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Defining Practical Significance Is Hard, But We Should Do It Anyway.

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    This summary is machine-generated.

    Researchers increasingly need to consider practical significance alongside statistical significance (p values). This article reviews practical significance and offers methods for its examination and communication in quantitative analysis.

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    Area of Science:

    • Biostatistics
    • Nursing Education Research

    Background:

    • The interpretation of p values, a long-standing practice in quantitative analysis, faces increasing scrutiny.
    • There is a growing recognition of the limitations of relying solely on statistical significance.

    Purpose of the Study:

    • To review the concept of practical significance in statistical analysis.
    • To compare practical significance with the evolving understanding of statistical significance.
    • To provide examples for examining and communicating practical significance.

    Main Methods:

    • Review of the concept of practical significance.
    • Comparison between practical and statistical significance.
    • Illustrative examples of assessing and reporting practical significance.

    Main Results:

    • Statistical significance (p values) alone is insufficient for interpreting research findings.
    • Practical significance offers a complementary and crucial layer of interpretation.
    • Methods for evaluating and communicating practical significance can enhance the understanding of study outcomes.

    Conclusions:

    • The urgency to move beyond simplistic p-value interpretation is increasing.
    • Actively considering practical significance is essential for robust quantitative analysis.
    • Effective communication of practical significance is vital for informing research and practice.