The Role of Coding Time in Estimating and Interpreting Growth Curve Models

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Citation

Biesanz, Jeremy C.; Deeb-Sossa, Natalia; Papadakis, Alison A.; Bollen, Kenneth A.; & Curran, Patrick J. (2004). The Role of Coding Time in Estimating and Interpreting Growth Curve Models. Psychological Methods, 9(1), 30-52.

Abstract

The coding of time in growth curve models has important implications for the interpretation of the resulting model that are sometimes not transparent. The authors develop a general framework that includes predictors of growth curve components to illustrate how parameter estimates and their standard errors are exactly determined as a function of recoding time in growth curve models. Linear and quadratic
growth model examples are provided, and the interpretation of estimates given a particular coding of time is illustrated. How and why the precision and statistical power of predictors of lower order growth curve components changes over time is illustrated and discussed. Recommendations include coding time to produce readily interpretable estimates and graphing lower order effects across time with appropriate confidence intervals to help illustrate and understand the growth process.

URL

http://dx.doi.org/10.1037/1082-989X.9.1.30

Reference Type

Journal Article

Year Published

2004

Journal Title

Psychological Methods

Author(s)

Biesanz, Jeremy C.
Deeb-Sossa, Natalia
Papadakis, Alison A.
Bollen, Kenneth A.
Curran, Patrick J.

ORCiD

Bollen - 0000-0002-6710-3800