Continuous-time modelling of irregularly spaced panel data using a cubic spline model

Sy Miin Chow, Guangjian Zhang

Research output: Contribution to journalArticle

4 Citations (Scopus)

Abstract

Continuous-time modelling remains a somewhat 'idealized' representation tool. Even though conceptualizing a dynamic process as a continuous process has clear appeal from a theoretical standpoint, practical tools that allow researchers to effectively map an idealized continuous model onto a set of discrete-time observed data are still lacking observed data. Irregularly spaced longitudinal data frequently arise in empirical settings because of the prevalence of longitudinal studies with partially randomized measurement intervals and other related designs. We present a practical approach that capitalizes on a nonparametric spline interpolation approach to impute the gaps in irregularly spaced panel data. Simulated and empirical examples are provided to demonstrate the applicability of the proposed approach to studies of group-based dynamics using panel data.

Original languageEnglish (US)
Pages (from-to)131-154
Number of pages24
JournalStatistica Neerlandica
Volume62
Issue number1
DOIs
StatePublished - Feb 1 2008

Fingerprint

Cubic Spline
Panel Data
Continuous Time
Spline Interpolation
Longitudinal Study
Appeal
Dynamic Process
Longitudinal Data
Modeling
Discrete-time
Interval
Model
Demonstrate
Continuous time
Panel data
Cubic spline
Design

All Science Journal Classification (ASJC) codes

  • Statistics and Probability
  • Statistics, Probability and Uncertainty

Cite this

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Continuous-time modelling of irregularly spaced panel data using a cubic spline model. / Chow, Sy Miin; Zhang, Guangjian.

In: Statistica Neerlandica, Vol. 62, No. 1, 01.02.2008, p. 131-154.

Research output: Contribution to journalArticle

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