Latent growth factors as predictors of distal outcomes.

IF 7.6 1区 心理学 Q1 PSYCHOLOGY, MULTIDISCIPLINARY
Ethan M McCormick, Patrick J Curran, Gregory R Hancock
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引用次数: 0

Abstract

A currently overlooked application of the latent curve model (LCM) is its use in assessing the consequences of development patterns of change-that is as a predictor of distal outcomes. However, there are additional complications for appropriately specifying and interpreting the distal outcome LCM. Here, we develop a general framework for understanding the sensitivity of the distal outcome LCM to the choice of time coding, focusing on the regressions of the distal outcome on the latent growth factors. Using artificial and real-data examples, we highlight the unexpected changes in the regression of the slope factor which stand in contrast to prior work on time coding effects, and develop a framework for estimating the distal outcome LCM at a point in the trajectory-known as the aperture-which maximizes the interpretability of the effects. We also outline a prioritization approach developed for assessing incremental validity to obtain consistently interpretable estimates of the effect of the slope. Throughout, we emphasize practical steps for understanding these changing predictive effects, including graphical approaches for assessing regions of significance similar to those used to probe interaction effects. We conclude by providing recommendations for applied research using these models and outline an agenda for future work in this area. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

作为远端结果预测因素的潜伏生长因子。
潜曲线模型(LCM)目前被忽视的一个应用是其在评估发展变化模式的后果方面的用途,即作为远端结果的预测指标。然而,在适当指定和解释远端结果 LCM 时还会遇到更多的复杂问题。在此,我们建立了一个总体框架,用于理解远端结果 LCM 对时间编码选择的敏感性,重点关注远端结果对潜在增长因素的回归。利用人工和真实数据示例,我们强调了斜率因子回归中的意外变化,这与之前关于时间编码效应的研究形成了鲜明对比,我们还开发了一个框架,用于在轨迹中的某一点估计远端结果 LCM(称为孔径),从而最大限度地提高效应的可解释性。我们还概述了为评估增量有效性而开发的优先排序方法,以获得可持续解释的斜率效应估计值。在整个过程中,我们强调了理解这些不断变化的预测效应的实用步骤,包括评估显著性区域的图形方法,类似于用于探究交互效应的方法。最后,我们为使用这些模型的应用研究提出了建议,并概述了该领域未来的工作议程。(PsycInfo Database Record (c) 2024 APA,保留所有权利)。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Psychological methods
Psychological methods PSYCHOLOGY, MULTIDISCIPLINARY-
CiteScore
13.10
自引率
7.10%
发文量
159
期刊介绍: Psychological Methods is devoted to the development and dissemination of methods for collecting, analyzing, understanding, and interpreting psychological data. Its purpose is the dissemination of innovations in research design, measurement, methodology, and quantitative and qualitative analysis to the psychological community; its further purpose is to promote effective communication about related substantive and methodological issues. The audience is expected to be diverse and to include those who develop new procedures, those who are responsible for undergraduate and graduate training in design, measurement, and statistics, as well as those who employ those procedures in research.
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