Test for a general trilinear hypothesis in the generalized growth curve model

Justine Dushimirimana, Isaac Kipchirchir Chumba, Lydia Musiga, Joseph Nzabanita and Ronald Waliaula Wanyonyi

Journal of Multivariate Analysis, 2025, vol. 210, issue C

Abstract: In this paper, we consider the problem of testing a general trilinear hypothesis in the generalized growth curve model. The general trilinear hypothesis was formulated to test for example the significance of the generalized growth curves or the equality of the trilinear mean between groups in the two dimensions. The null hypothesis considered is of the form ℬ×{L,M,N}=O, where L,M and N are known matrices, ℬ is unknown parameter tensor and O is a tensor of zeros. The estimators of the parameters were obtained using a flip-flop algorithm under the null and alternative hypotheses. The likelihood ratio test for testing the general trilinear hypothesis was discussed. The proposed test is an extension of the likelihood ratio test for the general linear hypothesis under the growth curve model. A simulation study was performed to evaluate the performance of the proposed test and a real dataset was used for an illustrative example.

Keywords: Asymptotic distribution; Generalized growth curve model; General trilinear hypothesis; Likelihood ratio test (search for similar items in EconPapers)
Date: 2025
References: Add references at CitEc
Citations:

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0047259X2500065X
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:jmvana:v:210:y:2025:i:c:s0047259x2500065x

Ordering information: This journal article can be ordered from
http://www.elsevier.com/wps/find/supportfaq.cws_home/regional
https://shop.elsevie ... _01_ooc_1&version=01

DOI: 10.1016/j.jmva.2025.105470

Access Statistics for this article

Journal of Multivariate Analysis is currently edited by de Leeuw, J.

More articles in Journal of Multivariate Analysis from Elsevier
Bibliographic data for series maintained by Catherine Liu ().