1 |
Murad, H., Fleischman, A., Sadetzki, S., Geyer, O., and Freedman, L. S.(2003). Small Samples and Ordered Logistic Regression: Does it Help to Collapse Categories of Outcome?' The American Statistician. 57, 3, 155-160
DOI
ScienceOn
|
2 |
Velicer, W. F.(1978). Suppressor Variables and the Sernipartial Correlation Coefficient. Educational and Psychological Measurement, 38: 953-958
DOI
|
3 |
Nagelkerke, N. J. D.(1991). A Note on a General Definition of the Coefficient of Determination. Biometrika. 78: 691-692
DOI
ScienceOn
|
4 |
Mittlebock, M. and Schemper, M.(1996). Explained Variation for Logistic Regression, Statistics in Medicine, 15, 1987-1997
DOI
ScienceOn
|
5 |
Schey, H. M.(1993). The Relationship Between the Magnitudes of SSR() and SSR(): A Geometric Description, The American Statistician, 47, 26-30
DOI
ScienceOn
|
6 |
Cox, D. R and Snell, E. J.(1989). Analysis of Binary Data, Chapman and Hall
|
7 |
Sharpe, N. R., and Roberts, R. A.(1997). The Relationship Among Sums of Squares, Correlation Coefficients, and Suppression, The American Statistician, 51, 46-48
DOI
ScienceOn
|
8 |
Walker. S. H. and Duncan, D. B.(1967). Estimation of the Probability of an Event as a Function of Several Independent Variables. Biometrika. 54, 167-179
DOI
|
9 |
Cohen, J. and Cohen, P.(1975). Applied Multiple Regression/Correlation Analysis for the Behavioral Sciences, New Jersey: Lawrence Erlbaum Associates
|
10 |
Conger, A. J.(1975). A Revised Definition for Suppressor Variables: A Guide to Their Identification and Interpretation, Educational and Psychological Measurement, 34, 35-46
DOI
|
11 |
Hamilton, D.(1987). Sometimes $R^2\;>\;r^2_{yx_1}+R^2_{yx_2}$ Correlated Variables are not Always Redundant, The American Statistician, 41, 129-132
DOI
ScienceOn
|
12 |
Horst, P.(1941). The Role of Prediction Variables Which are Independent of the Criterion, in The Prediction Adjustment, ed. P. Horst, New York: Social Science Research Council
|
13 |
Hong, C. S.(2004). Suppression and Collapsibility for Log-linear Model, The Korean Communication in Statistics, 11, 3, 519-527
DOI
ScienceOn
|
14 |
Lynn, H. S.(2003). Suppression and Confounding in Action, The American Statistician, 57, 58-61
DOI
ScienceOn
|
15 |
McCullagh, P.(1980), Regression Models for Ordinal Data (with discussion), Journal of Royal Statistical Society, Ser. B, 42, 109-142
|
16 |
Menard, S.(2000). Coefficients of Determination for Multiple Logistic Regression Analysis, The American Statistician, 54, 17-24
DOI
ScienceOn
|