Growth curve (statistics)

Then defines the growth curve model, where A and C are known, B and Σ are unknown, and E is a random matrix distributed as Np,n(0,Ip,n).

[3] Many writers have considered the growth curve analysis, among them Wishart (1938),[4] Box (1950) [5] and Rao (1958).

[6] Potthoff and Roy in 1964;[3] were the first in analyzing longitudinal data applying GMANOVA models.

GMANOVA is frequently used for the analysis of surveys, clinical trials, and agricultural data,[7] as well as more recently in the context of Radar adaptive detection.

[11] When variables are measured with error, a Latent growth modeling SEM can be used.

Table of height and weight for boys over time. The growth curve model (also known as GMANOVA) is used to analyze data such as this, where multiple observations are made on collections of individuals over time.