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

Le Chen; Ruochen Tian; Guanjie Chen; Ao Yuan; Chuan-Ming Li; Amy R Bentley; Howard J Hoffman; Charles Rotimi

doi:10.1080/02664763.2022.2134316

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

J Appl Stat. 2022 Oct 21;51(3):430-450. doi: 10.1080/02664763.2022.2134316. eCollection 2024.

Authors

Le Chen¹, Ruochen Tian², Guanjie Chen³, Ao Yuan^{2

3}, Chuan-Ming Li¹, Amy R Bentley³, Howard J Hoffman¹, Charles Rotimi³

Affiliations

¹ Division of Scientific Programs, National Institute on Deafness and Other Communication Disorders, Rockville, MD, USA.
² Department of Biostatistics, Bioinformatics and Biomathematics, Georgetown University, Washington, DC, USA.
³ Center for Research on Genomics and Global Health, NHGRI, NIH, Bethesda, MD, USA.

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.

Keywords: Early Childhood Longitudinal Study; monotonice function; partial linear model; semiparametric maximum likelihood estimation.

Grants and funding

This work is supported in part by the National Center for Research Resources at Foundation for the National Institutes of Health NIH grant 2G12RR003048. Le Chen was supported by the Federal Pathway Program at the National Institute on Deafness and Other Communication Disorders (NIDCD). The U.S. ECLS-K: 2011 study is a longitudinal cohort study of students evaluated from the start of kindergarten (2010) through fifth grade (2016) and is sponsored by the National Center for Education Statistics (NCES) within the Institute of Education Sciences (IES) of the U.S. Department of Education. The ECLS-K:2011 hearing examinations and questions were funded by NIDCD via an Interagency Agreement with NCES. The evaluations were overseen by audiologists from the National Institute for Occupational Safety and Health (NIOSH), Centers for Disease Control and Prevention (CDC).