title: Longitudinal analysis of the strengths and difficulties questionnaire scores of the Millennium Cohort Study children in England usingM-quantile random-effects regression.
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.
authors.affiliation: University of Southampton UK.
authors.forename: Nikos
authors.initials: N
authors.lastname: Tzavidis
authors.affiliation: Università di Pisa Italy.
authors.forename: Nicola
authors.initials: N
authors.lastname: Salvati
authors.affiliation: Freie Universität Berlin Germany.
authors.forename: Timo
authors.initials: T
authors.lastname: Schmid
authors.affiliation: University College London UK.
authors.forename: Eirini
authors.initials: E
authors.lastname: Flouri
authors.affiliation: University College London UK.
authors.forename: Emily
authors.initials: E
authors.lastname: Midouhas
keywords: Influence function; Multilevel modelling; Quantile regression; Repeated measures; Robust estimation