Evidence map›Paper›PMID 41310173›Full record

ArticleScientific reports2025

Comparison of cNORM and LMS methods for estimating reference percentile curves from biometric data.

Ronja Laurenz, Wolfgang Lenhard

Abstract readComparative Study
In one paragraph

Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
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1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

Ronja LaurenzInstitute of Psychology, Ruprecht-Karls-University, Heidelberg, Germany.
Wolfgang LenhardInstitute of Psychology, Julius-Maximilians-University, Würzburg, Germany. wolfgang.lenhard@uni-wuerzburg.de.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Accurate reference curves for biometric measures are essential for population health monitoring and screening. The Lambda Mu Sigma Method (LMS), introduced by Cole and Green, is widely used in public health for generating age-specific reference percentiles. This study compares LMS with cNORM, a distribution-free approach based on Taylor polynomials, previously validated in psychometric applications. Using publicly accessible National Health and Nutrition Examination Survey (NHANES) datasets, we compared the performance of LMS and cNORM in modelling reference curves for body mass index (BMI) and maximum oxygen consumption (VO

Indexed as

BiometryAdultBody Mass IndexFemaleHumansMaleMiddle AgedNutrition SurveysOxygen ConsumptionReference ValuesContinuous normingData normalizationLambda Mu Sigma methodReference percentile curvesTaylor polynomial

Identifiers

PMID41310173
PMCPMC12663128

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.