一大块 发表于 2025-3-26 21:01:55
Latent Variable Modeling and Applications to Causality978-1-4612-1842-5Series ISSN 0930-0325 Series E-ISSN 2197-7186Pathogen 发表于 2025-3-27 04:40:52
http://reply.papertrans.cn/59/5819/581808/581808_32.pngConspiracy 发表于 2025-3-27 07:55:52
Models as Instruments, With Applications to Moment Structure Analysis,n a simple geometrical argument, and on expansions of the loss functions around the estimate, the target, and the replication. We give both delta-method and Jackknife computational procedures to estimate the relevant quantities.Gorilla 发表于 2025-3-27 11:39:23
http://reply.papertrans.cn/59/5819/581808/581808_34.png伤心 发表于 2025-3-27 17:35:29
http://reply.papertrans.cn/59/5819/581808/581808_35.pngcogent 发表于 2025-3-27 18:29:48
Measurement, Causation and Local Independence in Latent Variable Models,xplanation. The latent variables may be continuous or discrete and the indicators of these may be continuous and/or discrete as well. Crossing the levels of measurement of the indicators with the assumptions on the level of measurement and distribution of the latent variables yields a variety of dismoratorium 发表于 2025-3-27 23:37:25
On the Identification of Nonparametric Structural Models,lity distributions of the disturbances remain unspecified. Identifiability in such models does not mean uniqueness of structural parameters but rather uniqueness of policy-related predictions that such parameters would normally support..We provide sufficient and necessary conditions for identifying芦笋 发表于 2025-3-28 03:26:50
http://reply.papertrans.cn/59/5819/581808/581808_38.pngLIEN 发表于 2025-3-28 08:58:07
http://reply.papertrans.cn/59/5819/581808/581808_39.png披肩 发表于 2025-3-28 13:09:29
Latent Variable Growth Modeling with Multilevel Data, software. Latent variable modeling of growth considers a vector of observations over time for an individual, reducing the two-level problem to a one-level problem Analogous to this, three-level data on students, time points, and schools can be modeled by a two-level growth model. An interesting fea