Chapter 17. Analysis, Interpretation and Research Quality

Quantitative analysis. Choose methods suited to your design and data, check assumptions, handle missing data transparently, and report effect sizes and uncertainty. Pre-register analysis plans where possible, and avoid selective reporting [45][46].

Qualitative analysis. Approaches include thematic analysis, grounded theory, narrative analysis, discourse analysis and framework analysis. Thematic analysis involves familiarization, coding, developing and reviewing themes, defining and naming them, and writing up [50][51]. Keep an audit trail of coding decisions.

Quality criteria for qualitative research. Lincoln and Guba proposed credibility, transferability, dependability and confirmability. Tracy proposes eight criteria, including a worthy topic, rich rigour, sincerity, credibility, resonance, significant contribution, ethics and meaningful coherence [52][53]. Use strategies such as triangulation, member checking, thick description, reflexivity and peer debriefing.

Working across languages. If data are collected in one language and reported in another, decide how to handle translation (translate transcripts or code in the original language), record choices, and consider reporting key terms in the original language alongside translations [57].

Interpretation in context. Avoid treating Southeast Asian societies through frameworks developed elsewhere without testing their fit. Seek local scholarly input, discuss findings with participants and partners, and consider alternative explanations.

Mixed methods integration. Integrate the data purposefully: for example, use interviews to explain survey results, or use survey findings to test patterns identified in qualitative work [45].

Limitations. Be honest about sampling, language, access, power, bias and political constraints. Limitations are part of good scholarship and help readers interpret findings.

Participant validation and feedback. Where safe and appropriate, share draft findings with participants and local partners and consider their responses.

Data management. Organize data and documentation, record versions and decisions, and plan secure storage and archiving, following FAIR principles where consistent with privacy and community rights [13].

Reflection: How will you show readers that your analysis is credible, including how you handled language and translation?