论文信息 - Multilevel modeling: When and why

Multilevel modeling: When and why

Multilevel models have become popular for the analysis of a variety of problems. This chapter gives a summary of the reasons for using multilevel models, and provides examples why these reasons are indeed valid. Next, recent (simulation) research is reviewed on the robustness and power of the usual estimation procedures with varying sample sizes.

Joop J. Hox | J. Hox

[1] Chris Warhurst,et al. High Society in a Workers' Society: Work, Community and Kibbutz , 1996 .

[2] Noreen Goldman,et al. An assessment of estimation procedures for multilevel models with binary responses , 1995 .

[3] Harvey Goldstein,et al. Improved Approximations for Multilevel Models with Binary Responses , 1996 .

[4] A. Wald. Tests of statistical hypotheses concerning several parameters when the number of observations is large , 1943 .

[5] Richard L. Tate,et al. Random Versus Nonrandom Coefficient Models for Multilevel Analysis , 1983 .

[6] Roel Bosker,et al. Modeled Variance in Two-Level Models , 1994 .

[7] Robert S. Barcikowski,et al. Statistical Power with Group Mean as the Unit of Analysis , 1981 .

[8] P. van den Eeden,et al. A Short History of Multi-Level Research , 1982 .

[9] Anthony S. Bryk,et al. A Hierarchical Model for Studying School Effects , 1986 .

[10] Randall Peter Fotiu. A comparison of the em and data augmentation algorithms on simulated small-sample hierarchical data from research on education , 1989 .

[11] Jan de Leeuw,et al. Random Coefficient Models for Multilevel Analysis , 1986 .