Encyclopedia of Gerontology and Population Aging

Living Edition
| Editors: Danan Gu, Matthew E. Dupre

Semiparametric Methods

Living reference work entry
DOI: https://doi.org/10.1007/978-3-319-69892-2_561-1


Semiparametric methods are statistical methods which make use of both parametric and nonparametric components. In particular, they avoid assumptions which fully characterize the distribution of the data while still imposing a minimal structure. Although semiparametric models offer a diverse array of statistical applications, the Cox proportional hazard model and the group-based model for latent heterogeneity in trajectories within populations are commonly used ones and have proven to be particularly valuable in gerontological research.


The notion of a semiparametric model can be understood by first observing the extreme cases of parametric and nonparametric models. Consider the problem of modeling an outcome y as a function of a set of covariates X. The standard linear regression model where y =  + ϵ and the components of ϵ are i.i.d. N(02) is a simple example of a parametric model. On the other extreme are nonparametric models which assume little more than y = f(...

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Authors and Affiliations

  1. 1.Capital One Financial CorporationRichmondUSA
  2. 2.Department of SociologyYale UniversityNew HavenUSA

Section editors and affiliations

  • Kenneth C. Land
    • 1
  • Anthony R. Bardo
    • 2
  1. 1.Department of Sociology and Social Science Research InstituteDuke UniversityDurhamUSA
  2. 2.Department of SociologyUniversity of KentuckyLexingtonUSA