Purpose <p>In measurement-based care or routine outcome monitoring self-report questionnaires are used to monitor how a patient fares in therapy. Interpretation and utilization of test results are improved and communication facilitated when raw scores are converted to common metrics, such as standard scores (T-scores) and percentile rank scores. Both types of common metrics are described and reviewed and a warning is issued that percentiles may be misinterpreted at the tails of the scale.</p> Methods <p>Data from the Manchester Short Assessment (MANSA) was used to investigate various approaches to obtain T-scores. The study analyzed cross-sectional data from two normative samples: a representative sample of the Dutch general population (N = 11,789) and a clinical sample (N = 9987) of patients with substance use disorder. Linear, normalized, and IRT-based T-scores were compared.</p> <p>Results revealed that T-scores derived from a linear conversion were biased at the lower end of the scale. Normalizing raw test scores through either Rankit normalization or by an IRT approach yielded improved and quite similar T-scores. For all possible raw scores on the MANSA, corresponding normalized T-scores are presented, as well as Percentile Rank scores for the two reference groups. Finally, cut-off values for reliable change and clinically significant change are presented for raw scores and T-scores.</p> Conclusion <p>Practical guidance is offered for converting raw test scores into two common metrics: normalized T-scores and Percentile Rank scores. For T-scores, simple linear conversions yielded biased results. These findings have implications for test developers, practitioners, and researchers who want to express test results in valid and unbiased common metrics.</p>

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The Devil Is in the Tail: Manchester Short Assessment of Quality of Life (MANSA) test percentiles and normalized T-scores

  • Edwin de Beurs,
  • Bertus F. Jeronimus

摘要

Purpose

In measurement-based care or routine outcome monitoring self-report questionnaires are used to monitor how a patient fares in therapy. Interpretation and utilization of test results are improved and communication facilitated when raw scores are converted to common metrics, such as standard scores (T-scores) and percentile rank scores. Both types of common metrics are described and reviewed and a warning is issued that percentiles may be misinterpreted at the tails of the scale.

Methods

Data from the Manchester Short Assessment (MANSA) was used to investigate various approaches to obtain T-scores. The study analyzed cross-sectional data from two normative samples: a representative sample of the Dutch general population (N = 11,789) and a clinical sample (N = 9987) of patients with substance use disorder. Linear, normalized, and IRT-based T-scores were compared.

Results revealed that T-scores derived from a linear conversion were biased at the lower end of the scale. Normalizing raw test scores through either Rankit normalization or by an IRT approach yielded improved and quite similar T-scores. For all possible raw scores on the MANSA, corresponding normalized T-scores are presented, as well as Percentile Rank scores for the two reference groups. Finally, cut-off values for reliable change and clinically significant change are presented for raw scores and T-scores.

Conclusion

Practical guidance is offered for converting raw test scores into two common metrics: normalized T-scores and Percentile Rank scores. For T-scores, simple linear conversions yielded biased results. These findings have implications for test developers, practitioners, and researchers who want to express test results in valid and unbiased common metrics.