believable to broader audi- ences, because they represent the world more completely.

Our second belief is that the particular research question concerning developmental processes should determine whether and how qualitative and quantitative methods should be combined. As with other forms of research, methods should fol- low the question rather than vice versa. This means that not all research studies in devel- opmental science call for the use of both kinds of methods. We will describe certain common types of research questions that we think lend themselves to the process of mix- ing methods.