The role of coding time in estimating and interpreting growth curve models
The role of coding time in estimating and interpreting growth curve models
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DOI：
10.1037/1082-989x.9.1.30
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发表时间：
2004-03-01
影响因子：
7
通讯作者：
Curran, PJ
中科院分区：
文献类型：
--
作者：
Biesanz, JC;Deeb-Sossa, N;Curran, PJ
增长曲线模型中的时间编码对于解释有时不透明的模型具有重要意义。作者开发了一个一般框架，其中包括预测的增长曲线组件，以说明如何参数估计和他们的标准误差，准确地确定为一个函数的重新编码时间的增长曲线模型。线性和二次增长模型的例子，并说明了一个特定的时间编码的估计的解释。如何以及为什么低阶增长曲线组件的预测精度和统计能力随时间变化的说明和讨论。建议包括编码时间以产生易于解释的估计值，并用适当的置信区间绘制时间上的低阶效应，以帮助说明和理解增长过程。
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.