Linear mixed models for longitudinal shape data with applications to facial modelling

Sarah J. E. Barry, Adrian W. Bowman

Research output: Contribution to journalArticle

19 Citations (Scopus)

Abstract

We present a novel application of methods for analysis of high-dimensional longitudinal data to a comparison of facial shape over time between babies with cleft lip and palate and similarly aged controls. A pairwise methodology is used that was introduced in Fieuws and Verbeke (2006) in order to apply a linear mixed-effects model to data of high dimensions, such as describe facial shape. The approach involves fitting bivariate linear mixed-effects models to all the pairwise combinations of responses, where the latter result from the individual coordinate positions, and aggregating the results across repeated parameter estimates (such as the random-effects variance for a particular coordinate). We describe one example using landmarks and another using facial curves from the cleft lip study, the latter using B-splines to provide an efficient parameterization. The results are presented in 2 dimensions, both in the profile and in the frontal views, with bivariate confidence intervals for the mean position of each landmark or curve, allowing objective assessment of significant differences in particular areas of the face between the 2 groups. Model comparison is performed using Wald and pseudolikelihood ratio tests.
LanguageEnglish
Pages555-565
Number of pages11
JournalBiostatistics
Volume9
Issue number3
Early online date5 Feb 2008
DOIs
Publication statusPublished - 1 Jul 2008

Fingerprint

Linear Mixed Model
Linear Mixed Effects Model
Landmarks
Pairwise
Modeling
Ratio test
Pseudo-likelihood
Curve
Model Comparison
Longitudinal Data
High-dimensional Data
B-spline
Random Effects
Parameterization
Higher Dimensions
Confidence interval
Face
Methodology
Estimate
Mixed model

Keywords

  • Curves, Mixed models, Multivariate longitudinal profiles, Pairwise modelling, Shape analysis
  • cleft palate
  • cleft lip

Cite this

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title = "Linear mixed models for longitudinal shape data with applications to facial modelling",
abstract = "We present a novel application of methods for analysis of high-dimensional longitudinal data to a comparison of facial shape over time between babies with cleft lip and palate and similarly aged controls. A pairwise methodology is used that was introduced in Fieuws and Verbeke (2006) in order to apply a linear mixed-effects model to data of high dimensions, such as describe facial shape. The approach involves fitting bivariate linear mixed-effects models to all the pairwise combinations of responses, where the latter result from the individual coordinate positions, and aggregating the results across repeated parameter estimates (such as the random-effects variance for a particular coordinate). We describe one example using landmarks and another using facial curves from the cleft lip study, the latter using B-splines to provide an efficient parameterization. The results are presented in 2 dimensions, both in the profile and in the frontal views, with bivariate confidence intervals for the mean position of each landmark or curve, allowing objective assessment of significant differences in particular areas of the face between the 2 groups. Model comparison is performed using Wald and pseudolikelihood ratio tests.",
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Linear mixed models for longitudinal shape data with applications to facial modelling. / Barry, Sarah J. E.; Bowman, Adrian W.

In: Biostatistics, Vol. 9, No. 3, 01.07.2008, p. 555-565.

Research output: Contribution to journalArticle

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AB - We present a novel application of methods for analysis of high-dimensional longitudinal data to a comparison of facial shape over time between babies with cleft lip and palate and similarly aged controls. A pairwise methodology is used that was introduced in Fieuws and Verbeke (2006) in order to apply a linear mixed-effects model to data of high dimensions, such as describe facial shape. The approach involves fitting bivariate linear mixed-effects models to all the pairwise combinations of responses, where the latter result from the individual coordinate positions, and aggregating the results across repeated parameter estimates (such as the random-effects variance for a particular coordinate). We describe one example using landmarks and another using facial curves from the cleft lip study, the latter using B-splines to provide an efficient parameterization. The results are presented in 2 dimensions, both in the profile and in the frontal views, with bivariate confidence intervals for the mean position of each landmark or curve, allowing objective assessment of significant differences in particular areas of the face between the 2 groups. Model comparison is performed using Wald and pseudolikelihood ratio tests.

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