Name
Title | ||
|---|---|---|
Comparison of two methods in estimating standard error of the method of simulated moments estimators for generalized linear mixed models. |
Abstract | ||
|---|---|---|
The likelihood of a generalized linear mixed model (GLMM) often involves high-dimensional integrals, which in general cannot be computed explicitly. When direct computation is not available, method of simulated moments (MSM) is a fairly simple way to estimate the parameters of interest. In this research, we compared parametric bootstrap (PB) and nonparametric bootstrap methods (NPB) in estimating the standard errors of MSM estimators for GLMM. Simulation results show that when the group size is large, the PB and NPB perform similarly; when group size is medium, NPB performs better than PB in estimating standard errors of the mean. |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1080/03610918.2017.1361979 | COMMUNICATIONS IN STATISTICS-SIMULATION AND COMPUTATION |
Keywords | Field | DocType |
Generalized linear mixed model,Method of simulated moments,Non-parametric bootstrap,Parametric bootstrap,Simulations,Standard errors | Econometrics,Parametric statistics,Method of simulated moments,Statistics,Generalized linear mixed model,Nonparametric bootstrap,Standard error,Bootstrapping (electronics),Mathematics,Computation,Estimator | Journal |
Volume | Issue | ISSN |
47.0 | 10.0 | 0361-0918 |
Citations | PageRank | References |
0 | 0.34 | 2 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Yan Lu | 1 | 865 | 86.69 |
| Zhongxue Chen | 2 | 244 | 15.77 |
| Danielle Durán | 3 | 0 | 0.34 |