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This dissertation examines the quality of routine tuberculosis data in Uganda, identifying sources of variation and assessing the implementation of a biometric approach for patient identification
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Define the objectives of your evaluation clearly.
02
Identify the research questions you aim to answer.
03
Choose the mixed methods approach that suits your evaluation (e.g., convergent, explanatory, exploratory).
04
Collect qualitative data through interviews, focus groups, or surveys.
05
Collect quantitative data through structured surveys, experiments, or secondary data analysis.
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Analyze qualitative data for themes and narratives relevant to your objectives.
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Analyze quantitative data using statistical methods for trends and patterns.
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Integrate findings from both qualitative and quantitative analyses to provide comprehensive insights.
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Draw conclusions and make recommendations based on the integrated findings.
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Prepare a report that clearly communicates the mixed methods evaluation results.

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Mixed methods evaluation refers to an approach that combines qualitative and quantitative research methods to assess and evaluate a program, project, or intervention.
Individuals or organizations conducting research or evaluations that incorporate both qualitative and quantitative data may be required to file a mixed methods evaluation, particularly if mandated by funding bodies or regulatory agencies.
To fill out a mixed methods evaluation, start by clearly defining your evaluation questions. Collect both qualitative and quantitative data, analyze the findings separately, and then integrate the results to provide a comprehensive evaluation. Finally, report the findings in a structured format.
The purpose of mixed methods evaluation is to provide a more complete understanding of the evaluation subject by leveraging the strengths of both qualitative and quantitative approaches, allowing for a more nuanced analysis.
Information that must be reported includes the evaluation objectives, the methodologies used (both qualitative and quantitative), data collection methods, analysis techniques, findings from both data types, and conclusions drawn from the integration of the findings.
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