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Publication Details
AFRICAN RESEARCH NEXUS
SHINING A SPOTLIGHT ON AFRICAN RESEARCH
agricultural and biological sciences
Methods for analysis of unbalanced, longitudinal, growth data
American Journal of Primatology, Volume 28, No. 1, Year 1992
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Description
We describe an approach to analysis of growth that does not depend on assumptions about the underlying functional growth pattern and that allows for multiple observations arising from individual‐specific, irregularly spaced data. We produce estimated growth curves for predefined subject groups by using LOWESS, a nonparametric smoothing algorithm. We describe how statistical significance of curve features may be evaluated by using the “jackknife,” a sample re‐use method; this technique can be used to assess differences between subject groups. We then obtain residuals at each data point by reference to the estimated curve. Consistency of residuals is evaluated as a characteristic of individual subjects, and in the presence of individual consistency, relative size‐for‐age is then scored by the average residual for each individual. This allows study of relationships between relative size and other individual characteristics such as birth order, dominance rank, or age of maturation. Finally, we indicate flexibility of these methods and alternatives, propose uses related to other questions about growth, and suggest potential applications to variables other than body size. Appendices demonstrate application of the LOWESS and jackknife algorithms to the problem of testing sex differences in growth. © 1992 Wiley‐Liss, Inc. Copyright © 1992 Wiley‐Liss, Inc., A Wiley Company
Authors & Co-Authors
Moses, Lincoln E.
United States, Palo Alto
Stanford University
United States, Stanford
Center for Advanced Study in the Behavioral Sciences
Gale, Lynn C.
United States, Stanford
Center for Advanced Study in the Behavioral Sciences
Altmann, Jeanne
United States, Chicago
The University of Chicago
United States, Brookfield
Brookfield Zoo
Kenya, Nairobi
National Museums of Kenya
Statistics
Citations: 45
Authors: 3
Affiliations: 5
Identifiers
Doi:
10.1002/ajp.1350280105
ISSN:
02752565
e-ISSN:
10982345
Study Design
Cohort Study