CANONICAL ANALYSIS FOR INCOMPLETE DATA MATRIX
| Project/Area Number |
15500184
|
|---|
| Research Category |
Grant-in-Aid for Scientific Research (C)
|
| Allocation Type | Single-year Grants |
|---|
| Section | 一般 |
|---|
| Research Field |
Statistical science
|
|---|
| Research Institution | Niigata University |
|---|
Principal Investigator |
SHIBAYAMA Tadashi Niigata University, Faculty of Education and Human Sciences, Associate Professor, 教育人間科学部, 助教授 (70240752)
|
|---|
| Project Period (FY) |
2003 – 2004
|
| Project Status |
Completed (Fiscal Year 2004)
|
| Budget Amount *help |
¥1,800,000 (Direct Cost: ¥1,800,000)
Fiscal Year 2004: ¥600,000 (Direct Cost: ¥600,000)
Fiscal Year 2003: ¥1,200,000 (Direct Cost: ¥1,200,000)
|
|---|
| Keywords | CANONICAL ANALYSIS / ANOVA / MISSING VALUES / INCOMPETE DATA / INDIVIDUAL DIFFERENCES / PCA / 不完全多変量データ / 欠損値 / 合成変量 / 正凖変量 / 大学入試 / 科目選択 |
|---|
| Research Abstract |
Equivalence of two methods for maximizing individual differences with incomplete test scores is formally proved. One method is based on the least squares criterion and can get composite scores in such a way that individual differences become as large as possible allowing for differences between difficulties of tests.
The other method is formulated from the viewpoint of ANOVA model, which is able to be easily extended to multi-component case. The basic result on the equivalence can be used to show the effective algorithm of PGA for incomplete data matrix.
The algorithm is written in S-PLUS.
|
Report
(3 results)
Research Products
(3 results)
