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Investigating impacts of complex sampling on latent growth curve modelling

Investigating impacts of complex sampling on latent growth curve modelling
Investigating impacts of complex sampling on latent growth curve modelling
We investigate the impacts of complex sampling on point and standard error estimates in latent growth curve modelling of survey data. Methodological issues are illustrated with empirical evidence from the analysis of longitudinal data on life satisfaction trajectories using data from the British Household Panel Survey, a national representative survey in Great Britain. A multi-process second-order latent growth curve model with conditional linear growth is used to study variation in the two perceived life satisfaction latent factors considered. The benefits of accounting for the complex survey design are considered, including obtaining unbiased both point and standard error estimates, and therefore correctly specified confidence intervals and statistical tests. We conclude that, even for the rather elaborated longitudinal data models that were considered, estimation procedures are affected by variance-inflating impacts of complex sampling.
complex sampling, latent growth curve models, longitudinal data, misspecification effects, BHPS, AMS (62P25), JEL (C33)
0266-4763
1-12
Vieira, Marcel de Toledo
d78eb443-9a6e-400d-a534-5e9a6c56ddf0
Salgueiro, Maria de Fátima
b6ea9210-a0a1-4507-ab7a-f2f64f62c9a4
Smith, Peter W. F.
961a01a3-bf4c-43ca-9599-5be4fd5d3940
Vieira, Marcel de Toledo
d78eb443-9a6e-400d-a534-5e9a6c56ddf0
Salgueiro, Maria de Fátima
b6ea9210-a0a1-4507-ab7a-f2f64f62c9a4
Smith, Peter W. F.
961a01a3-bf4c-43ca-9599-5be4fd5d3940

Vieira, Marcel de Toledo, Salgueiro, Maria de Fátima and Smith, Peter W. F. (2015) Investigating impacts of complex sampling on latent growth curve modelling. Journal of Applied Statistics, 1-12. (doi:10.1080/02664763.2015.1100590).

Record type: Article

Abstract

We investigate the impacts of complex sampling on point and standard error estimates in latent growth curve modelling of survey data. Methodological issues are illustrated with empirical evidence from the analysis of longitudinal data on life satisfaction trajectories using data from the British Household Panel Survey, a national representative survey in Great Britain. A multi-process second-order latent growth curve model with conditional linear growth is used to study variation in the two perceived life satisfaction latent factors considered. The benefits of accounting for the complex survey design are considered, including obtaining unbiased both point and standard error estimates, and therefore correctly specified confidence intervals and statistical tests. We conclude that, even for the rather elaborated longitudinal data models that were considered, estimation procedures are affected by variance-inflating impacts of complex sampling.

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More information

Accepted/In Press date: 23 September 2015
e-pub ahead of print date: 26 October 2015
Keywords: complex sampling, latent growth curve models, longitudinal data, misspecification effects, BHPS, AMS (62P25), JEL (C33)
Organisations: Statistical Sciences Research Institute

Identifiers

Local EPrints ID: 385210
URI: http://eprints.soton.ac.uk/id/eprint/385210
ISSN: 0266-4763
PURE UUID: 9713e73f-56d8-4373-bfc4-979702b72a3c
ORCID for Peter W. F. Smith: ORCID iD orcid.org/0000-0003-4423-5410

Catalogue record

Date deposited: 18 Jan 2016 11:49
Last modified: 15 Mar 2024 02:43

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Contributors

Author: Marcel de Toledo Vieira
Author: Maria de Fátima Salgueiro

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