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Muller, Keith

  • Kairalla, J. A., Coffey, C. S., & Muller, K. E. (2008). GLUMIP 2.0: SAS/IML® software for planning internal pilots. Journal of Statistical Software, 28(7): 1-32.

  • Komro, K. A., Maldonado-Molina, M. M., Tobler, A. L., Bonds, J. & Muller, K. E. (2007). Effects of home access and availability of alcohol on young adolescents' alcohol use. Addiction, 102(10): 1597-1608.

  • Coffey, C. S., Kairalla, J. A. & Muller, K. E. (2007) Practical methods for bounding type I error rates with an internal pilot design. Communications in Statistics: Theory and Methods, 36(11): 2143-2157.

  • Komro, K. A., Maldonado-Molina, M. M., Tobler, A. L., Bonds, J. R. & Muller, K. E. (2007). Effects of home access and availability of alcohol on young adolescents alcohol use. The Scientific Journal of Addiction Issues, 13: 91-110.

  • Kleinbaum, D. G., Kupper, L. L., Nizam, A. & Muller, K. E. (2007). Applied Regression Analysis and Other Multivariable Methods. Fourth Edition. Boston: Duxbury Press.

  • Ahn, J., Marron, J. S., Muller, K. E., & Chi, Y.-Y. (2007). The high dimension, low sample size geometric representation holds under mild conditions. Biometrika, 94: 760-766.

  • Gurka, M. J., Coffey, C. S., & Muller, K. E. (2007). Internal pilots for a class of linear mixed models with Gaussian and compound symmetric data. Statistics in Medicine, 26: 4083–4099.

  • Muller, K. E., Edwards, L. J., Simpson, S. L., & Taylor, D. J. (2007). Statistical tests with accurate size and power for balanced linear mixed models. Statistics in Medicine, 26: 3639–3660.

  • Ahn, J., Marron, J. S., Muller, K. E. & Chi, Y. Y. (2007). The High Dimension, Low Sample Size Geometric Representation Holds Under Mild Conditions. Biometrika, 94: 760 - 766.

  • Muller, K. E., & Stewart, P.W. (2006). Linear Model Theory; Univariate, Multivariate, and Mixed Models. New York: Wiley.

  • Gurka, M. J., Edwards, L. J., Muller, K. E., & Kupper, L. L. (2006). Extending the Box-Cox transformation to the linear mixed model. Journal of the Royal Statistical Society Series A: Statistics in Society, 169(2): 255-272.

  • Kim, H., Gribbin, M. J., Muller, K. E., & Taylor, D. J. (2006). Analytic and computational forms for the ratio of a noncentral chi square and a Gaussian quadratic form. Journal of Computational and Graphical Statistics, 15: 443-459.

  • Kim, H. H., Pisano, E. D., Cole, E. B., Jiroutek, M. R., Muller, K. E., et al. (2006). Comparison of specificity for calcifications in digital mammography using softcopy display versus screen-film mammography. American Journal of Roentgenology, 187: 47-50.

  • Hemminger, B. M., Molina, P. L., Egan, T. M., Detterbeck, F. C., Muller, K. E., Coffey, C. S. & Lee, J. K. T. (2005). Assessment of realtime 3D visualization for cardiothoracic diagnostic evaluation and surgery planning. Journal of Digital Imaging, 18: 145-153.

  • Cole, E., Pisano, E., Zeng, D., Muller, K. E., et al. (2005). The effects of grey scale image processing on digital mammography interpretation performance. Academic Radiology, 12: 585-595.

  • Rao M., Stough, J., Chi, Y. Y., Muller, K. E., Tracton, G. S., Pizer, S. M., & Chaney, E. L. (2005). Comparison of Human and Automatic Segmentations of Kidneys from CT Images. International Journal of Radiation Oncology, Biology and Physics, 61: 954 - 960.

  • Kistner, E. O., & Muller, K. E. (2004). Exact distributions of intraclass correlation and Cronbach's alpha and Gaussian data and general covariance. Psychometrika, 69: 459-474.

  • Jiroutek, M. R., Muller, K. E., Kupper, L. L., & Stewart, P. W. (2003). A new method for choosing sample size for confidence interval-based inferences. Biometrics, 59: 580-590.

  • Coffey, C.S., & Muller, K. E. (2003). Properties of internal pilots with the univariate approach to repeated measures. Statistics in Medicine, 22: 2469-2485.

  • Glueck, D. H., & Muller, K. E. (2003). Adjusting power for a baseline covariate in a linear model. Statistics in Medicine, 22: 2535-2551.

  • Gerig G., Muller, K. E., Kistner, E. O., Chi, Y. Y., Chakos, M., Styner M., & Lieberman, J. A. (2003). Age and Treatment Related Local Hippocampal Changes in Schizophrenia Explained by a Novel Shape Analysis Method. MICCAI, 2: 653 - 660.

  • Muller, K. E., & Fetterman, B. A. (2002). A Unified Approach to Regression and ANOVA: Theory and Applications Using SAS® Software. Cary, NC: SAS Institute.

  • Catellier, D. J. & Muller, K. E. (2002). Sample size and power considerations in physical activity research. Chapter 6, In G. J. Welk, (Ed.), Physical Activity Assessments for Health-Related Research (pp. 93-104). Champaign, IL: Human Kinetics.

  • Taylor, D. J., Kupper, L. L., & Muller, K. E. (2002). Improved approximate confidence intervals for the mean of a lognormal distribution. Statistics in Medicine, 21: 1443-1459.

  • Edwards, L. J., Stewart, P. W., Muller, K. E., & Helms, R. W. (2001). Linear equality constrants in the general mixed model. Biometrics, 57: 1185-1190.

  • Coffey, C. S. & Muller, K. E. (2001). Controlling test size while gaining the benefits of an internal pilot design. Biometrics, 57: 625-631.

  • Catellier, D. J. & Muller, K. E. (2000) Tests for Gaussian repeated measures with missing data in small samples. Statistics in Medicine, 19: 1101-1114.

  • Coffey, C. S., & Muller, K. E. (1999). Exact test size and power of a Gaussian error linear model for an internal pilot study. Statistics in Medicine, 18: 1199-1214.

  • Muller, K.E. (1998). Power of a hypothesis test. In P. Armitage & T. Colton, (Ed.), The Encyclopedia of Biostatistics. London, England: Wiley, UK.

  • Selicato, G. R., & Muller, K. E. (1998). Approximating power of the unconditional test for correlated binary pairs. Communications in Statistics: Simulation and Computation, 27: 553-564.

  • Muller, K. E., & Pasour, V. B. (1997). Bias in linear model power and sample size due to estimating variance. Communications in Statistics: Theory and Methods, 26: 839-851.

  • Muller, K. E., & Chen Mok, M. (1997) The distribution of Cook's D statistic. Communications in Statistics: Theory and Methods, 26: 525-546.

  • Taylor, D. J., & Muller, K. E. (1996). Bias in linear model power and sample size calculation due to estimating noncentrality. Communications in Statistics: Theory and Methods, 25: 1595-1610.

  • DiSantostefano, R. L., & Muller, K. E. (1995). A comparison of power approximations for Satterthwaite's test. Communications in Statistics: Simulation and Computation, 24: 583-593.

  • O'Brien, R. G., & Muller, K. E. (1993). A unified approach to statistical power for t-tests to multivariate models. Chapter 8, In L.K. Edwards (Ed.), Applied Analysis of Variance in Behavioral Sciences (pp. 297-344). New York: Marcel Dekker.

  • Dozier, W. G., & Muller, K. E. (1993). Small-sample power of uncorrected and Satterthwaite corrected t tests for comparing binomial proportions. Communications in Statistics: Simulation and Computation, 22: 245-264.

  • Dozier, W. G. & Muller, K. E. (1993). Small-sample power of uncorrected and Satterthwaite corrected t tests for comparing binomial proportions. Communications in Statistics: Simulation and Computation, 22: 245-264.

  • Muller, K. E., LaVange, L. M., Ramey, S. L., & Ramey, C. T. (1992). Power calculations for general linear multivariate models including repeated measures applications. Journal of the American Statistical Association, 87: 1209-1226.

  • Frey, C. M., & Muller, K. E. (1992). Analysis methods for nonlinear models with compound-symmetric covariance. Communications in Statistics: Theory and Methods, 21: 1163-1182.

  • Muller, K. E., & Benignus, V. A. (1992). Increasing scientific power with statistical power. Neurotoxicology and Teratology, 14: 211-219.

  • Muller, K. E., & Barton, C. N. (1989). Approximate power for repeated-measures ANOVA lacking sphericity. Journal of the American Statistical Association, 84: 549-555. Also see (1991). Correction to "Approximate power for repeated measures ANOVA lacking sphericity," Journal of the American Statistical Association, 86: 255-256.

  • Muller, K. E. (1986). Design and analytical methods. Chapter 18. In Z. Annau (Ed.), Neurobehavioral Toxicology, (pp. 404-423). Baltimore: Johns Hopkins Press.

  • Muller, K. E., Barton, C. N., & Benignus, V.A. (1984). Recommendations for appropriate statistical practice in toxicologic experiments. Neurotoxicology, 5: 113-126.

  • Muller, K. E., & Peterson, B. L. (1984). Practical methods for computing power in testing the multivariate general linear hypothesis. Computational Statistics and Data Analysis, 2: 143-158.

  • Muller, K. E., Otto, D. A., & Benignus, V. A. (1983). Design and analysis issues and strategies in psychophysiological research. Psychophysiology, 20: 212-218.

  • Muller, K. E. (1982). Understanding canonical correlation through the general linear model and principal components. American Statistician, 36: 342-354.

  • Wardrop, J. L., Anderson, T. H., Hively, W., Hastings, C. N., Anderson, R. I. & Muller, K. E. (1982). A framework for analyzing the inference structure of educational achievement tests. Journal of Educational Measurement, 19: 1-18.

  • Muller, K. E. (1981). Relationships between redundancy analysis, canonical correlation, and multivariate regression. Psychometrika, 46: 139-142.

Most Recent EHPR Publications
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