构建标准化参考分数的方法:评估24个月大儿童发育的应用。

IF 5.3 3区 心理学 Q1 MATHEMATICS, INTERDISCIPLINARY APPLICATIONS
Multivariate Behavioral Research Pub Date : 2023-09-01 Epub Date: 2022-12-06 DOI:10.1080/00273171.2022.2142189
Vasiliki Bountziouka, Samantha Johnson, Bradley N Manktelow
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引用次数: 0

摘要

λ-μ-西格玛(LMS)方法用于估计百分位数和产生参考范围在临床实践中引起了很大的兴趣,尤其是在评估儿童生长方面。然而,这种方法可能不直接适用于基于从有限区间内的问题-回答类别计算的分数的测量,例如,在心理测量学中。在这种情况下,由于存在天花板(和地板)效应,违反了转换响应测量的条件分布正态性的主要假设,导致在使用常见LMS方法推导时出现偏差拟合的百分位数。本文描述了当反应变量有界时构建参考区间的方法,并使用父母在24岁时完成的认知和语言发展评估得出的分数,探索了用于百分位数估计的不同分布族 一个月大的孩子。结果表明,当峰度也被建模时,z分数以及由此提取的百分位数都得到了改善,并且通过使用膨胀的二项式分布来解决天花板效应。因此,在构造百分位数曲线时,选择合适的分布是至关重要的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Methods for Constructing Normalised Reference Scores: An Application for Assessing Child Development at 24 Months of Age.

The use of the lambda-mu-sigma (LMS) method for estimating centiles and producing reference ranges has received much interest in clinical practice, especially for assessing growth in childhood. However, this method may not be directly applicable where measures are based on a score calculated from question response categories that is bounded within finite intervals, for example, in psychometrics. In such cases, the main assumption of normality of the conditional distribution of the transformed response measurement is violated due to the presence of ceiling (and floor) effects, leading to biased fitted centiles when derived using the common LMS method. This paper describes the methodology for constructing reference intervals when the response variable is bounded and explores different distribution families for the centile estimation, using a score derived from a parent-completed assessment of cognitive and language development in 24 month-old children. Results indicated that the z-scores, and thus the extracted centiles, improved when kurtosis was also modeled and that the ceiling effect was addressed with the use of the inflated binomial distribution. Therefore, the selection of the appropriate distribution when constructing centile curves is crucial.

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来源期刊
Multivariate Behavioral Research
Multivariate Behavioral Research 数学-数学跨学科应用
CiteScore
7.60
自引率
2.60%
发文量
49
审稿时长
>12 weeks
期刊介绍: Multivariate Behavioral Research (MBR) publishes a variety of substantive, methodological, and theoretical articles in all areas of the social and behavioral sciences. Most MBR articles fall into one of two categories. Substantive articles report on applications of sophisticated multivariate research methods to study topics of substantive interest in personality, health, intelligence, industrial/organizational, and other behavioral science areas. Methodological articles present and/or evaluate new developments in multivariate methods, or address methodological issues in current research. We also encourage submission of integrative articles related to pedagogy involving multivariate research methods, and to historical treatments of interest and relevance to multivariate research methods.
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