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This is a repository copy of An examination of therapists professional characteristics as moderators of the effect of feedback on psychological treatment outcomes. White Rose Research Online URL for
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Identify your research question or hypothesis.
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Determine the levels of analysis and variables you will be studying.
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Gather your data at each level of analysis.
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Organize your data into a hierarchical structure.
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Researchers and analysts who are interested in examining relationships and differences between variables at different levels of a hierarchy.
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Individuals conducting studies that involve nested or grouped data, such as students within schools or patients within hospitals.
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Research projects that aim to understand within-group variation and between-group differences.
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A multilevel analysis is a statistical technique used to analyze data that is structured at more than one level, typically involving data organized by groups or clusters, such as individuals nested within organizations.
Researchers or organizations that conduct studies involving hierarchical data structures, such as educational assessments or health studies, are required to file a multilevel analysis.
To fill out a multilevel analysis, one must specify the levels of analysis, choose appropriate statistical models, prepare the data accordingly, and run the analysis using software designed for hierarchical modeling.
The purpose of a multilevel analysis is to understand the influence of variables at different levels and to improve the accuracy of inferences drawn from complex data that involves multiple hierarchies.
The report should include information on the data structure, the models used, assumptions made, results including estimates and significance levels, and interpretations of the findings.
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