Mixed Methods: A short guide to applied mixed methods research

by Sam Ladner

This book provides a brief introduction to mixed research methods for applied researchers working in technology, marketing, communications, or market research.

Genres: Design, Nonfiction

100 pages, Paperback

Published May 1, 2019

About the author

Sam Ladner is a sociologist who researches the intersection of work, technology, and organizations. She has worked at major technology companies including Microsoft and Amazon, creating real-world technology products. She received her PhD in sociology from York University, served as Postdoctoral Fellow at Ryerson University’s School of Information Technology Management. She is also the author of Practical Ethnography: A Guide To Doing Ethnography in The Private Sector and Mixed Methods: A Guide to Applied Mixed Methods Research

Reviews

[Marcela · Rating 4 out of 5]

Short but mind-expanding

This was both down to earth and intellectual at the same time. I would say it’s written at the graduate school level since it assumes you know the difference between deductive/inductive and constructivist/objectivist. I will have to read it again before I can say I get it but I definitely felt like my brain got a workout by reading this—in a good way.

[Fernando Medeiros santos · Rating 4 out of 5]

O aviso dessa vez é o seguinte: tenho muitas dificuldades para avaliar livros técnicos principalmente quando tomei duas doses de uísque, mas vou tentar o meu melhor.

Esse aqui é uma ótima pedida para os amigos designers que trabalham com pesquisa de experiência e querem trazer um viés mais quantitativo para suas investigações. Ao mesmo tempo também é ótimo para os analistas de dados que as vezes sentem que no meio daqueles gráficos todos faltam alguns "por ques" e "comos".

Basicamente Sam Ladner apresenta como realizar uma pesquisa de método misto (mixed method) de forma muito prática. E não, não é uma quali e depois uma quanti ou vice e versa; são as duas ao mesmo tempo. No início é de explodir a cabeça, mas depois você vai se acostumando.

Não é a leitura mais fácil do mundo (considerando, inclusive, que você vai precisar ler em inglês), mas é um livro curto. Em menos de 100 páginas a autora apresenta seus métodos da concepção até a apresentação de resultados de um jeito prático, com bons exemplos e muita base teórica.

Leia se você não está satisfeito em fazer apenas um tipo de pesquisa e quer se aventurar em novos métodos.

[Maksim Korolev · Rating 3 out of 5]

Not very practical.

Pros:
- Interesting parts about philosophical foundations of quantitative and qualitative research methods
- links to other books about specific research questions

Cons:
- just one case, which seems a little artificial

If you want to get more familiar with mixed methods, I would rather advice
- to google "spotify mixed methods" or "athenahealth machine learning in ux", both teams wtote several brilliant articles on topic.
- to find somebody from Facebook/Spotify/any other mature UX team on uxcoffeehours or adplist and ask about their process.

[Glenn Stevens · Rating 5 out of 5]

A short book that mixes (yep) philosophical, nothing short of mind-expanding explorations, with practical techniques to use next week on the job. Changed the lenses through which I look at my job as a user researcher. Enjoyed the writing style, quotes and footnotes.

[Flávio Araújo · Rating 4 out of 5]

Mixed Methods brings several reflections on research dilemmas to service design point of view. Sam starts to present two research methods: quantitative and qualitative and shows us how they need to be complementary.
Another interesting point is about the approaches: Deductive, narrower and used when we have clear and precise hypotheses; and inductive, used to first understand the subject as a whole. And after that, he presents us with some situations, which method and approach could be better to start with and how to converge to understand and interpret the root causes of the research problem.
I just missed more details and real examples with used tools and it works, but it's a good and quick read

[meera ramachandran · Rating 5 out of 5]

Short and insight-packed read

I am qualitative-trained researcher interested in strengthening my mixed methods approaches and this was the perfect read for that purpose. I would definitely use the coherence / focus and scale and correlation concepts with me forever. Thanks for a great read!

[Plof · Rating 4 out of 5]

Explains in clear terms the fundamental differences between quant/qual methods and how they can be used together by practitioners. Brings to the fore the real value of the qualitative method in data analysis. Short and interesting read.

[Liz · Rating 5 out of 5]

Concise while providing illustrative examples, and articulates what every successful researcher needs to know. It's a great read for even the most experienced research as Ladner's explanations will empower you with new language to explain concepts.

[Meghan Burke · Rating 5 out of 5]

Really great read for someone like me who has made the transition from the academy to industry; who now often works on mixed methods teams; and who draws on her sociological training to drive meaningful (and endlessly fascinating!) customer insights.

[Rhye Mirch · Rating 5 out of 5]

This book was an incredible introduction to mixing methods in a corporate setting. It started from the core philosophical differences between deductive and inductive reasoning and how mixing methods is challenging but can provide many benefits.

[Kristina · Rating 4 out of 5]

If the book were about twice as long, it would be indispensable for researchers.

[Paulo Peres · Rating 5 out of 5]

Livro excelente!!! Conciso e precisamente escrito na medida certa entre profundo e técnico, e objetivo. Sam nos mostra ótimos argumentos do porque misturar/ combinar métodos quali e quanti. Sam deixa o texto extremamente rico e gostoso de ser lido para ajudar o pesquidador a ampliar seus argumentos sobre processos de pesquisa. Nao é um guia how-to, mas why-now.

Compre.

[Xavi · Rating 3 out of 5]

This book accomplishes two key objectives with exceptional clarity. First, it effectively delineates the fundamental distinction between qualitative and quantitative research methodologies. Second, it offers practical guidance on their integration. The author achieves this with remarkable concision, striking an excellent balance between accessibility and academic rigor, particularly through thoughtful references to philosophy of science scholars.

In my opinion, the book's strongest section is its first part, which presents the conceptual framework (up to page 38). The subsequent sections, while comprehensive, focus on implementation guidelines that feel somewhat self-evident.

At its core, the book challenges how we commonly treat quantitative and qualitative methods as if they were of the same nature, when in fact they are based in two fundamentally different schools of thought (objectivism and constructivism) which are to some extent irreconcilable because they represent distinct ontological perspectives. As the author aptly notes, "mixed methods research is not simply about mixing data sets-it's about mixing philosophical points of view."

The text skillfully contrasts these approaches: quantitative methods, rooted in numbers, prioritize scale and causation, while qualitative methods focus on descriptive qualities, coherence, and participant perspectives. Quantitative research typically adopts an objectivist stance, assuming reality is stable and measurable (exemplified by binary gender categorization in surveys, which treats biological sex as an objective reality). In contrast, qualitative research embraces constructivism, where researchers build their understanding of concepts like gender from participants' own interpretations and experiences. This represents the constructivist view that humans actively construct reality through their interpretations (brief foot note: as Luckman explains, this process of "reification" occurs when these social constructions come to be viewed as natural phenomena).

These philosophical differences significantly impact research design. Quantitative methods resist mid-study modifications, prioritizing stable methods, participants, and categories to ensure rigor. Qualitative approaches, however, welcome ongoing adjustments as new insights emerge. This creates a natural tendency for quantitative research to follow top-down approaches, while qualitative research favors bottom-up methodologies. Particularly insightful is the book's definition of induction as the act to "elevate the meaning," which captures the essence of qualitative analysis.

In conclusion, this work serves as an excellent resource for developing more sophisticated research plans, successfully combining straightforward accessibility with scholarly rigor.