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Reliability – Ensures consistent and repeatable results

Validity – Measures what it intends to measure; internal & external

Objectivity – Minimizes researcher bias

Generalizability – Findings apply to broader populations

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Credibility – Confidence in findings’ accuracy

Transferability – Applicability to similar contexts

Reflexivity – Awareness of researcher influence

Thick Description – Detailed contextual understanding

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Integration of Data – Combining qualitative and quantitative findings

Convergence & Complementarity – Bringing together strengths of both approaches

Validity & Reliability – Balancing measurement precision with context

Triangulation – Cross-verifying findings from multiple sources

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Systematic Approach – Structured research processes

Validity & Reliability – Maintaining research accuracy

Transparency – Clear documentation and open methodology

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Objectivity vs. Subjectivity – Quantitative seeks neutrality, qualitative values perspective

Generalizability vs. Contextual Depth – Large sample vs. in-depth insights

Numbers vs. Narratives – Statistical data vs. participant experiences

Replication vs. Uniqueness – Standardization vs. case-specific insights