Currently submitted to: JMIR Pediatrics and Parenting
Date Submitted: Aug 26, 2026
Open Peer Review Period: Aug 28, 2026 - Oct 23, 2026
(currently open for review)
Warning: This is an author submission that is not peer-reviewed or edited. Preprints - unless they show as "accepted" - should not be relied on to guide clinical practice or health-related behavior and should not be reported in news media as established information.
Multivariate Growth Assessment in Infants Aged 0–24 Months Using RaschKIDMAP: Development and Application
ABSTRACT
Background:
Infant growth is commonly assessed using separate percentile charts for height, weight, and head circumference. An integrated multidimensional approach may provide complementary information.
Objective:
To describe RaschKIDMAP, a lightweight web application that applies Rasch measurement to multidimensional growth assessment in infants aged 0–24 months.
Methods:
RaschKIDMAP integrates height, weight, and head-circumference measurements with sex- and age-matched reference data. For each assessment, the application identifies 50 reference infants matched by sex and month of age, then appends the assessed infant as a 51st record. Measurements are transformed within the matched group and analyzed using a probability-based continuous-response Rasch model, with optional TAM rating-scale and partial-credit models. Outputs include person measures, item difficulties, standard errors, fit statistics, residual Z-scores, and empirical percentiles.
Results:
The application generates an accessible visual report comprising individual and group forest plots, a KIDMAP item-residual display, a Wright map, original comparison data, person and item tables, and conventional percentile plots. It accepts routine anthropometric inputs and returns results immediately without a database backend.
Conclusions:
RaschKIDMAP is a proof-of-concept tool designed to complement conventional single-indicator growth percentiles with an integrated Rasch-based representation of infant growth. Further empirical validation is required before clinical implementation.
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