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Semiparametric partial linear modeling of risk factors for ear infections: the Early Childhood Longitudinal Study

Author

Listed:
  • Le Chen
  • Ruochen Tian
  • Guanjie Chen
  • Ao Yuan
  • Chuan-Ming Li
  • Amy R. Bentley
  • Howard J. Hoffman
  • Charles Rotimi

Abstract

The Early Childhood Longitudinal Study–Kindergarten Class of 2010–2011 (ECLS-K:2011) ascertained timing of ear infections within age specified intervals and parent's/caregiver's report of medically diagnosed hearing loss. In this nationally representative, school-based sample of children followed from kindergarten entry through fifth grade, academic performance in reading, mathematics, and science was assessed longitudinally. Prior investigations of this ECLS-K:2011 cohort showed that age has a non-linear, monotonically increasing functional relationship with academic performance. Because of this knowledge, a semiparametric partial linear model is proposed, in which the effect of age is modeled by an unknown monotonically increasing function along with other regression parameters. The parameters are estimated by a semiparametric maximum likelihood estimator. A test of a constant effect of age is also proposed. Simulation studies are conducted to evaluate the performance of the proposed method, as compared with the commonly used linear model; the former outperforms the latter based on several criteria. We then analyzed ECLS-K:2011 data to compare results of the partial linear parametric model estimation with that of classical linear regression models.

Suggested Citation

  • Le Chen & Ruochen Tian & Guanjie Chen & Ao Yuan & Chuan-Ming Li & Amy R. Bentley & Howard J. Hoffman & Charles Rotimi, 2024. "Semiparametric partial linear modeling of risk factors for ear infections: the Early Childhood Longitudinal Study," Journal of Applied Statistics, Taylor & Francis Journals, vol. 51(3), pages 430-450, February.
  • Handle: RePEc:taf:japsta:v:51:y:2024:i:3:p:430-450
    DOI: 10.1080/02664763.2022.2134316
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