References - C

A B C D E F G H I J K L M N O P Q R S T U V W Y Z

Campbell D. T., & Fiske, D. W. (1959). Convergent and discriminant validation by the multitrait-multimethod matrix. Psychological Bulletin, 56, 81-105.

Cario, M.C., Nelson, B.L., 1997. Modeling and generating random vectors with arbitrary marginal distributions and correlation matrix. Technical Report, Department of Industrial Engineering and Management Sciences, Northwestern University.

Carling, A. (1992). Introducing Neural Networks. Wilmslow, UK: Sigma Press.

Carmines, E. G., & Zeller, R. A. (1980). Reliability and validity assessment. Beverly Hills, CA: Sage Publications.

Carrol, J. D., Green, P. E., and Schaffer, C. M. (1986). Interpoint distance comparisons in correspondence analysis. Journal of Marketing Research, 23, 271-280.

Carroll, J. D., & Wish, M. (1974). Multidimensional perceptual models and measurement methods. In E. C. Carterette and M. P. Friedman (Eds.), Handbook of perception. (Vol. 2, pp. 391-447). New York: Academic Press.

Cattell, R. B. (1966). The scree test for the number of factors. Multivariate Behavioral Research, 1, 245-276.

Cattell, R. B., & Jaspers, J. A. (1967). A general plasmode for factor analytic exercises and research. Multivariate Behavioral Research Monographs.

Cattell, R. B., & Khanna, D. (1977). Principles and procedures for factor analysis. In R. Einstein, A. Ralston, & H. S. Will (Eds.), Statistical Methods for Digital Computers. New York: Wiley Interscience.

Chambers, J. M., Cleveland, W. S., Kleiner, B., & Tukey, P. A. (1983). Graphical methods for data analysis. Bellmont, CA: Wadsworth.

Chan, L. K., Cheng, S. W., & Spiring, F. (1988). A new measure of process capability: Cpm. Journal of Quality Technology, 20, 162-175.

Chen, J. (1992). Some results on 2(nk) fractional factorial designs and search for minimum aberration designs. Annals of Statistics, 20, 2124-2141.

Chen, J., & Wu, C. F. J. (1991). Some results on s(nk) fractional factorial designs with minimum aberration or optimal moments. Annals of Statistics, 19, 1028-1041.

Chen, J., Sun, D. X., & Wu, C. F. J. (1993). A catalog of two-level and three-level fractional factorial designs with small runs. International Statistical Review, 61, 131-145.

Chernoff, H. (1973). The use of faces to represent points in k-dimensional space graphically. Journal of American Statistical Association, 68, 361-368.

Christ, C. (1966). Econometric models and methods. New York: Wiley.

Clarke, G. M., & Cooke, D. (1978). A basic course in statistics. London: Edward Arnold.

Clements, J. A. (1989). Process capability calculations for non-normal distributions. Quality Progress. September, 95-100.

Cleveland, W. S. (1979). Robust locally weighted regression and smoothing scatterplots. Journal of the American Statistical Association, 74, 829-836.

Cleveland, W. S. (1984). Graphs in scientific publications. The American Statistician, 38, 270-280.

Cleveland, W. S. (1985). The elements of graphing data. Monterey, CA: Wadsworth.

Cleveland, W. S. (1993). Visualizing data. Murray Hill, NJ: AT&T.

Cleveland, W. S., Harris, C. S., & McGill, R. (1982). Judgements of circle sizes on statistical maps. Journal of the American Statistical Association, 77, 541-547.

Cliff, N. (1983). Some cautions concerning the application of causal modeling methods. Multivariate Behavioral Research, 18, 115-126.

Cochran, W. G. (1950). The comparison of percentages in matched samples. Biometrika, 37, 256-266.

Cohen, J. (1977). Statistical power analysis for the behavioral sciences. (Rev. ed.). New York: Academic Press.

Cohen, J. (1983). Statistical power analysis for the behavioral sciences. (2nd Ed.). Mahwah, NJ: Lawrence Erlbaum Associates.

Cohen, J. (1994). The earth is round (p < .05). American Psychologist, 49, 997-1003.

Cole, D. A., Maxwell, S. E., Arvey, R., & Salas, E. (1993). Multivariate group comparisons of variable systems: MANOVA and structural equation modeling. Psychological Bulletin, 114, 174-184.

Collett, D. (2003). Modelling survival data in medical research. CRC Press.

Connor, W. S., & Young, S. (1984). Fractional factorial experiment designs for experiments with factors at two and three levels. In R. A. McLean & V. L. Anderson (Eds.), Applied factorial and fractional designs. New York: Marcel Dekker.

Connor, W. S., & Zelen, M. (1984). Fractional factorial experiment designs for factors at three levels. In R. A. McLean & V. L. Anderson (Eds.), Applied factorial and fractional designs. New York: Marcel Dekker.

Conover, W. J. (1974). Some reasons for not using the Yates continuity correction on 2 x 2 contingency tables. Journal of the American Statistical Association, 69, 374-376.

Conover, W. J., Johnson, M. E., & Johnson, M. M. (1981). A comparative study of tests for homogeneity of variances with applications to the outer continental shelf bidding data. Technometrics, 23, 357-361.

Cook, R. D. (1977). Detection of influential observations in linear regression. Technometrics, 19, 15-18.

Cook, R. D., & Nachtsheim, C. J. (1980). A comparison of algorithms for constructing exact D-optimal designs. Technometrics, 22, 315-324.

Cook, R. D., & Weisberg, S. (1982). Residuals and Influence in Regression. (Monographs on statistics and applied probability). New York: Chapman and Hall.

Cooke, D., Craven, A. H., & Clarke, G. M. (1982). Basic statistical computing. London: Edward Arnold.

Cooley, J. W., & Tukey, J. W. (1965). An algorithm for the machine computation of complex Fourier series. Mathematics of Computation, 19, 297-301.

Cooley, W. W., & Lohnes, P. R. (1971). Multivariate data analysis. New York: Wiley.

Cooley, W. W., & Lohnes, P. R. (1976). Evaluation research in education. New York: Wiley.

Coombs, C. H. (1950). Psychological scaling without a unit of measurement. Psychological Review, 57, 145-158.

Coombs, C. H. (1964). A theory of data. New York: Wiley.

Corballis, M. C., & Traub, R. E. (1970). Longitudinal factor analysis. Psychometrika, 35, 79-98.

Corbeil, R. R., & Searle, S. R. (1976). Restricted maximum likelihood (REML) estimation of variance components in the mixed model. Technometrics, 18, 31-38.

Cormack, R. M. (1971). A review of classification. Journal of the Royal Statistical Society, 134, 321-367.

Cornell, J. A. (1990a). How to run mixture experiments for product quality. Milwaukee, Wisconsin: ASQC.

Cornell, J. A. (1990b). Experiments with mixtures: designs, models, and the analysis of mixture data (2nd ed.). New York: Wiley.

Cox, D. R. (1957). Note on grouping. Journal of the American Statistical Association, 52, 543-547.

Cox, D. R. (1959). The analysis of exponentially distributed life-times with two types of failures. Journal of the Royal Statistical Society, 21, 411-421.

Cox, D. R. (1964). Some applications of exponential ordered scores. Journal of the Royal Statistical Society, 26, 103-110.

Cox, D. R. (1970). The analysis of binary data. New York: Halsted Press.

Cox, D. R. (1972). Regression models and life tables. Journal of the Royal Statistical Society, 34, 187-220.

Cox, D. R., & Oakes, D. (1984). Analysis of survival data. New York: Chapman & Hall.

Cramer, H. (1946). Mathematical methods in statistics. Princeton, NJ: Princeton University Press.

Cristianini, N., & Shawe-Taylor, J. (2000). Introduction to support vector machines and other kernel-based learning methods. Cambridge, UK: Cambridge University Press.

Crowley, J., & Hu, M. (1977). Covariance analysis of heart transplant survival data. Journal of the American Statistical Association, 72, 27-36.

Cudeck, R. (1989). Analysis of correlation matrices using covariance structure models. Psychological Bulletin, 105, 317-327.

Cudeck, R., & Browne, M. W. (1983). Cross-validation of covariance structures. Multivariate Behavioral Research, 18, 147-167.

Cutler, S. J., & Ederer, F. (1958). Maximum utilization of the life table method in analyzing survival. Journal of Chronic Diseases, 8, 699-712.