Analyzing Grant Data: Methods, Interpretation, and Mixed-Approach Strategies for Non-Profit Organizations

This article explores methodologies for analyzing grant data, emphasizing the complementary roles of qualitative, quantitative, and mixed-method approaches. It reviews qualitative techniques such as thematic, content, and narrative analysis, which capture the lived experiences of beneficiaries, alongside quantitative methods that provide measurable evidence through descriptive and inferential statistics. The article highlights the strategic value of integrating these approaches to strengthen validity, reliability, and funder confidence. Data interpretation is presented as a contextualized process that incorporates local realities, baseline indicators, and sector benchmarks. Practical considerations such as visualization, software tools, and iterative analysis further enhance clarity and credibility. Case illustrations demonstrate how combining diverse methods produces actionable insights that inform strategic decision-making and strengthen organizational sustainability.

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Publication Details

Published
2025-01-01
DOI
https://doi.org/10.64357/neya-gjnps-grant-data-05
Citations
2
Primary Topic
Healthcare Policy and Management
Type
article
Field-Weighted Citation Impact
6.26
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article

Analyzing Grant Data: Methods, Interpretation, and Mixed-Approach Strategies for Non-Profit Organizations

Anna Neya Kazanskaia
2 citations
Healthcare Policy and Management
6.26
article

Analyzing Grant Data: Methods, Interpretation, and Mixed-Approach Strategies for Non-Profit Organizations

Anna Neya Kazanskaia
article en
2 citations

Abstract

This article explores methodologies for analyzing grant data, emphasizing the complementary roles of qualitative, quantitative, and mixed-method approaches. It reviews qualitative techniques such as thematic, content, and narrative analysis, which capture the lived experiences of beneficiaries, alongside quantitative methods that provide measurable evidence through descriptive and inferential statistics. The article highlights the strategic value of integrating these approaches to strengthen validity, reliability, and funder confidence. Data interpretation is presented as a contextualized process that incorporates local realities, baseline indicators, and sector benchmarks. Practical considerations such as visualization, software tools, and iterative analysis further enhance clarity and credibility. Case illustrations demonstrate how combining diverse methods produces actionable insights that inform strategic decision-making and strengthen organizational sustainability.

Openalex Percentile: Top 4%
Healthcare Policy and Management
6.26
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Analyzing Grant Data: Methods, Interpretation, and Mixed-Approach Strategies for Non-Profit Organizations — Anna Neya Kazanskaia · (2025) | TGRS Research Map | TGRS