Yutaka Kano
Biographic Data
| ID | 5091551 |
|---|---|
| NAME | Yutaka Kano |
| GIVEN NAMES | Yutaka |
| FAMILY NAME | Kano |
| SIGNATURE | KANO Y |
| ORCID | 0000-0003-0913-9714 |
| VERIFIED | Yes |
| TOTAL WORKS | 3 |
| TOTAL CITATIONS | 60 |
| WORKS AS AUTHOR | 3 |
| WORKS AS EDITOR | 0 |
| FIRST PUBLICATION YEAR | 1990 |
| LATEST PUBLICATION YEAR | 2013 |
| H-INDEX | 1 |
New Developments in Psychometrics
Can test statistics in covariance structure analysis be trusted
Covariance structure analysis uses chi 2 goodness-of-fit test statistics whose adequacy is not known. Scientific conclusions based on models may be distorted when researchers violate sample size, variate independence, and distributional assumptions. The behavior of 6 test statistics is evaluated with a Monte Carlo confirmatory factor analysis study. The tests performed dramatically differently under 7 distributional conditions at 6 sample sizes. …
On the Equivalence of Factors and Components
(1990). On the Equivalence of Factors and Components. Multivariate Behavioral Research: Vol. 25, No. 1, pp. 67-74
Can test statistics in covariance structure analysis be trusted
Covariance structure analysis uses chi 2 goodness-of-fit test statistics whose adequacy is not known. Scientific conclusions based on models may be distorted when researchers violate sample size, variate independence, and distributional assumptions. The behavior of 6 test statistics is evaluated with a Monte Carlo confirmatory factor analysis study. The tests performed dramatically differently under 7 distributional conditions at 6 sample sizes. …
On the Equivalence of Factors and Components
(1990). On the Equivalence of Factors and Components. Multivariate Behavioral Research: Vol. 25, No. 1, pp. 67-74
Can test statistics in covariance structure analysis be trusted
Covariance structure analysis uses chi 2 goodness-of-fit test statistics whose adequacy is not known. Scientific conclusions based on models may be distorted when researchers violate sample size, variate independence, and distributional assumptions. The behavior of 6 test statistics is evaluated with a Monte Carlo confirmatory factor analysis study. The tests performed dramatically differently under 7 distributional conditions at 6 sample sizes. …
New Developments in Psychometrics
Advanced Statistical Modeling Techniques (2 works) · Econometrics (2 works) · Mathematics (2 works) · Psychology (2 works) · Statistics (2 works) · Advanced Statistical Methods and Models (1 work) · Analysis of covariance (1 work) · Behavioral and Psychological Studies (1 work) · Computer Science (1 work) · Confirmatory factor analysis (1 work)