|
Activity Number:
|
369
|
|
Type:
|
Contributed
|
|
Date/Time:
|
Wednesday, August 6, 2008 : 8:30 AM to 10:20 AM
|
|
Sponsor:
|
Section on Statistical Computing
|
| Abstract - #300534 |
|
Title:
|
Asymptotic Expansions in Mean and Covariance Structure Analysis
|
|
Author(s):
|
Haruhiko Ogasawara*+
|
|
Companies:
|
Otaru University of Commerce
|
|
Address:
|
3-5-21 Midori, Otaru, International, 047-8501, Japan
|
|
Keywords:
|
mean and covariance structure ; factor means ; Edgeworth expansion ; Cornish-Fisher expansion ; bias ; skewness and kurtosis
|
|
Abstract:
|
Asymptotic expansions of the distributions of parameter estimators in mean and covariance structures are derived. The parameters may be common to or specific in means and covariances of observable variables. The means are possibly structured by the common/specific parameters. First, the distributions of the parameter estimators standardized by the population asymptotic standard errors are expanded using the single- and the two-term Edgeworth expansions. In practice, the pivotal statistic or the Studentized estimator with the asymptotically distribution free standard error is of interest. An asymptotic distribution of the pivotal statistic is also derived by the Cornish-Fisher expansion. Simulations are performed for a factor analysis model with nonzero factor means to see the accuracy of the asymptotic expansions in finite samples.
|
