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Modelling neuromotor ratings with floor-effects


Gasser, T; Rousson, V (2004). Modelling neuromotor ratings with floor-effects. Statistics in Medicine, 23(23):3641-3653.

Abstract

Associated movements (AMs) are a classical diagnostic tool to assess differences between normal children and children with some motor dysfunction. This paper presents a methodology to produce age- and gender-dependent reference-curves for AMs of normal children, for various tasks of a test battery. Data available consist of separate ratings of duration and extent of AMs, which are ordinal quantities with few levels. Other problems are severe age- and gender-dependent floor-effects (as well as some ceiling-effects), leaving little information for analysis at older ages. To get a better scale, we combined the two ordinal ratings into one meaningful and quasi-continuous quantity referred to as intensity of AMs. In order to solve problems due to floor-effects, ceiling-effects and discreteness, we assumed left- , right- and interval-censored values, respectively. We considered a censored regression problem and postulated a truncated normal distribution for the non-censored values (after an appropriate transformation of the data). Using Wei and Tanner's poor man's data augmentation algorithm, together with the technique of linear mixed effects modelling, useful reference-curves could be produced. In contrast to the cumulative probabilities approach for ordinal data, our methodology allows the calculation of individual age- and gender-standardized values, which puts us in a position to investigate numerous scientific questions.

Abstract

Associated movements (AMs) are a classical diagnostic tool to assess differences between normal children and children with some motor dysfunction. This paper presents a methodology to produce age- and gender-dependent reference-curves for AMs of normal children, for various tasks of a test battery. Data available consist of separate ratings of duration and extent of AMs, which are ordinal quantities with few levels. Other problems are severe age- and gender-dependent floor-effects (as well as some ceiling-effects), leaving little information for analysis at older ages. To get a better scale, we combined the two ordinal ratings into one meaningful and quasi-continuous quantity referred to as intensity of AMs. In order to solve problems due to floor-effects, ceiling-effects and discreteness, we assumed left- , right- and interval-censored values, respectively. We considered a censored regression problem and postulated a truncated normal distribution for the non-censored values (after an appropriate transformation of the data). Using Wei and Tanner's poor man's data augmentation algorithm, together with the technique of linear mixed effects modelling, useful reference-curves could be produced. In contrast to the cumulative probabilities approach for ordinal data, our methodology allows the calculation of individual age- and gender-standardized values, which puts us in a position to investigate numerous scientific questions.

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9 citations in Web of Science®
7 citations in Scopus®
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Additional indexing

Item Type:Journal Article, refereed, original work
Communities & Collections:04 Faculty of Medicine > Epidemiology, Biostatistics and Prevention Institute (EBPI)
Dewey Decimal Classification:610 Medicine & health
Language:English
Date:2004
Deposited On:17 Jun 2009 15:35
Last Modified:06 Dec 2017 20:02
Publisher:Wiley-Blackwell
ISSN:0277-6715
Publisher DOI:https://doi.org/10.1002/sim.1914
PubMed ID:15534892

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