排序方式： 共有5条查询结果，搜索用时 15 毫秒
1
1.
Dr. Eva-Marie Kessler Prof. Dr. Ulman Lindenberger Prof. Dr. Ursula M. Staudinger 《Zeitschrift für Erziehungswissenschaft》2009,12(3):361-381
In this review article, “aging and learning” is discussed from the perspective of life span developmental psychology. Accordingly, aging is regarded as a continuous and multidimensional process which is characterized by a potential for change (plasticity) at all ages. We give an overview of age-related changes in two psychological domains which are considered to be highly relevant for learning processes, namely cognitive resources and resources related to personality, motivation and emotion. In addition, we describe developmental contexts which were shown to contribute to plasticity in the second half of life. The findings allow for the conclusion that learning is possible throughout the adult life span, albeit under changing conditions. Key implications for learning processes and learning contexts are discussed. 相似文献
2.
Christopher Hertzog Timo von Oertzen Paolo Ghisletta Ulman Lindenberger 《Structural equation modeling》2013,20(4):541-563
We evaluated the statistical power of single-indicator latent growth curve models to detect individual differences in change (variances of latent slopes) as a function of sample size, number of longitudinal measurement occasions, and growth curve reliability. We recommend the 2 degree-of-freedom generalized test assessing loss of fit when both slope-related random effects, the slope variance and intercept-slope covariance, are fixed to 0. Statistical power to detect individual differences in change is low to moderate unless the residual error variance is low, sample size is large, and there are more than four measurement occasions. The generalized test has greater power than a specific test isolating the hypothesis of zero slope variance, except when the true slope variance is close to 0, and has uniformly superior power to a Wald test based on the estimated slope variance. 相似文献
3.
Donald Kennedy John Perky Carolyn Lougee Marsh McCall Paul Robinson James Gibb Clara N. Bush Judith Brown George Dekker Bill King William Chace Carlos Camargo J. Martin Evans Ronald Rebholz Carl Degler Barbara Gelpi Renato Rosaldo Clara N. Bush William Mahrt Halsey Rayden Herbert Lindenberger Albert Gelpi Gregson Davis Diane Middlebrook David Kennedy Dennis Phillips Harry Papasotiriou Paul Robinson Martin Evans Ron Rebholz George Dekker Bill Chace Van Harvey Jim Sneehan David Riggs Clara N. Bush 《Minerva》1989,27(2-3):223-411
4.
Manuel C. Voelkle Johan H. L. Oud Timo von Oertzen Ulman Lindenberger 《Structural equation modeling》2013,20(3):329-350
This article has 3 objectives that build on each other. First, we demonstrate how to obtain maximum likelihood estimates for dynamic factor models (the direct autoregressive factor score model) with arbitrary T and N by means of structural equation modeling (SEM) and compare the approach to existing methods. Second, we go beyond standard time series analysis (T large and N = 1) and conventional SEM (N large and T = 1 or small) by integrating both approaches. The resulting combined model offers a variety of new modeling options including a direct test of the ergodicity hypothesis, according to which the factorial structure of an individual observed at many time points is identical to the factorial structure of a group of individuals observed at a single point in time. Third, we illustrate the flexibility of SEM time series modeling by extending the approach to account for complex error structures. We end with a discussion of current limitations and future applications of SEM-based time series modeling for arbitrary T and N. 相似文献
5.
1