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

• Published in: Journal of applied statistics 2024-02, Vol.51 (3), p.430-450
• Main Authors: Chen, Le, Tian, Ruochen, Chen, Guanjie, Yuan, Ao, Li, Chuan-Ming, Bentley, Amy R., Hoffman, Howard J., Rotimi, Charles
• Format: Article
• Language: English
• Subjects: Academic achievement; Age factors; Childhood; Ear; Early Childhood Longitudinal Study; Kindergarten; Longitudinal studies; Maximum likelihood estimators; monotonice function; Parameter estimation; partial linear model; Performance evaluation; Regression models; semiparametric maximum likelihood estimation; Statistical methods
• ISSN: 0266-4763; 1360-0532
• DOI: 10.1080/02664763.2022.2134316

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.