The Benefits of Robustness in Measures of Spatiotemporal Stability: An Investigation in Childhood Apraxia of Speech.

Purpose: When using the spatiotemporal index (STI) to measure variability across repetitions of the same stimulus, researchers will typically screen and remove productions that contain errors or disfluencies. However, this screening process is highly subjective, reduces the amount of data available,...

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Publicado en:Journal of Speech, Language & Hearing Research Vol. 68; pp. 3495 - 3507
Autores principales: Wisler, Alan, Vuolo, Janet, Fletcher, Annalise
Formato: Artículo
Publicado: American Speech-Language-Hearing Association 2025 Supplement
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Acceso en línea:Ver este registro en EBSCOhost
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        10.1044/2024_JSLHR-24-00360
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        atl: The Benefits of Robustness in Measures of Spatiotemporal Stability: An Investigation in Childhood Apraxia of Speech.
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        au:
          Wisler, Alan
          Vuolo, Janet
          Fletcher, Annalise
        affil:
          Department of Mathematics and Statistics, Utah State University, Logan
          Department of Speech and Hearing Science, The Ohio State University, Columbus
          Department of Communicative Disorders and Deaf Education, Utah State University, Logan
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        Sound recordings
        Social classes
        Children
        Research funding
        T-test (Statistics)
        Descriptive statistics
        Physiological aspects of speech
        Simulation methods in education
        Speech evaluation
        Speech apraxia
        Video recording
      sug:
        subj:
          Sound recordings
          Social classes
          Children
          Sound recording merchant wholesalers
          Record Production
          Integrated Record Production/Distribution
          Research funding
          T-test (Statistics)
          Descriptive statistics
          Physiological aspects of speech
          Simulation methods in education
          Speech evaluation
          Speech apraxia
          Video recording
      ab: Purpose: When using the spatiotemporal index (STI) to measure variability across repetitions of the same stimulus, researchers will typically screen and remove productions that contain errors or disfluencies. However, this screening process is highly subjective, reduces the amount of data available, and may generate samples that are less representative of true speech difficulties. In this study, we quantify the degree to which the STI is skewed by the inclusion of highly deviating productions and whether alternative calculations could better facilitate their inclusion. Method: First, we conducted a controlled simulation to quantify how highly deviating productions skew STI values. The traditional STI calculation was compared to three robust alternative measures proposed to reduce the influence of outlying productions. Next, using audio recordings from typically developing (TD) children and children with childhood apraxia of speech (CAS), we investigated how effectively each STI measure differentiated the two groups. Results: Simulation findings demonstrated that the STI can be heavily skewed (more than doubling in value) by the inclusion of a single outlying production. In contrast, the robust alternative measures were all able to incorporate multiple outlying productions before their value was significantly altered. The proposed best-5 STI measure produced larger group differences between TD children and children with CAS compared to the traditional STI in both "Mom pets the puppy" and "Buy Bobby a puppy" stimuli. Conclusions: The STI is highly sensitive to outlying productions and requires careful consideration of the repetitions included in its calculation. However, conservative approaches to data removal may be problematic when studying populations that are prone to fluency errors. In these scenarios, more robust alternatives to the STI, such as the best-5 STI measure, may provide a more practical approach to measuring speech variability.
      pubtype: Academic Journal
      doctype: Article
      src: R
    language: English
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