Design and Analysis of Experiments

Design and Analysis of Experiments

Volumn 2, Issue , 2005, Pages 1-780

  Hinkelmann, Klaus ^a   Kempthorne, Oscar ^b  

^a VIRGINIA POLYTECHNIC INSTITUTE AND STATE UNIVERSITY   (United States)

^b IOWA STATE UNIVERSITY   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

PHILOSOPHICAL ASPECTS; STATISTICS; STUDENTS;

DESIGN AND ANALYSIS OF EXPERIMENTS; FRACTIONAL FACTORIAL DESIGNS; GRADUATE STUDENTS; HISTORICAL DEVELOPMENT; INDUSTRY PROFESSIONALS; LATEST DEVELOPMENT; STATISTICAL ANALYSIS SYSTEMS; SUPERSATURATED DESIGNS;

DESIGN OF EXPERIMENTS;

EID: 84949527882     PISSN: None     EISSN: None     Source Type: Book    
DOI: 10.1002/0471709948     Document Type: Book

References (383)

1. Abel, R. J. R., A. E. Brouwer, C. J. Colbourn and J. H. Dinitz (1996). Mutually orthogonal latin squares (MOLS). In: The CRC Handbook of Combinatorial Designs. C. J. Colbourn and J. H. Dinitz (eds.). Boca Raton, FL : CRC, pp. 111-142.
2. Abraham, B., H. Chipman and K. Vijayan (1999). Some risks in the construction and analysis of supersaturated designs. Technometrics, 41, 135-141.
3. n factorial experiment. Technometrics, 3, 479-496.
4. Addelman, S. (1962a). Orthogonal main-effect plans for asymmetrical factorial experiments. Technometrics, 4, 21-46 (Erratum 4, 440).
5. Addelman, S. (1962b). Symmetrical and asymmetrical fractional factorial plans. Technometrics, 4, 47-58.
6. Addelman, S. and O. Kempthorne (1961). Some main-effect plans and orthogonal arrays of strength two. Ann. Math. Statist., 32, 1167-1176.
7. Adhikary, B. (1966). Some types of m-associate PBIB association schemes. Calcutta Statist. Assoc. Bull., 15, 47-74.
8. Adhikary, B. (1967). A new type of higher associate cyclical association schemes. Calcutta Statist. Assoc. Bull., 16, 40-44.
9. Afsarinejad, K. (1983). Balanced repeated measurement designs. Biometrika, 70, 199-204.
10. Afsarinejad, K. (1990). Repeated measurement designs-A review. Commun. Statist.-Theory Meth., 19, 3985-4028.
11. Afsarinejad, K. and A. S. Hedayet (2002). Repeated measurements designs for a model with self and simple mixed carryover effects. J. Statist. Plann. Inf., 106, 449-459.
12. Aggarwal, K. R. (1974). Some higher-class PBIB designs and their applications as confounded factorial experiments. Ann. Inst. Statist. Math., 26, 315-323.
13. Aggarwal, K. R. and T. P. Singh (1981). Methods of construction of balanced arrays with application to factorial designs. Calcutta Statist. Assoc. Bull., 30, 89-93.
14. Atkinson, A. C. and A. N. Donev (1992). Optimum Experimental Design. Oxford: Clarendon.
15. Baksalary, J. K. and P. D. Puri (1990). Pairwise-balanced, variance-balanced and resistant incomplete block designs revisited. Ann. Inst. Statist. Math., 42, 163-171.
16. 2 experimental units. Biometrics, 24, 61-73.
17. Banerjee, K. S. (1970). Some observations on the White-Hultquist procedure for the construction of confounding plans for mixed factorial designs. Ann. Math. Statist., 41, 1108-1113.
18. Banerjee, K. S. (1975). Weighing Designs. New York: Dekker.
19. Baumert, L. D., S. W. Golomb and M. Hall, Jr. (1962). Discovery of an Hadamard matrix of order 92. Bull. Am. Math. Soc., 68, 237-238.
20. Bechhofer, R. E. and A. C. Tamhane (1981). Incomplete block designs for comparing treatments with a control: General theory. Technometrics, 23, 45-57 (Corrigendum 24, 171).
21. Bechhofer, R. E. and A. C. Tamhane (1983a). Incomplete block designs for comparing treatments with a control (II): Optimal designs for p = 2(1)6, k = 2 and p = 3, k = 3. Sankhyā, Ser. B, 45, 193-224.
22. Bechhofer, R. E. and A. C. Tamhane (1983b). Design of experiments for comparing treatments with a control: Tables of optimal allocations of observations. Technometrics, 25, 87-95.
23. Bechhofer, R. E. and A. C. Tamhane (1985). Tables of admissible and optimal balanced treatment incomplete block (BTIB) designs for comparing treatments with a control. Selected Tables Math. Statist., 8, 41-139.
24. Berenblut, I. I. (1964). Change-over design with complete balance for first residual effects. Biometrics, 20, 707-712.
25. Berenblut, I. I. (1967). A change-over design for testing a treatment factor at four equally spaced levels. J. Roy. Statist. Soc., B, 29, 370-373.
26. Berenblut, I. I. (1968). Change-over designs balanced for the linear component of first residual effects. Biometrika, 55, 297-303.
27. Beyer, W. H. (ed.) (1991). CRC Standard Probability and Statistics Tables and Formulae. Boca Raton, FL : CRC.
28. Bhattacharya, C. G. (1998). Goodness of Yates-Rao procedure for recovery of inter-block information. Sankhyā A, 60, 134-144.
29. k-p designs. Technometrics, 36, 308-311.
30. Blaisdell, E. A. and D. Raghavarao (1980). Partially balanced changeover designs based on m-associate PBIB designs. J. Roy. Statist. Soc., B, 42, 334-338.
31. Booth, K. H. V. and D. R. Cox (1962). Some systematic supersaturated designs. Technometrics, 4, 489-495.
32. Bose, R. C. (1939). On the construction of balanced incomplete block designs. Ann. Eugenics, 9, 353-399.
33. Bose, R. C. (1942). A note on the resolvability of balanced incomplete block designs. Sankhyā, 6, 105-110.
34. Bose, R. C. (1947a). On a resolvable series of balanced incomplete block designs. Sankhyā, 8, 249-256.
35. Bose, R. C. (1947b). Mathematical theory of the symmetrical factorial design. Sankhyā, 8, 107-166.
36. Bose, R. C. and K. A. Bush (1952). Orthogonal arrays of strength two and three. Ann. Math. Statist., 23, 508-524.
37. Bose, R. C. and W. S. Connor (1952). Combinatorial properties of group divisible incomplete block designs. Ann. Math. Statist., 23, 367-383.
38. Bose, R. C. and K. Kishen (1940). On the problem of confounding in the general symmetrical factorial design. Sankhyā, 5, 21-36.
39. Bose, R. C. and D. M. Mesner (1959). On linear associative algebras corresponding to association schemes of partially balanced designs. Ann. Math. Statist., 30, 21-38.
40. Bose, R. C. and K. R. Nair (1939). Partially balanced incomplete block designs. Sankhyā, 4, 337-372.
41. Bose, R. C. and T. Shimamoto (1952). Classification and analysis of partially balanced incomplete block designs with two associate classes. J. Am. Statist. Assoc., 47, 151-184.
42. Bose, R. C., W. H. Clatworthy and S. S. Shrikhande (1954). Tables of partially balanced incomplete block designs with two associate classes. North Carolina Agricultural Experiment Station Technical Bulletin No. 107, Raleigh, NC.
43. Bose, R. C., S. S. Shrikhande and K. N. Bhattacharya (1953). On the construction of group divisible incomplete block designs. Ann. Math. Statist., 24, 167-195.
44. Box, G. E. P. (1988). Signal-to-noise ratios, performance criteria, and transformation. Technometrics, 30, 1-17.
45. k-p fractional factorial designs. Part I. Technometrics, 3, 311-351 (Errata 5, 417).
46. k-p fractional factorial designs. Part II. Technometrics, 3, 449-458.
47. Box, G. E. P. and R. D. Meyer (1986a). An analysis of unreplicated fractional factorials. Technometrics, 28, 11-18.
48. Box, G. E. P. and R. D. Meyer (1986b). Dispersion effects from fractional designs. Technometrics, 28, 19-27.
49. Box, G. E. P. and K. B. Wilson (1951). On the experimental attainment of optimum conditions. J. Roy. Statist. Soc., B, 13, 1-45.
50. Bradley, J. V. (1958). Complete counterbalancing of immediate sequential effects in a Latin square design. J. Am. Statist. Assoc., 53, 525-528.
51. Bulutoglu, D. A. and C.-S. Cheng (2003). Hidden projection properties of some nonregular fractional factorial designs and their applications. Ann. Statist., 31, 1012-1026.
52. Calinski, T. and S. Kageyama (2000). Block Designs: A Randomization Approach. Volume I: Analysis. New York: Springer.
53. Calvin, L. D. (1954). Doubly balanced incomplete block designs for experiments in which the treatment effects are correlated. Biometrics, 10, 61-88.
54. Carmichael, R. D. (1956). Introduction to the Theory of Groups of Finite Order. New York: Dover.
55. Chakravarti, I. M. (1956). Fractional replication in asymmetrical factorial designs and partially balanced arrays. Sankhyā, 17, 143-164.
56. Chakravarti, I. M. (1961). On some methods of construction of partially balanced arrays. Ann. Math. Statist., 32, 1181-1185.
57. Chang, C.-T. (1989). On the construction of hypercubic design. Comm. Statist.-Theory Meth., 18, 3365-3371.
58. Chang, C.-T. and K. Hinkelmann (1987). A new series of EDG-PBIB designs. J. Statist. Plann. Inf., 16, 1-13.
59. Chang, L.-C. and W.-R. Liu (1964). Incomplete block designs with square parameters for which k ≤ 10 and r ≤ 10. Sci. Sinica, 13, 1493-1495.
60. Chang, L.-C., C.-W. Liu and W.-R. Liu (1965). Incomplete block designs with triangular parameters for which k ≤ 10 and r ≤ 10. Sci. Sinica, 14, 329-338.
61. Chatterjee, K., L.-Y. Deng and D. K. J. Lin (2001). Two-level search design for main-effect plus two plan. Metrika, 54, 233-245.
62. Chatterjee, K. and R. Mukerjee (1986). Some search designs for symmetric and asymmetric factorials. J. Statist. Plann. Inf., 13, 357-363.
63. Chatterjee, K. and R. Mukerjee (1993). Search designs for estimating main effects and searching several two-factor interactions in general factorials. J. Statist. Plann. Inf., 35, 131-138.
64. Chen, H. and C.-S. Cheng (1999). Theory of optimal blocking of 2n-m designs. Ann. Statist., 27, 1948-1973.
65. Chen, H. H. and C.-S. Cheng (2004). Aberration, estimation capacity and estimation index. Statist. Sinica, 14, 203-215.
66. Cheng, C.-S. (1996). Optimal design: Exact theory. In: Handbook of Statistics, Volume 13. S. Ghosh and C. R. Rao (eds.). Amsterdam: Elsevier Science, pp. 977-1006.
67. 2)-optimal supersaturated designs. Statist. Sinica, 7, 929-939.
68. Cheng, C.-S., D. M. Steinberg and D. X. Sun (1999). Minimum aberration and maximum estimation capacity. J. Roy. Statist. Soc., B, 61, 85-93.
69. Cheng, C.-S. and C.-F. Wu (1980). Balanced repeated measurement designs. Ann. Statist., 8, 1272-1283 [Correction 11, (1983), 349].
70. 8 fractional factorial designs of resolution V, 37 ≤ n ≤ 51. Sankhyā, A, 36, 41-52.
71. 7 fractional factorial designs of resolution V, 43 ≤ n ≤ 48. Sankhyā, B, 37, 429-447.
72. Clatworthy, W. H. (1955). Partially balanced incomplete block designs with two associate classes and two treatments per block. J. Res. National Bur. Standards, 54.
73. Clatworthy, W. H. (1956). Contributions on partially balanced incomplete block designs with two associate classes. NBS Appl. Math. Series, 47.
74. Clatworthy, W. H. (1967). Some new families of partially balanced designs of the Latin square type and related designs. Technometrics, 9, 229-244.
75. Clatworthy, W. H. (1973). Tables of two-associate-class partially balanced designs. NBS Appl. Math. Series, 63.
76. Cochran, W. G. (1939). Long-term agricultural experiments (with discussion). J. Roy. Statist. Soc., B, 6, 104-148.
77. Cochran, W. G., K. M. Autrey and C. Y. Cannon (1941). A double change-over design for dairy cattle feeding experiments. J. Dairy Sci., 24, 937-951.
78. Cochran, W. G. and G. M. Cox (1957). Experimental Designs, 2nd ed. New York: Wiley.
79. Cochran, W. G. and G. M. Cox (1992). Experimental Designs. New York: Wiley.
80. Cohen, A. and H. B. Sackrowitz (1989). Exact tests that recover interblock information in balanced incomplete block designs. J. Am. Statist. Assoc., 84, 556-559.
81. Connor, W. S. and W. H. Clatworthy (1954). Some theorems for partially balanced designs. Ann. Math. Statist., 25, 100-112.
82. Constantine, G. (1983). On the trace efficiency for control of reinforced balanced incomplete block designs. J. Roy. Statist. Soc., B, 45, 31-36.
83. Corbeil, R. R. and S. R. Searle (1976). Restricted maximum likelihood (REML) estimation of variance components in the mixed model. Technometrics, 18, 31-38.
84. Cotter, S. C., J. A. John and T. M. F. Smith (1973). Multi-factor experiments in nonorthogonal designs. J. Roy. Statist. Soc., B, 35, 361-367.
85. Cotton, J. W. (1998). Analyzing Within-Subjects Experiments. Mahwah, NJ: Lawrence Earlbaum Associates.
86. Cox, D. R. (1958). The interpretation of the effects of non-additivity in the Latin square. Biometrika, 45, 69-73.
87. Cox D. R. and N. Reid (2000). The Theory of the Design of Experiments. Boca Raton, FL : Chapman and Hall / CRC.
88. Daniel, C. (1959). Use of half-normal plots in interpreting factorial two-level experiments. Technometrics, 1, 311-341.
89. Daniel, C. (1973). One-at-a-time plans. J. Am. Statist. Assoc., 68, 353-360.
90. Das, M. N. (1958). On reinforced incomplete block designs. J. Indian Soc. Agric. Statist., 10, 73-77.
91. David, H. A. (1963). The Method of Paired Comparisons. London: Griffin.
92. David, H. A. (1965). Enumeration of cyclic paired-comparison designs. Am. Math. Monthly, 72, 241-248.
93. David, H. A. and F.W.Wolock (1965). Cyclic designs. Ann. Math. Statist., 36, 1526-1534.
94. Davies, O. L. (ed.) (1956). The Design and Analysis of Industrial Experiments. London: Oliver and Boyd.
95. Davis, A. W. and W. B. Hall (1969). Cyclic change-over designs. Biometrika, 56, 283-293.
96. Dean, A. M. and J. A. John (1975). Single replication factorial experiments in generalized cyclic designs: II. Asymmetrical arrangements J. Roy. Statist. Soc, B, 37, 72-76.
97. Dénes, J. and A. D. Keedwell (1974). Latin Squares and Their Applications. London: English Universities Press.
98. Dey, A. (1985). Orthogonal Fractional Factorial Design. New York: Halsted.
99. Dunnett, C. W. (1955). A multiple comparison procedure for comparing several treatments with a control. J. Am. Statist. Assoc., 50, 1096-1121.
100. Dunnett, C. W. (1964). New tables for multiple comparisons with a control. Biometrics, 20, 482-491.
101. Eccleston, J. A. and C. A. McGilchrist (1986). Algebra of a row-column design. J. Statist. Plann. Inf., 12, 305-310.
102. Eccleston, J. A. and K. G. Russell (1975). Connectedness and orthogonality in multi-factor designs. Biometrika, 62, 341-345.
103. Eccleston, J. A. and K. G. Russell (1977). Adjusted orthogonality in non-orthogonal designs. Biometrika, 64, 339-345.
104. Ehrenfeld, S. (1953). On the efficiency of experimental design. Ann. Math. Statist., 26, 247-255.
105. Engel, J. (1992). Modelling variation in industrial experiments. Appl. Statist., 41, 579-593.
106. Fan, J. and R. Li (2001). Variable selection via nonconcave penalized likelihood and its oracle properties. J. Am. Statist. Assoc., 96, 1348-1360.
107. Fang, K.-T., D. K. J. Lin and C.-X. Ma (2000). On the construction of multi-level supersaturated designs. J. Statist. Plann. Inf., 86, 239-252.
108. Federer, W. T. (1955). Experimental Design-Theory and Application. New York: Macmillan.
109. Fichtner, A. (2000). Auswertung eines Mais-Feldexperimentes zur Untersuchung von Genotypeffekten bei quantitativen Merkmalen. Unpubl. Diplomarbeit: Universität Dortmund.
110. Finney, D. J. (1945). The fractional replication of factorial experiments. Ann. Eugenics, 12, 291-301 (Correction 15, 276).
111. Finney, D. J. (1956). Cross-over designs in bioassay. Proc. Roy. Soc., B, 145, 42-60.
112. Fisher, R. A. (1940). An examination of the different possible solutions of a problem in incomplete blocks. Ann. Eugenics, 10, 52-75.
113. Fisher, R. A. (1942). The theory of confounding in factorial experiments in relation to the theory of groups. Ann. Eugenics, 11, 341-353.
114. Fisher, R. A. (1945). A system of confounding for factors with more than two alternatives, giving completely orthogonal cubes and higher powers. Ann. Eugenics, 12, 283-290.
115. Fisher, R. A. (1949). The Design of Experiments, 5th ed. London: Hafner.
116. Fisher, R. A. and F. Yates (1957). Statistical Tables for Biological, Agricultural and Medical Research, 5th ed. New York: Hafner.
117. Fletcher, D. J., S. M. Lewis and J. N. S. Matthews (1990). Factorial designs for crossover clinical trials. Statist. Medicine, 9, 1121-1129.
118. Folks, J. L. and O. Kempthorne (1960). The efficiency of blocking in incomplete block designs. Biometrika, 47, 273-283.
119. k-p designs. Technometrics, 22, 601-608.
120. Fujii, Y. (1976). An upper bound of resolution in symmetrical fractional factorial designs. Ann. Statist., 4, 662-667.
121. m factorial experiments. J. Statist. Plann. Inf., 5, 381-389.
122. Ghosh, S. (1982). Robustness of BIBD against the unavailability of data. J. Statist. Plann. Inf., 6, 29-32.
123. Ghosh, S. and C. Burns (2001). Two general classes of search designs for factor screening experiments with factors at three levels. Metrika, 54, 1-7.
124. Ghosh, S. and C. Burns (2002). Comparison of four new classes of search designs. Austr. New Zealand J. Statist., 44, 357-366.
125. Ghosh, S. and L. Teschmacher (2002). Comparisons of search designs using search probabilities. J. Statist. Plann. Inf., 104, 439-458.
126. Gill, P. S. (1992). Balanced change-over designs for autocorrelated observations. Austral. J. Statist., 34, 415-420.
127. Good, I. J. (1958). The interaction algorithm and practical Fourier analysis. J. Roy. Statist. Soc., B., 20, 361-372 (Addendum 22, 372-375).
128. Graybill, F. A. (1969). Matrices with Applications in Statistics. Belmont, CA: Wadsworth.
129. Graybill, F. A. and R. B. Deal (1959). Combining unbiased estimators. Biometrics, 15, 543-550.
130. Graybill, F. A. and D. L.Weeks (1959). Combining inter-block and intra-block information in balanced incomplete block designs. Ann. Math. Statist., 30, 799-805.
131. Grundy, P. M. and M. J. R. Healy (1950). Restricted randomization and quasi-Latin squares. J. Roy. Statist. Soc., B., 12, 286-291.
132. m factorial experiments. In: Probability, Statistics and Design of Experiment, R. R. Bahadur (ed.). New Delhi: Wiley Eastern. pp. 329-345.
133. Gupta, S. and R.Mukerjee (1989). A Calculus for Factorial Arrangements.Berlin: Springer.
134. Harshbarger, B. (1947). Rectangular lattices. Va. Agri. Expt. Stat. Memoir, 1, 1-26.
135. Harshbarger, B. (1949). Triple rectangular lattices. Biometrics, 5, 1-13.
136. Harshbarger, B. (1951). Near balance rectangular lattices. Va. J. Sci., 2, 13-27.
137. Harshbarger, B. and L. L. Davis (1952). Latinized rectangular lattices. Biometrics, 8, 73-84.
138. Hartley, H. O. and J. N. K. Rao (1967). Maximum-likelihood estimation for the mixed analysis of variance model. Biometrika, 54, 93-108.
139. Hartley, H. O. and C. A. B. Smith (1948). The construction of Youden squares. J. Roy. Statist. Soc., B, 10, 262-263.
140. Hedayat, A. and K. Afsarinejad (1975). Repeated measurement designs I. In: A Survey of Statistical Design and Linear Models. J. N. Srivastava, (ed.). Amsterdam: North Holland, pp. 229-242.
141. Hedayat, A. and K. Afsarinejad (1978). Repeated measurement designs II. Ann. Statist., 6, 619-628.
142. Hedayat, A. and P. W. M. John (1974). Resistant and susceptible BIB designs. Ann. Statist., 2, 148-158.
143. Hedayat, A. S. and D. Majumdar (1984). A-Optimal incomplete block designs for controltest treatment comparisons. Technometrics, 26, 363-370.
144. Hedayat, A. and E. Seiden (1970). F-square and orthogonal F-square design: A generalization of Latin square and orthogonal Latin square design. Ann. Math. Statist., 41, 2035-2044.
145. Hedayat A. S. and W. D. Wallis (1978). Hadamard matrices and their applications. Ann. Statist., 6, 1184-1238.
146. Hedayat A. S. and M. Yang (2003). Universal optimality of balanced uniform crossover designs. Ann. Statist., 31, 978-983.
147. Hedayat, A. S., M. Jacroux and D. Majumdar (1988). Optimal designs for comparing test treatments with controls (with discussion). Statist. Sci., 4, 462-491.
148. Hedayat, A., D. Raghavarao and E. Seiden (1975). Further contributions to the theory of F-squares design. Ann. Statist., 3, 712-716.
149. Hedayat, A. S., N. J. A. Sloane and J. Stufken (1999). Orthogonal Arrays: Theory and Applications. New York: Springer.
150. Hemmerle, W. J. and H. O. Hartley (1973). Computing maximum likelihood estimates for the mixed A. O. V. model using the W-transformation. Technometrics, 15, 819-831.
151. Hinkelmann, K. (1964). Extended group divisible partially balanced incomplete block designs. Ann. Math. Statist., 35, 681-695.
152. Hinkelmann, K. (1997). The Kempthorne-parameterization for asymmetrical factorials. Technical Report 97-7, Department of Statistics, Virginia Tech, Blacksburg, VA.
153. Hinkelmann, K. (2001). Remembering Oscar Kempthorne (1919-2000). Statist. Sci., 16, 169-183.
154. Hinkelmann, K. and O. Kempthorne (1963). Two classes of group divisible partial diallel crosses. Biometrika, 50, 281-291.
155. Hinkelmann, K. and O. Kempthorne (1994). Design and Analysis of Experiments. Volume 1. Introduction to Experimental Design. New York: Wiley.
156. Hoblyn, T. N., S. C. Pearce and G. H. Freeman (1954). Some considerations in the design of successive experiments in fruit plantations. Biometrics, 10, 503-515.
157. Holcomb, D. R., D. C. Montgomery and W. M. Carlyle (2003). Analysis of supersaturated designs. J. Qual. Tech., 35, 13-27.
158. Hotelling, H. (1944). Some improvements in weighing and other experimental techniques. Ann. Math. Statist., 15, 297-306.
159. Huang, W.-C. L. (1989). Applications of the Chinese remainder theorem to the construction and analysis of confounding systems and randomized fractional replicates for mixed factorial experiments. Unpublished Ph.D. dissertation, Virginia Polytechnic Institute and State University, Blacksburg, VA.
160. Jacroux, M. (1984). Upper bounds for efficiency factors of block designs. Sankhyā, B, 46, 263-274.
161. Jacroux, M. (1987). On the determination and construction of MV-optimal block designs for comparing test treatments with a standard treatment. J. Statist. Plann. Inf., 15, 205-225.
162. Jarrett, R. G. (1983). Definitions and properties for m-concurrence designs. J. Roy. Statist. Soc., B., 64, 1-10.
163. Jarrett, R. G. and W. B. Hall (1978). Generalized cyclic incomplete block designs. Biometrika, 65, 397-401.
164. John, J. A. (1966). Cyclic incomplete block designs. J. Roy. Statist. Soc., B., 28, 345-360.
165. John, J. A. (1969). A relationship between cyclic and PBIB designs. Sankhyā, B, 31, 535-540.
166. John, J. A. (1973). Factorial experiments in cyclic designs. Ann. Statist, 6, 188-194.
167. John, J. A. (1987). Cyclic Designs. London: Chapman and Hall.
168. John, J. A. and A. M. Dean (1975). Single replicate factorial experiments in generalized cyclic designs: I. Symmetrical arrangements. J. Roy. Statist. Soc., B, 37, 63-71.
169. John, J. A. and J. A. Eccleston (1986). Row-column α-designs. Biometrika, 73, 301-306.
170. John, J. A. and M. H. Quenouille (1977). Experiments: Design and Analysis, 2nd ed. New York: Macmillan.
171. John, J. A. and T. M. F. Smith (1972). Two factor experiments in nonorthogonal designs. J. Roy. Statist. Soc., B, 34, 401-409.
172. John, J. A. and D. J. Street (1992). Bounds for the efficiency factor of row-column designs. Biometrika, 79, 658-661.
173. John, J. A. and D. J. Street (1993). Bounds for the efficiency factor of row-column designs (amendment). Biometrika, 80, 712-713.
174. John, J. A. and E. R. Williams (1995). Cyclic and Computer Generated Designs, 2nd ed. London: Chapman and Hall.
175. John, J. A., F. W. Wolock and H. A. David (1972). Cyclic designs. Appl. Math. Series 62. National Bureau Standards: Washington, D.C.
176. John, P. W. M. (1966). An extension of the triangular association scheme to three associate classes. J. Roy. Statist. Soc., B, 28, 361-365.
177. John, P. W. M. (1976). Robustness of balanced incomplete block designs. Ann. Statist., 4, 956-959.
178. Jones, B. and M. G. Kenward (2003). Design and Analysis of Cross-over Trials, 2nd ed. Boca Raton, FL: Chapman and Hall/CRC.
179. Kackar, R. N. (1985). Off-line quality control, parameter design, and the Taguchi method. J. Qual. Tech., 17, 176-188.
180. Kageyama, S. (1972). On the reduction of associate classes for certain PBIB designs. Ann. Math. Statist., 43, 1528-1540.
181. Kempthorne, O. (1947). A simple approach to confounding and fractional replication in factorial experiments. Biometrika, 34, 255-272.
182. Kempthorne, O. (1948). The factorial approach to the weighing problem. Ann. Math. Statist., 19, 238-245.
183. Kempthorne, O. (1952). Design and Analysis of Experiments. New York: Wiley.
184. Kempthorne, O. (1953). A class of experimental designs using blocks of two plots. Ann. Math. Statist., 24, 76-84.
185. Kempthorne, O. (1956). The efficiency factor of an incomplete block design. Ann. Math. Statist., 27, 846-849.
186. Kempthorne, O. (1984). Statistical methods and science. In: W. G. Cochran's Impact on Statistics, P.S.R.S. Rao and J. Sedransk (eds.). New York: Wiley, pp. 287-308.
187. n varieties in blocks of p plots. Biometrics, 4, 54-79.
188. s plots and in squares. Biometrics, 4, 109-121.
189. Kershner, R. P. and W. T. Federer (1981). Two-treatment crossover designs for estimating a variety of effects. J. Am. Statist. Assoc., 76, 612-618.
190. Khare, M. and W. T. Federer (1981). A simple construction procedure for resolvable incomplete block designs for any number of treatments. Biom. J., 23, 121-132.
191. Kiefer, J. (1958). On the nonrandomized optimality and randomized nonoptimality of symmetrical designs. Ann. Math. Statist., 29, 675-699.
192. Kiefer, J. (1975a). Construction and optimality of generalized Youden designs. In: A Survey of Statistical Design and Linear Models, J. N. Srivastava (ed.). Amsterdam: North-Holland, pp. 333-353.
193. Kiefer, J. (1975b). Balanced block designs and generalized Youden designs. I. Construction (Patchwork). Ann. Statist., 3, 109-118.
194. Kishen, K. and J. N. Srivastava (1959). Mathematical theory of confounding in asymmetrical and symmetrical factorial designs. J. Indian Soc. Agric. Statist., 11, 73-110.
195. Kramer, C. Y. and R. A. Bradley (1957). Intra-block analysis for factorials in two-associate class group divisible designs. Ann. Math. Statist., 28, 349-361 (Addenda, 29, 933-935).
196. Kshirsagar, A. M. (1966). Balanced factorial designs. J. Roy. Statist. Soc., B, 28, 559-567.
197. Kunert, J. (1984). Optimality of balanced uniform repeated measurements designs. Ann. Statist., 12, 1006-1017.
198. Kunert, J. (1985). Optimal repeated measurements designs for correlated observations and analysis by weighted least squares. Biometrika, 72, 375-389.
199. Kunert, J. (1997). On the use of the factor-sparsity assumption to get an estimate of the variance in saturated designs. Technometrics, 39, 81-90.
200. Kunert, J. and J. Stufken (2002). Optimal crossover designs in a model with self and mixed carryover effects. J. Am. Statist. Assoc., 97, 898-906.
201. Kurkjian, B. and M. Zelen (1962). A calculus for factorial arrangements. Ann. Math. Statist., 33, 600-619.
202. Kurkjian, B. and M. Zelen (1963). Applications of the calculus of factorial arrangements. I. Block and direct product designs. Biometrika, 50, 63-73.
203. Kusumoto, K. (1965). Hyper cubic designs. Wakayama Med. Rept., 9, 123-132.
204. Lenth, R. V. (1989). Quick and easy analysis of unreplicated factorials. Technometrics, 31, 469-473.
205. Lentner, M. and T. Bishop (1993). Experimental Design and Analysis, 2nd ed. Blacksburg, VA: Valley Book.
206. Leon, R. V., A. C. Shoemaker and R. N. Kackar (1987). Performance measure independent of adjustment: An explanation and extension of Taguchi's signal to noise ratio. Technometrics, 29, 253-265.
207. Lewis, S. M. (1982). Generators for asymmetrical factorial experiments. J. Statist. Plann. Inf., 6, 59-64.
208. Li, J. C. R. (1944). Design and statistical analysis of some confounded factorial experiments. Iowa Agri. Expt. Stat. Res. Bull. 333, 452-492.
209. Li, R. and D. K. J. Lin (2002). Data analysis in supersaturated designs. Statist. Prob. Lett., 59, 135-144.
210. Li, R. and D. K. J. Lin (2003). Analysis methods for supersaturated design: Some comparisons. J. Data Sci., 1, 249-260.
211. Lin, D. K. J. (1993). A new class of supersaturated designs. Technometrics, 35, 28-31.
212. Lin, D. K. J. and N. R. Draper (1992). Projection properties of Plackett and Burman designs. Technometrics, 34, 423-428.
213. Lin, D. K. J. and N. R. Draper (1993). Generating alias relationships for two-level Plackett and Burman designs. Comp. Statist. Data Anal., 15, 147-157.
214. Lin, P. K. (1986). Using the Chinese remainder theorem in constructing confounded designs in mixed factorial experiments. Comm. Statist.-Theory Methods, 15, 1389-1398.
215. 2) optimal supersaturated designs using cyclic BIBDs. J. Statist. Plann. Inf., 91, 139-150.
216. Lorenzen, T. J. and M. A. Wincek (1992). Blocking is simply fractionation. GM Research Publication 7709.
217. Lucas, H. L. (1957). Extra-period Latin-square change-over designs. J. Dairy Sci., 40, 225-239.
218. Majumdar, D. (1996). Optimal and efficient treatment-control designs. In: Handbook of Statistics 13, S. Ghosh and C. R. Rao (eds.). Amsterdam: Elsevier Science, pp. 1007-1053.
219. Majumdar, D. and W. Notz (1983). Optimal incomplete block designs for comparing treatments with a control. Ann. Statist., 11, 258-266.
220. m designs and two-factor aliasing. Technometrics, 10, 559-573.
221. Margolin, B. H. (1969). Resolution IV fractional factorial designs. J. Roy. Statist. Soc., B, 31, 514-523.
222. Mason, J. M. and K. Hinkelmann (1971). Change-over designs for testing different treatment factors at several levels. Biometrics, 27, 430-435.
223. Masuyama, M. (1965). Cyclic generation of triangular PBIB designs. Rep. Stat. Appl. Res. Un. Japan, Sci. Engrs., 12, 73-81.
224. Mathew, T., B. K. Sinha and L. Zhou (1993). Some statistical procedures for combining independent tests. J. Am. Statist. Assoc., 88, 912-919.
225. Mathon, R. and A. Rosa (1996). 2-(v, k, λ) designs of small order. In: The CRC Handbook of Combinatorial Designs, C. J. Colbourn and J. H. Dinitz (eds.). Boca Raton, FL: CRC, pp. 3-41.
226. Matthews, J. N. S. (1987). Optimal crossover designs for the comparison of two treatments in the presence of carryover effects and autocorrelated errors. Biometrika, 74, 311-320.
227. Montgomery, D. C. (1991). Introduction to Statistical Quality Control, 2nd ed. New York: Wiley.
228. Montgomery, D. C. (1999). Experimental design for product and process design and development. Statistician, 48, 159-173.
229. Morgan, J. P. (1996). Nested designs. In: Handbook of Statistics, 13, S. Ghosh and C. R. Rao (eds.). Amsterdam: Elsevier Science, pp. 939-976.
230. Morgan, J. P. and R. A. Bailey (2000). Optimal design with many blocking factors. Ann. Statist., 28, 553-577.
231. Muller, E.-R. (1966). Balanced confounding in factorial experiments. Biometrika, 53, 507-524.
232. Myers, R. H., A. I. Khuri and G. Vining (1992). Response surface alternatives to the Taguchi robust parameter design approach. Am. Statist., 46, 131-139.
233. Nair, K. R. (1944). The recovery of inter-block information in incomplete block designs. Sankhyā, 6, 383-390.
234. Nair, K. R. (1951). Rectangular lattices and partially balanced incomplete block designs. Biometrics, 7, 145-154.
235. Nair, V. N. (1986). Testing in industrial experiments with ordered categorical data. Technometrics, 28, 283-291.
236. Neyman, J., K. Iwaszkiewicz and S. Kolodziejczyk (1935). Statistical problems in agricultural experimentation. Suppl. J. Roy. Statist. Soc., 2, 107-154.
237. Nguyen, N.-K. (1996). An algorithmic approach to constructing supersaturated designs. Technometrics, 38, 69-73.
238. Nguyen, N.-K. and E. R. Williams (1993). An algorithm for constructing optimal resolvable row-column designs. Austral. J. Statist., 35, 363-370.
239. Ogasawara, M. (1965). A necessary condition for the existence of regular and symmetric PBIB designs. Inst. Stat. Mimeo Series 418: Chapel Hill, NC.
240. Ogawa, J. (1974). Statistical Theory of the Analysis of Experimental Designs. New York: Dekker.
241. n factorial experiments. J. Statist. Plann. Inf., 11, 241-245.
242. Paley R. E. A. C. (1933). On orthogonal matrices. J. Math. Phys., 12, 311-320.
243. Paterson, L. J. (1983). Circuits and efficiency in incomplete block designs. Biometrika, 70, 215-225.
244. Patterson, H. D. (1951). Change-over trials. J. Roy. Statist. Soc., B, 13, 256-271.
245. Patterson, H. D. (1952). The construction of balanced designs for experiments involving sequences of treatments. Biometrika, 39, 32-48.
246. Patterson, H. D. and H. L. Lucas (1959). Extra-period change-over designs. Biometrics, 15, 116-132.
247. Patterson, H. D. and H. L. Lucas (1962). Change-over designs. North Carolina Agr. Exp. Station Tech. Bull., 147.
248. Patterson, H. D. and R. Thompson (1971). Recovery of inter-block information when block sizes are unequal. Biometrika, 58, 545-554.
249. Patterson, H. D. and E. R. Williams (1976). A new class of resolvable incomplete block designs. Biometrika, 63, 83-92.
250. Pearce, S. C. (1953). Field experimentation with fruit trees and other perennial plants. Commonwealth Bur. Horticulture Plantation Crops, Tech. Comm., 23.
251. Pearce, S. C. (1960). Supplemented balance. Biometrika, 47, 263-271 (Corrigenda 48, 475).
252. Pearce, S. C. (1963). The use and classification of non-orthogonal designs (with discussion). J. Roy. Statist. Soc., A, 126, 353-377.
253. Pearce, S. C. (1964). Experimenting with blocks of natural size. Biometrics, 20, 699-706.
254. Phadke, M. S. (1982). Quality engineering using design of experiments. ASA Proceedings, Section on Statistical Education, 11-20. Alexandria, VA: American Statistical Association.
255. Plackett, R. L. (1946). Some generalizations in the multifactorial design. Biometrika, 33, 328-332.
256. Plackett, R. L. and J. P. Burman (1946). The design of optimum multifactorial experiments. Biometrika, 33, 305-325.
257. Prvan, T. and D. J. Street (2002). An annotated bibliography of application papers using certain classes of fractional factorial and related designs. J. Statist. Plann. Inf., 106, 245-269.
258. Pukelsheim, F. (1993). Optimal Design of Experiments. New York: Wiley.
259. Quenouille, M. H. (1953). The Design and Analysis of Experiments. London: Griffin.
260. Raghavarao, D. (1960). A generalization of group divisible designs. Ann. Math. Statist., 31, 756-771.
261. Raghavarao, D. (1971). Construction and Combinatorial Problems in Design of Experiments. New York: Wiley.
262. Raghavarao, D. (1986). Random balance designs. In: Encyclopedia of Statistical Science. S. Kotz, N. L. Johnson and C. B. Read (eds.). New York: Wiley, pp. 505-506.
263. Raghavarao, D. (1990). Cross-over designs in industry. In: Statistical Design and Analysis of Industrial Experiments. S. Ghosh (ed.). New York: Dekker, pp. 517-530.
264. Raghavarao, D. and K. Chandrasekhararao (1964). Cubic designs. Ann. Math. Statist., 35, 389-397.
265. Raghavarao, D. and S. K. Thartare (1967). An inequality for doubly balanced incomplete block designs. Calcutta Statist. Assoc. Bull., 16, 37-39.
266. Raghavarao, D. and S. K. Thartare (1970). A new series of doubly balanced designs. Calcutta Statist. Assoc. Bull., 19, 95-96.
267. Raktoe, B. L. (1969). Combining elements from distinct finite fields in mixed factorials. Ann. Math. Statist., 40, 498-504.
268. Raktoe, B. L. (1970). Generalized combining of elements from finite fields. Ann. Math. Statist., 41, 1763-1767.
269. Raktoe, B. L., A. Hedayat and W. T. Federer (1981). Factorial Designs. New York: Wiley.
270. Raktoe, B. L., A. A. Rayner and D. O. Chalton (1978). On construction of confounded mixed factorial and lattice designs. Austral. J. Statist., 20, 209-218.
271. Rao, C. R. (1946a). Hypercubes of strength d leading to confounded designs in factorial experiments. Bull. Calcutta Math. Soc., 38, 67-78.
272. Rao, C. R. (1946b). Difference sets and combinatorial arrangements derivable from finite geometries. Proc. Nat. Inst. Sci. India, 12, 123-135.
273. Rao, C. R. (1947a). General methods of analysis for incomplete block designs. J. Am. Statist. Assoc., 42, 541-561.
274. Rao, C. R. (1947b). Factorial experiments derivable from combinatorial arrangements of arrays. J. Roy. Statist. Soc., B, 9, 128-139.
275. Rao, C. R. (1950). The theory of fractional replication in factorial experiments. Sankhyā, 10, 81-86.
276. Rao, V. R. (1958). A note on balanced designs. Ann. Math. Statist., 29, 290-294.
277. Rashed, D. H. (1984). Designs for multiple comparisons of control versus test treatments. Unpublished Ph.D. dissertation, Virginia Polytechnic Institute and State University, Blacksburg, VA.
278. Ratkowsky, D. A., M. A. Evans and J. R. Alldredge (1993). Cross-over Experiments-Design, Analysis and Application. New York: Dekker.
279. Ray-Chaudhuri, D. K. (1965). Some configurations in finite projective spaces and partially balanced incomplete block designs. Can. J. Math., 17, 114-123.
280. Riedwyl, H. (1998). Modifying and using Yates' algorithm. Statist. Papers, 39, 41-60.
281. Roy, J. and K. R. Shah (1962). Recovery of interblock information. Sankhyā, A, 24, 269-280.
282. Roy, P. M. (1953-1954). Hierarchical group divisible incomplete block designs with m-associate classes. Sci. Culture, 19, 210-211.
283. Russell, K. G., J. A. Eccleston and G. J. Knudsen (1981). Algorithms for the construction of (m, S)-optimal block designs and row-column designs. J. Statist. Comp. Simul., 12, 93-105.
284. SAS Institute (1999-2001). SAS ® Proprietary Software Release 8.2. Cary, NC: SAS Institute.
285. Satterthwaite, F. E. (1946). An approximate distribution of estimates of variance components. Biometrics, 2, 110-114.
286. Satterthwaite, F. E. (1959). Random balance experimentation. Technometrics, 1, 111-137.
287. Seely, J. and D. Birkes (1984). Parametrizations and resolution IV. In: Experimental Design, Statistical Models, and Genetic Statistics. K. Hinkelmann (ed.). New York: Dekker, pp. 77-94.
288. Sen, M. and R. Mukerjee (1987). Optimal repeated measurements designs under interaction. J. Statist. Plann. Inf., 17, 81-91.
289. Senn, S. J. (1993). Cross-over Trials in Clinical Research. Chichester, U.K.: Wiley.
290. Seshradi, V. (1963). Combining unbiased estimators. Biometrics, 19, 163-170.
291. Shah, B. V. (1958). On balancing in factorial experiments. Ann. Math. Statist., 29, 766-779.
292. Shah, B. V. (1959). A generalization of partially balanced incomplete block designs. Ann. Math. Statist., 30, 1041-1050.
293. 2 factorial experiment. Biometrics, 16, 115-118.
294. Shah, K. R. (1964). Use of inter-block information to obtain uniformly better estimators. Ann. Math. Statist., 35, 1064-1078.
295. Shah, K. R. (1970). On the loss of information in combined inter-and intra-block estimation. J. Am. Statist. Assoc., 65, 1562-1564.
296. Shah, K. R. (1977). Analysis of designs with two-way elimination of heterogeneity. J. Statist. Plann. Inf., 1, 207-216.
297. Sharma, V. K. (1977). Change-over designs with complete balance for first and second residual effects. Canadian J. Statist., 5, 121-132.
298. Shing, C.-C. and K. Hinkelmann (1992). Repeated measurement designs for factorial treatments when high order interactions are negligible. J. Statist. Plann. Inf., 31, 81-91.
299. m factorials. J. Statist. Plann. Inf., 27, 65-74.
300. m factorials derived from balanced arrays of strength 2(l + 1) and AD-optimal search designs. J. Statist. Plann. Inf., 11, 247-258.
301. Shirakura, T., T. Takahashi and J. N. Srivastava (1996). Searching probabilities for nonzero effects in search designs for the noisy case. Ann. Statist., 24, 2560-2568.
302. Shrikhande, S. S. (1950). The impossibility of certain symmetrical balanced incomplete block designs. Ann. Math. Statist., 21, 106-111.
303. Shrikhande, S. S. (1952). On the dual of some balanced incomplete block designs. Biometrics, 8, 66-72.
304. Shrikhande, S. S. (1960). Relations between certain incomplete block designs. In: Contributions to Probability and Statistics. I. Olkin (ed.). Stanford, CA: Stanford University Press, pp. 388-395.
305. Shrikhande, S. S. (1965). On a class of partially balanced incomplete block designs. Ann. Math. Statist., 36, 1807-1814.
306. Shrikhande, S. S. and D. Raghavarao (1963). A method of constructing incomplete block designs. Sankhyā, A, 25, 399-402.
307. Sihota, S. S. and K. S. Banerjee (1981). On the algebraic structures in the construction of confounding plans in mixed factorial designs on the lines of White and Hultquist. J. Am. Statist. Assoc., 76, 996-1001.
308. Sitter, R. R., J. Chen and M. Feder (1997). Fractional resolution and minimum aberration in blocking factorial designs. Technometrics, 39, 382-390.
309. m fractional factorial designs. In: S. N. Roy Memorial Volume. Chapel Hill, NC: University of North Carolina and Calcutta: Indian Statistical Institute.
310. Srivastava, J. N. (1975). Designs for searching non-negligible effects. In: A Survey of Statistical Design and Linear Models. J. N. Srivastava (ed.). Amsterdam: North-Holland, pp. 507-519.
311. Srivastava, J. N. (1984). Sensitivity and revealing power: Two fundamental statistical criteria other than optimality arising in discrete experimentation. In: Experimental Design, Statistical Models, and Genetic Statistics. K. Hinkelmann (ed.). New York: Dekker, pp. 95-117.
312. Srivastava, J. N. (1993). Nonadditivity in row-column designs. J. Comb. Inform. System Sci., 18, 85-96.
313. Srivastava, J. N. (1996). A critique of some aspects of experimental design. In: Handbook of Statistics, 13. S. Ghosh and C. R. Rao (eds.). Amsterdam: Elsevier Science, pp. 309-341.
314. Srivastava, J. N. and D. A. Anderson (1970). Some basic properties of multidimensional partially balanced designs. Ann. Math. Statist., 41, 1438-1445.
315. m fractional factorial designs of resolution V, m ≤ 6. Technometrics, 13, 257-269.
316. Srivastava, J. N. and D. V. Chopra (1973). Balanced arrays and orthogonal arrays. In: A Survey of Combinatorial Theory. J. N. Srivastava, F. Harary, C. R. Rao, G.-C. Rota, and S. S. Shrikhande (eds.). Amsterdam: North-Holland, pp. 411-428.
317. m factorial designs of resolution V which allow search and estimation of one extra unknown effect. Sankhyā, B, 38, 280-289.
318. Srivastava, J. N. and S. Ghosh (1977). Balanced 2m factorial designs of resolution V which allow search and estimation of one extra unknown effect, 4 ≤ m ≤ 8. Comm. Statist.-Theor. Meth., 6, 141-166.
319. Srivastava, J. N. and S. Ghosh (1996). On nonorthogonality and nonoptimality of Addelman's main-effect plans satisfying the condition of proportional frequencies. Statist. Prob. Lett., 26, 51-60.
320. m factorials which allow search and estimation of one unknown effect. J. Statist. Plann. Inf., 3, 259-265.
321. Srivastava, J. N. and Y. C. Wang (1998). Row-column designs: How and why nonadditivity may make them unfit for use. J. Statist. Plann. Inf., 73, 277-315.
322. Srivastava, R., V. K. Gupta and A. Dey (1990). Robustness of some designs against missing observations. Comm. Statist., A, 19, 121-126.
323. Street, A. P. and D. J. Street (1987). Combinatorics of Experimental Design. Oxford: Clarendon.
324. Stufken, J. (1987). A-optimal block designs for comparing test treatments with a control. Ann. Statist., 15, 1629-1638.
325. Stufken, J. (1991). On group divisible treatment designs for comparing test treatments with a standard treatment in blocks of size 3. J. Statist. Plann. Inf., 28, 205-211.
326. Stufken, J. (1996). Optimal crossover designs. In: Handbook of Statistics, Vol. 13. S. Ghosh and C. R. Rao (eds.). Amsterdam: Elsevier Science, pp. 63-90.
327. n-p designs. Technometrics, 39, 298-307.
328. Surendran, P. U. (1968). Association matrices and the Kronecker product of designs. Ann. Math. Statist., 39, 676-680.
329. Taguchi, G. (1986). Introduction to Quality Engineering: Designing Quality into Products and Processes. Tokyo: Asian Productivity Organization.
330. Taguchi, G. (1987). System of Experimental Design: Engineering Methods to Optimize Quality and Minimize Costs. White Plains, NY: UNIPUB/Kraus Internation.
331. Taguchi, G. (1993). Taguchi Methods-Design of Experiments. Dearborn, MI: American Supplies Institute.
332. Takeuchi, K. (1962). A table of difference sets generating balanced incomplete block designs. Rev. Intern. Statist. Inst., 30, 361-366.
333. 2 optimality. Canadian J. Statist., 25, 191-201.
334. Tharthare, S. K. (1963). Right angular designs. Ann. Math. Statist., 34, 1057-1067.
335. Tharthare, S. K. (1965). Generalized right angular designs. Ann. Math. Statist., 36, 1051-1062.
336. Thompson, W. A. (1956). A note on the balanced incomplete block designs. Ann. Math. Statist., 27, 842-846.
337. Thompson, W. A., Jr. (1958). A note on PBIB design matrices. Ann. Math. Statist., 29, 919-922.
338. Thompson, W. A. (1962). The problem of negative estimates of variance components. Ann. Math. Statist., 33, 273-289.
339. Tjur, T. (1990). A new upper bound for the efficiency factor of a block design. Austral. J. Statist., 32, 231-237.
340. van der Waerden, B. L. (1966). Algebra. Berlin: Springer.
341. Vartak, M. N. (1955). On an application of Kronecker product of matrices to statistical designs. Ann. Math. Statist., 26, 420-438.
342. Vartak, M. N. (1959). The non-existence of certain PBIB designs. Ann. Math. Statist., 30, 1051-1062.
343. Venables, W. N. and J. A. Eccleston (1993). Randomized search strategies for finding optimal or near-optimal block and row-column designs. Austral J. Statist., 35, 371-382.
344. Vining, G. G. and R. H. Myers (1990). Combining Taguchi and response surface philosophies: A dual response approach. J. Quality Tech., 22, 38-45.
345. Voss, D. T. (1986). On generalizations of the classical method of confounding to asymmetrical factorial experiments. Comm. Statist., A, 15, 1299-1314.
346. Wald, A. (1943). On the efficient design of statistical investigations. Ann. Math. Statist., 14, 134-140.
347. Webb, S. R. (1964). Characterization of non-orthogonal incomplete factorial designs. In: Appendix B of ARL 65-116, Part I. Aerospace Research Laboratories: US. Air Force, Wright-Patterson Air Force Base, Dayton, OH.
348. Webb, S. R. (1968). Saturated sequential factorial designs. Technometrics, 10, 535-550.
349. Webb, S. R. (1971). Small incomplete factorial experiment designs for two-and three-level factors. Technometrics, 13, 243-256 (Correction 15, 951).
350. Westfall, P. H., S. S. Young and D. K. J. Lin (1998). Forward selection error control in the analysis of supersaturated designs. Statist. Sinica, 8, 101-117.
351. Whitaker, D., E. R. Williams and J. A. John (1997). CycDesigN: A Package for the Computer Generation of Experimental Design. Canberra: CSIRO.
352. White, D. and R. A. Hultquist (1965). Construction of confounding plans for mixed factorial designs. Ann. Math. Statist., 36, 1256-1271.
353. Williams, E. J. (1949). Experimental designs balanced for the estimation of residual effects of treatments. Austral. J. Sci. Res., A, 2, 149-168.
354. Williams, E. J. (1950). Experimental designs balanced for pairs of residual effects. Austral. J. Sci. Res., A, 3, 351-363.
355. Williams, E. R. and J. A. John (2000). Updating the average efficiency factor in α-designs. Biometrika, 87, 695-699.
356. Williams, E. R. and M. Talbot (1993). ALPHA+: Experimental Designs for Variety Trials. Design User Manual. Canberra: CSIRO and Edinburgh: SASS.
357. Wolfinger, R. D. and R. D. Tobias (1998). Joint estimation of location, dispersion, and random effects in robust design. Technometrics, 40, 62-71.
358. Wolock, F. W. (1964). Cyclic designs. Unpublished Ph.D. dissertation, Virginia Polytechnic Institute, Blacksburg, VA.
359. Worthley, R. and K. S. Banerjee (1974). A general approach to confounding plans in mixed factorial experiments when the number of a factor is any positive integer. Ann. Statist., 2, 579-585.
360. Wu, C. F. J. (1993). Construction of supersaturated designs through partially aliased interactions. Biometrika, 80, 661-669.
361. Wu, C. F. J. and Y. Chen (1992). A graph-aided method for planning two-level experiments when certain interactions are important. Technometrics, 34, 162-175.
362. Wu, C. F. J. and M. Hamada (2000). Experiments-Planning, Analysis, and Parameter Design Optimization. New York: Wiley.
363. Wu, H. and C. F. J. Wu (2002). Clear two-factor interactions and minimum aberration. Ann. Statist., 30, 1496-1511.
364. Yamada, S., Y. T. Ikebe, H. Hashiguchi and N. Niki (1999). Construction of three-level supersaturated design. J. Statist. Plann. Inf., 81, 183-193.
365. Yamada, S. and D. K. J. Lin (1999). Three-level supersaturated designs. Statist. Probab. Lett., 45, 31-39.
366. Yamada, S. and T. Matsui (2002). Optimality of mixed-level supersaturated design. J. Statist. Plann. Inf., 104, 459-468.
367. Yamamoto, S., Y. Fuji and N. Hamada (1965). Composition of some series of association algebras. J. Sci. Hiroshima Univ., A, 29, 181-215.
368. Yates, F. (1935). Complex experiments. J. Roy. Statist. Soc., B, 2, 181-223.
369. Yates, F. (1936a). Incomplete randomized blocks. Ann. Eugenics, 7, 121-140.
370. Yates, F. (1936b). A new method of arranging variety trial involving a large number of varieties. J. Agri. Sci, 26, 424-455.
371. Yates, F. (1937a). A further note on the arrangement of variety trials: Quasi-Latin squares. Ann. Eugenics, 7, 319-332.
372. Yates, F. (1937b). The design and analysis of factorial experiments. Imp. Bur. Soil Sci. Tech. Comm., 35, 1-95.
373. Yates, F. (1939). The recovery of inter-block information in variety trials arranged in three-dimensional lattices. Ann. Eugenics, 9, 136-156.
374. Yates, F. (1940a). The recovery of inter-block information in balanced incomplete block designs. Ann. Eugenics, 10, 317-325.
375. Yates, F. (1940b). Lattice squares. J. Agric. Sci., 30, 672-687.
376. Youden, W. J. (1937). Use of incomplete block replications in estimating tobacco-mosiac virus. Contr. Boyce Thompson Inst., 9, 41-48.
377. Youden, W. J. (1940). Experimental designs to increase accuracy of greenhouse studies. Contr. Boyce Thompson Inst., 11, 219-228.
378. Youden, W. J., O. Kempthorne, J. W. Tukey, G. E. P. Box and J. S. Hunter (1959). Discussion of "Random balance experimentation" by F. E. Satterthwaite and "The applications of random balance designs" by T. A. Budne. Technometrics, 1, 157-184.
379. Zahn, D. A. (1975). Modifications of revised critical values for the half-normal plot. Technometrics, 17, 189-200.
380. Zelen, M. (1958). The use of group divisible designs for confounded asymmetrical factorial arrangements. Ann. Math. Statist., 29, 22-40.
381. Zhang, R. and D. K. Park (2000). Optimal blocking of two-level fractional factorial designs. J. Statist. Plann. Inf., 91, 107-121.
382. Zhou, L. and T. Mathew (1993). Combining independent tests in linear models. J. Am. Statist. Assoc., 80, 650-655.
383. Zoellner, J. A. and O. Kempthorne (1954). Incomplete block designs with blocks of two plots. Iowa State College Agri. Expt. Stat. Res. Bull., 418.