David Rogosa
Dados Biográficos
| ID | 1660610 |
|---|---|
| NOME | David Rogosa |
| PRENOMES | David |
| SOBRENOME | Rogosa |
| ASSINATURA | ROGOSA D |
| AFILIAÇÕES | Stanford University |
| VERIFICADO | Não |
| TOTAL DE OBRAS | 5 |
| TOTAL DE CITAÇÕES | 122 |
| TOTAL COMO AUTOR | 5 |
| TOTAL COMO EDITOR | 0 |
| PRIMEIRO ANO DE PUBLICAÇÃO | 1980 |
| ANO MAIS RECENTE DE PUBLICAÇÃO | 2015 |
| ÍNDICE H | 3 |
Resampling Methods of Estimation
A growth curve approach to the measurement of change
On the Relationship Between the Johnson-Neyman Region of Significance and Statistical Tests of Parallel Within-Group Regressions
The form of the Johnson-Neyman region of significance is shown to be determined by the statistic for testing the null hypothesis that the population within-group regressions are parallel. Results are obtained for both simultaneous and nonsimultaneous regions of significance
Comparing nonparallel regression lines
Presents a comprehensive strategy for the statistical comparison of within-group regressions that is suitable for both parallel and nonparallel regression lines. New results are obtained from 2 groups of Ss, and new interpretations are formulated for standard statistical procedures such as analysis
A critique of cross-lagged correlation
Comments that cross-lagged correlation (CLC) is not a useful procedure for the analysis of longitudinal panel data. In particular, the difference between CLCs is not a sound basis for causal inference. Demonstrations of the failure of CLC are based mainly on results for the 2-wave, 2-variable longit
A growth curve approach to the measurement of change
A critique of cross-lagged correlation
Comments that cross-lagged correlation (CLC) is not a useful procedure for the analysis of longitudinal panel data. In particular, the difference between CLCs is not a sound basis for causal inference. Demonstrations of the failure of CLC are based mainly on results for the 2-wave, 2-variable longit
Comparing nonparallel regression lines
Presents a comprehensive strategy for the statistical comparison of within-group regressions that is suitable for both parallel and nonparallel regression lines. New results are obtained from 2 groups of Ss, and new interpretations are formulated for standard statistical procedures such as analysis
Comparing nonparallel regression lines
Presents a comprehensive strategy for the statistical comparison of within-group regressions that is suitable for both parallel and nonparallel regression lines. New results are obtained from 2 groups of Ss, and new interpretations are formulated for standard statistical procedures such as analysis
A critique of cross-lagged correlation
Comments that cross-lagged correlation (CLC) is not a useful procedure for the analysis of longitudinal panel data. In particular, the difference between CLCs is not a sound basis for causal inference. Demonstrations of the failure of CLC are based mainly on results for the 2-wave, 2-variable longit
On the Relationship Between the Johnson-Neyman Region of Significance and Statistical Tests of Parallel Within-Group Regressions
The form of the Johnson-Neyman region of significance is shown to be determined by the statistic for testing the null hypothesis that the population within-group regressions are parallel. Results are obtained for both simultaneous and nonsimultaneous regions of significance
A growth curve approach to the measurement of change
Resampling Methods of Estimation
Mathematics (5 obras) · Statistics (5 obras) · Econometrics (4 obras) · Psychology (4 obras) · Statistical hypothesis testing (2 obras) · Advanced Statistical Methods and Models (1 obras) · Algorithm (1 obras) · Alternative hypothesis (1 obras) · Bayesian Methods and Mixture Models (1 obras) · Behavioral and Psychological Studies (1 obras)