Curran Patrick J, Obeidat Khawla, Losardo Diane
University of North Carolina at Chapel Hill.
J Cogn Dev. 2010;11(2):121-136. doi: 10.1080/15248371003699969.
Longitudinal data analysis has long played a significant role in empirical research within the developmental sciences. The past decade has given rise to a host of new and exciting analytic methods for studying between-person differences in within-person change. These methods are broadly organized under the term growth curve models. The historical lines of development leading to current growth models span multiple disciplines within both the social and statistical sciences, and this in turn makes it challenging for developmental researchers to gain a broader understanding of the current state of this literature. To help address this challenge, the authors pose 12 questions that frequently arise in growth curve modeling, particularly in applications within developmental psychology. They provide concise and nontechnical responses to each question and make specific recommendations for further readings.
纵向数据分析长期以来在发展科学的实证研究中发挥着重要作用。在过去十年中,涌现出了许多新颖且令人兴奋的分析方法,用于研究个体内部变化中的个体间差异。这些方法大致归在增长曲线模型这一术语之下。通向当前增长模型的历史发展脉络跨越了社会科学和统计学中的多个学科,这反过来使得发展研究人员更广泛地理解该文献的当前状态具有挑战性。为了帮助应对这一挑战,作者提出了12个在增长曲线建模中经常出现的问题,特别是在发展心理学中的应用。他们为每个问题提供了简洁且非技术性的回答,并对进一步阅读提出了具体建议。