Longitudinal analysis of the strengths and difficulties questionnaire scores of the Millennium Cohort Study Children in England using M-quantile random-effects regression
Longitudinal analysis of the strengths and difficulties questionnaire scores of the Millennium Cohort Study Children in England using M-quantile random-effects regression
Multilevel modelling is a popular approach for longitudinal data analysis. Statistical models conventionally target a parameter at the centre of a distribution. However, when the distribution of the data is asymmetric, modelling other location parameters, e.g. percentiles, may be more informative. We present a new approach, M-quantile random-effects regression, for modelling multilevel data. The proposed method is used for modelling location parameters of the distribution of the strengths and difficulties questionnaire scores of children in England who participate in the Millennium Cohort Study. Quantile mixed models are also considered. The analyses offer insights to child psychologists about the differential effects of risk factors on children's outcomes.
427-452
Tzavidis, Nikos
431ec55d-c147-466d-9c65-0f377b0c1f6a
Salvati, Nicola
9be298e5-de55-4a24-9361-054a2ec09726
Schmid, Timo
6337d53e-bfc0-4a18-b31c-551d2f859336
Flouri, Eirni
4a237c97-b75a-4854-b262-eb22c33b9d4b
Midouhas, Emily
483c9ab7-80f5-4e57-bf35-75991f73df2d
February 2016
Tzavidis, Nikos
431ec55d-c147-466d-9c65-0f377b0c1f6a
Salvati, Nicola
9be298e5-de55-4a24-9361-054a2ec09726
Schmid, Timo
6337d53e-bfc0-4a18-b31c-551d2f859336
Flouri, Eirni
4a237c97-b75a-4854-b262-eb22c33b9d4b
Midouhas, Emily
483c9ab7-80f5-4e57-bf35-75991f73df2d
Tzavidis, Nikos, Salvati, Nicola, Schmid, Timo, Flouri, Eirni and Midouhas, Emily
(2016)
Longitudinal analysis of the strengths and difficulties questionnaire scores of the Millennium Cohort Study Children in England using M-quantile random-effects regression.
Journal of the Royal Statistical Society: Series A (Statistics in Society), 179 (2), .
(doi:10.1111/rssa.12126).
Abstract
Multilevel modelling is a popular approach for longitudinal data analysis. Statistical models conventionally target a parameter at the centre of a distribution. However, when the distribution of the data is asymmetric, modelling other location parameters, e.g. percentiles, may be more informative. We present a new approach, M-quantile random-effects regression, for modelling multilevel data. The proposed method is used for modelling location parameters of the distribution of the strengths and difficulties questionnaire scores of children in England who participate in the Millennium Cohort Study. Quantile mixed models are also considered. The analyses offer insights to child psychologists about the differential effects of risk factors on children's outcomes.
Text
Tzavidis_et_al-2016-Journal_of_the_Royal_Statistical_Society__Series_A_(Statistics_in_Society).pdf
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Accepted/In Press date: March 2015
e-pub ahead of print date: 1 July 2015
Published date: February 2016
Organisations:
Social Statistics & Demography
Identifiers
Local EPrints ID: 378404
URI: http://eprints.soton.ac.uk/id/eprint/378404
ISSN: 0964-1998
PURE UUID: 141f93f0-4a05-4aed-891f-99c1978ed45c
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Date deposited: 30 Jun 2015 11:13
Last modified: 15 Mar 2024 03:11
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Contributors
Author:
Nicola Salvati
Author:
Timo Schmid
Author:
Eirni Flouri
Author:
Emily Midouhas
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