Publications

GOOGLE SCHOLAR

John Stufken: https://scholar.google.com/citations?user=qrWcLn8AAAAJ&hl=en 

Books

1. Dean, A.M., Morris, M.D., Stufken, J., Bingham, D. (Eds., 2015). Handbook of Design and Analysis of Experiments. Handbooks of Modern Statistical Methods, Chapman & Hall / CRC, Boca Raton, FL.

2. Hedayat, A.S., Sloane, N.J.A., and Stufken, J. (1999). Orthogonal Arrays: Theory and Applications. Springer Series in Statistics, Springer Verlag, New York.

Refereed Publications

1. Liu, Y., Stufken, J., and Yang, M. (2024). Information-based Optimal Subdata Selection for Clusterwise Linear Regression. Statistica Sinica, to appear https://www3.stat.sinica.edu.tw/ss_newpaper/SS-2023-0302_na.pdf 

2. Singh, R. and Stufken, J. (2024). Factor selection in screening experiments by aggregation over random models. Computational Statistics & Data Analysis, to appear. https://doi.org/10.1016/j.csda.2024.107940 

3. Shi, Y., Yu, W., and Stufken. J. (2023). Optimal Design for Generalized Linear Mixed Models Based on the Penalized Quasi-Likelihood Method. Statistics and Computing, 33, article 114. https://doi.org/10.1007/s11222-023-10279-3 

4. Akhtar, Y., Zhang, F., Colbourn, C.J., Stufken, J., and Syrotiuk, V.R. (2023). Scalable level-wise screening experiments using Locating Arrays. Journal of Quality Technology, 55:5, 584-597. https://doi.org/10.1080/00224065.2023.2220973 

5. Singh, R. and Stufken, J. (2023). Subdata selection with a large number of variables. New England Journal of Statistics in Data Science, Volume 1, Issue 3, pp. 426–438. https://doi.org/10.51387/23-NEJSDS36 

6. Singh, R. and Stufken, J. (2023). Selection of two-level supersaturated designs for main effects models. Technometrics 65, 96-104. https://doi.org/10.1080/00401706.2022.2102080 

7. Wang, Z. and Stufken, J. (2022). Locally D-optimal designs for binary responses and multiple continuous design variables. Journal of Quantitative Economics 20, Supplement Issue 1, 101-113. (Special invited issue in honor of professor C.R. Rao.) https://doi.org/10.1007/s40953-022-00304-z 

8. Wang, Z and Stufken, J. (2021). Orthogonal Array Based Locally D-optimal Designs for Binary Responses in the Presence of Factorial Effects. Journal of Statistical Theory and Practice, 15, article 87. (Special invited issue on "State of the art in research on design and analysis of experiments".) https://doi.org/10.1007/s42519-021-00224-w 

9. Chai, F.-S., Singh, R. and Stufken, J. (2021). Connected row-column L-designs for symmetrical parallel line assays with two preparations. Journal of Statistical Theory and Practice, 15, article 89. (Special invited issue on "State of the art in research on design and analysis of experiments".)  https://doi.org/10.1007/s42519-021-00219-7 

10. Singh, R., Kunert, J. and Stufken, J. (2021). On optimal fMRI designs for correlated errors. Journal of Statistical Planning and Inference 212, 84-96. https://doi.org/10.1016/j.jspi.2020.08.003 

11. Singh, R. and Stufken, J. (2021). Efficient orthogonal fMRI designs in the presence of drift. Statistical Methods in Medical Research, 30, 277-285. https://doi.org/10.1177/0962280220953870 

12. Fang, G., Pan, R. and Stufken, J. (2021). Optimal Test Conditions Setting and Test Units Allocation for Accelerated Degradation Tests with Two Stress Variables. IEEE Transactions on Reliability, 70, 1096-1111. https://doi.org/10.1109/TR.2020.2995333 

13. Chai, F.-S., Das, A., Singh, R. and Stufken, J. (2020). Discriminating between superior UE(s^2)-optimal supersaturated designs. Statistics and Applications 20, 67-74 (special issue in honor of Bikas and Bimal Sinha). https://www.ssca.org.in/media/6_Vol._18_No._2_2020_Stufken.pdf 

14. Wang, Z. and Stufken, J. (2020). Locally D-optimal Designs for Binary Responses in the Presence of Factorial Effects. Journal of Statistical Theory and Practice 14, article 19. https://doi.org/10.1007/s42519-020-0085-0 

15. Chai, F.-S., Singh, R. and Stufken, J. (2019). Nearly magic rectangles. Journal of Combinatorial Designs 27, 562-567. https://doi.org/10.1002/jcd.21667  

16. Eshima, J., Ong, S., Davis, T.J., Miranda, C., Krishnamurthy, D., Nachtsheim, A., Plaisier, C., Stufken, J., Fricks, J., Bean, H.D. and Smith, B.S. (2019). Monitoring changes in the healthy female metabolome across the menstrual cycle using GCxGC-TOFMS. Journal of Chromatography B Analyt Technol Biomed Life Sci. 1121, 48-57. https://doi.org/10.1016/j.jchromb.2019.04.046 

17. Nachtsheim, A.C. and Stufken, J. (2019). Discussion on the paper: Data Science, Big Data and Statistics, by Pedro Galeano and Daniel Peña. Invited discussion, TEST 28, 345-348. https://doi.org/10.1007/s11749-019-00643-9 

18. Wang, H., Yang, M. and Stufken, J. (2019). Information-Based Optimal Subdata Selection for Big Data Linear Regression. Journal of the American Statistical Association 114, 393-405. https://doi.org/10.1080/01621459.2017.1408468 

19. Zhang, W., Mandal, A. and Stufken, J. (2017). Approximations of the Information Matrix for a Panel Mixed Logit Model. Journal of Statistical Theory and Practice 11, 269-295. https://doi.org/10.1080/15598608.2016.1219288 

20. Martin, R., Stufken, J. and Yang, M. (2016). A Conversation with Samad Hedayat. Statistical Science 31, 637-647. https://doi.org/10.1214/16-STS579 

21. Bludowsky, A., Kunert, J. and Stufken, J. (2015). Optimal designs for the carryover model with random interactions between subjects and treatments. Australian & New Zealand Journal of Statistics 57, 517-533. https://doi.org/10.1111/anzs.12136 

22. Hu, L., Yang, M. and Stufken, J. (2015). Saturated locally optimal designs under differentiable optimality criteria. Annals of Statistics 43, 30-56. https://doi.org/10.1214/14-AOS1263 

23. Kao, M.-H. and Stufken, J. (2015). Optimal design for event-related fMRI studies. In: Handbook of Design and Analysis of Experiments, A.M. Dean, M.D. Morris, J. Stufken and D. Bingham, eds., 895-924. Chapman & Hall / CRC.

24. Wu, H.-P. and Stufken, J. (2014). Locally φp-optimal designs for generalized linear models with a single-variable quadratic polynomial predictor. Biometrika 101, 365-375.

25. Kao, M.-H., Majumdar, D., Mandal, A., Stufken, J. (2013). Maximin and maximin-efficient event-related fMRI designs under a nonlinear model. Annals of Applied Statistics 7, 1940-1959.

26. Yang, M. and Stufken, J. (2012). Identifying locally optimal designs for nonlinear models: A simple extension with profound consequences. Annals of Statistics 40, 1665-1681.

27. Kao, M.-H., Mandal, A. and Stufken, J. (2012). Constrained Multi-objective Designs for Functional MRI Experiments via A Modied Nondominated Sorting Genetic Algorithm. Journal of the Royal Statistical Society, Series C (Applied Statistics) 61, 515-534.

28. Stufken, J. and Yang, M. (2012). On locally optimal designs for generalized linear models with group effects. Statistica Sinica 22, 1765-1786.

29. Stufken, J. and Taylor, R.L. (2012). A Brief History of the Department of Statistics at the University of Georgia. In: Strength in Numbers: The Rising of Academic Statistics Departments in the U.S., Alan Agresti and Xiao-Li Meng, eds., 381-394. Springer.

30. Stufken, J. and Yang, M. (2012). Optimal designs for generalized linear models. In: Design and Analysis of Experiments, Volume 3, Special Designs and Applications, K. Hinkelmann, ed., pp. 137-164. Wiley, New Jersey.

31. Wright, James H. and Stufken, J. (2011). Variance approximation under balanced sampling plans excluding adjacent units. Journal of Statistical Theory and Practice 5, 147-160.

32. Ozan, O. and Stufken, J. (2010). Assessing the Impact of Carryover Effects on the Variances of Estimators of Treatment Differences in Crossover Designs. Statistics in Medicine 29, 2480-2485.

33. Kao, M.-H., Mandal, A. and Stufken, J. (2009). Efficient Designs for Event-Related Functional Magnetic Resonance Imaging with Multiple Scanning Sessions. Communication in Statistics - Theory and Methods 38, 3170-3182. (Invited for special issue in honor of Shelley Zacks).

34. Kao, M.-H., Mandal, A., Lazar, N., and Stufken, J. (2009). Multi-objective Optimal Experimental Designs for Event-Related fMRI Studies. NeuroImage 44, 849-856.

35. Yang, M. and Stufken, J. (2009). Support points of locally optimal designs for nonlinear models with two parameters. Annals of Statistics 37, 518-541.

36. Kao, M.-H., Mandal, A. and Stufken, J. (2008). Optimal Design for Event-related Functional Magnetic Resonance Imaging Considering Both Individual Stimulus Effects and Pairwise Contrasts. Statistics and Applications 6, 235-256. (Invited for special issue in honor of Aloke Dey).

37. Kunert, J. and Stufken, J. (2008). Optimal crossover designs for two treatments in the presence of mixed and self carryover effects. Journal of the American Statistical Association 103, 1641-1647.

38. Majumdar, D. and Stufken, J. (2008). Optimal Designs for Mixed Models in Experiments Based On Ordered Units. Annals of Statistics 36, 1090-1107.

39. Wright, James H. and Stufken, J. (2008). New Balanced Sampling Plans Excluding Adjacent Units. Journal of Statistical Planning and Inference 138, 3326-3335.

40. Yang, M. and Stufken, J. (2008). Optimal and efficient crossover designs for comparing test treatments to a control treatment under various models. Journal of Statistical Planning and Inference 138, 278-285.

41. Bose, M. and Stufken, J. (2007). Optimal crossover designs when carryover effects are proportional to direct effects. Journal of Statistical Planning and Inference 137, 3291-3302.

42. Stufken, J. and Tang, B. (2007). Complete enumeration of two-level orthogonal arrays of strength d with d + 2 constraints. Annals of Statistics 35, 793-814.

43. Hedayat, A, Stufken, J. and Yang, M. (2006). Optimal and efficient crossover designs when subject effects are random. Journal of the American Statistical Association 101, 1031-1038.

44. Hedayat, A.S. and Stufken, J. (2003). Optimal and efficient crossover designs under different assumptions for the carryover effects. Journal of Biopharmaceutical Statistics 13, 519-528.

45. Kunert, J. and Stufken, J. (2002). Optimal crossover designs in a model with self and mixed carryover effects. Journal of the American Statistical Association 97, 898-906.

46. Lin, W.-C. and Stufken, J. (2002). Strongly linear trend-free designs and 1-factors of representative graphs. Journal of Statistical Planning and Inference 106, 375-386.

47. Rains, E.M., Sloane, N.J.A. and Stufken, J. (2002). The lattice of N-run orthogonal arrays. Journal of Statistical Planning and Inference 102, 477-500.

48. Stufken, J. and Wright, J.H. (2001). Polygonal designs with blocks of size k ≤ 10. Metrika 54, 179-184.

49. Hedayat, A.S. and Stufken, J. (2001). Compound orthogonal arrays and dispersion effects. In: Recent Advances in Experimental Designs and Related Topics , S. Altan and J. Singh, eds., pp. 119-132. Nova Science Publishers, Huntington, NY.

50. De Cock, D. and Stufken, J. (2000). On finding mixed orthogonal arrays of strength 2 with many 2-level factors. Statistics and Probability Letters 50, 383-388.

51. See, K., Stufken, J., Song, S.Y. and Bailer, A.J. (2000). Relative efficiencies of sampling plans for selecting a small number of units from a rectangular region. Journal of Statistical Computation and Simulation 66, 273-294.

52. Chai, F.-S. and Stufken, J. (1999). Trend-free block designs for higher order trends. Utilitas Mathematica 56, 65-78.

53. Lin, W.-C. and Stufken, J. (1999). On finding trend-free block designs. Journal of Statistical Planning and Inference 78, 57-70.

54. Stufken, J., Song, S.Y., See, K. and Driessel, K.R. (1999). Polygonal designs: Some existence and non-existence results. Journal of Statistical Planning and Inference 77, 155-166.

55. Hedayat, A.S. and Stufken, J. (1999). Compound orthogonal arrays. Technometrics 41, 57-61.

56. Lin, W.-C. and Stufken, J. (1998). Varietal trials in the presence of trends. Journal of Combinatorics, Information and System Sciences 23, 295-316. (Felicitation volume dedicated to Professor J.N. Srivastava.)

57. Hedayat, A., and Stufken, J. (1998). Sampling designs to control selection probabilities of contiguous units. Journal of Statistical Planning and Inference 72, 333-345.

58. Hedayat, A., Stufken, J., and Su, G. (1997). On the construction and existence of orthogonal arrays with 3 levels and indexes 1 and 2. Annals of Statistics 25, 2044-2053.

59. See K., Song, S.Y., and Stufken, J. (1997). On a class of partially balanced incomplete block designs with applications in survey sampling. Communications in Statistics 26, 1-13.

60. Hedayat, A., Seiden, E., and Stufken, J. (1997). On the maximal number of factors and the enumeration of 3-symbol orthogonal arrays of strength 3 and index 2. Journal of Statistical Planning and Inference 58, 43-63. (Special issue in honor of Paul Erdős.)

61. Sloane, N.J.A., and Stufken, J. (1996). A linear programming bound for orthogonal arrays with mixed levels. Journal of Statistical Planning and Inference 56, 295-305.

62. Hedayat, A.S., Stufken, J. and Su, G. (1996). On difference schemes and orthogonal arrays of strength t. Journal of Statistical Planning and Inference 56, 307-324.

63. Stufken, J. (1996). Optimal crossover designs. In: Handbook of Statistics 13: Design and Analysis of Experiments , S. Ghosh and C.R. Rao, eds., pp. 63-90. North-Holland, Amsterdam.

64. Hedayat, A., Stufken, J., and Zhang, W. G. (1995). Virtually balanced incomplete block designs for v = 22, k = 8, and λ = 4. Journal of Combinatorial Designs 3, 195-201.

65. Hedayat, A., Stufken, J., and Zhang, W. G. (1995). Contingently and virtually balanced incomplete block designs. Statistica Sinica 5, 575-591. (Invited contribution to special section on optimal design of experiments.)

66. Kim, K., and Stufken, J. (1995). On optimal block designs for comparing a standard treatment to test treatments. Utilitas Mathematica 47, 211-224.

67. Stufken, J. (1993). Combinatorial and statistical aspects of sampling plans to avoid the selection of adjacent units. Journal of Combinatorics, Information and System Sciences 18, 81-92. (Special issue in honor of C. R. Rao).

68. Stufken, J., and Wang, K.-J. (1992). Factorial designs and the theory of trade-off. Statistics and Probability Letters 15, 369-372.

69. Stufken, J., and Kim, K. (1992). Optimal group divisible treatment designs for comparing a standard treatment with test treatments. Utilitas Mathematica 41, 211-227.

70. Hedayat, A., Pu, K., and Stufken, J. (1992). On the construction of asymmetrical orthogonal arrays. Annals of Statistics 20, 2142-2152.

71. Stufken, J. (1992). On hierarchical partitioning. Letter to the Editor, The American Statistician 46, 70-71.

72. Hedayat, A., and Stufken, J. (1992). Some mathematical results on incomplete orthogonal arrays. Sankhya Special Volume 54, 197-202. (Special Volume of Sankhya in memory of R. C. Bose).

73. Stufken, J. (1991). Bayes A-optimal and efficient block designs for comparing test treatments with a standard treatment. Communications in Statistics - Theory and Methods 20, 3849-3862.

74. Stufken, J. (1991). On group divisible treatment designs for comparing test treatments with a standard treatment in blocks of size 3. Journal of Statistical Planning and Inference 28, 205-221.

75. Stufken, J. (1991). Some families of optimal and highly efficient repeated measurements designs. Journal of Statistical Planning and Inference 27, 75-83.

76. Hedayat, A., Lin, B. Y., and Stufken, J. (1989). The construction of ΠPS sampling designs through a method of emptying boxes. Annals of Statistics 17, 1886-1905.

77. Hedayat, A., and Stufken, J. (1989). A relation between pairwise balanced and variance balanced block designs. Journal of the American Statistical Association 84, 753-755.

78. Hedayat, A., Stufken, J., and Landgev, I. N. (1989). The possible support sizes for BIB designs with v = 8 and k = 4. Journal of Combinatorial Theory, Series A 51, 258-267.

79. Hedayat, A., and Stufken, J. (1989). On the maximum number of constraints in orthogonal arrays. Annals of Statistics 17, 448-451.

80. Stufken, J. (1988). On the existence of linear trend-free block designs. Communications in Statistics - Theory and Methods 17, 3857-3863.

81. Stufken, J. (1988). On bounds for the efficiency of block designs for comparing test treatments with a control. Journal of Statistical Planning and Inference 19, 361-372.

82. Hedayat, A., Rao, C. R., and Stufken, J. (1988). Sampling plans excluding contiguous units. Journal of Statistical Planning and Inference 19, 159-170.

83. Cheng, C.-S., Majumdar, D., Stufken, J., and Ture, T. E. (1988). Optimal step type designs for comparing test treatments with a control. Journal of the American Statistical Association 83, 477-482.

84. Stufken, J. (1987). A-optimal block designs for comparing test treatments with a control. Annals of Statistics 15, 1629-1638.

Non-Refereed Publications

1. Stufken, J. (2020). Standing on the shoulders of a giant: The life and work of Samad Hedayat. Journal of Statistical Theory and Practice, 14 article 32.

2. Stufken, J. (2009). An Invitation: Editor's Introduction to "Desired and Feared-What Do We Do Now and Over the Next 50 Years?". The American Statistician 63 (3), 201.

3. Hedayat, S. and Stufken, J. (2009). Comment on "What is Statistics?". The American Statistician 63 (2), 115-116.

4. Stufken, J. (2007). Samad Hedayat: A Friend and Mentor. In the April 21 issue of the Daily Newsletter of the Conference on Algebraic Graph Theory, IPM, Tehran, Iran, April 21-27, 2007.

5. Stufken, J. (2005). Comment on "The Impact of Technology on the Scientific Method" by S. Keller-McNulty, A.G. Wilson, and G. Wilson. Chance 18 (4), 16.

6. Groeneveld, R. A. and Stufken, J. (2002). Solution of "A careless walk toward zero". The American Mathematical Monthly 109, 855-856.

7. Hedayat, A.S. and Stufken, J. (2002). Optimal and efficient crossover designs for a model with self and mixed carryover effects. In: ASA Proceedings of the 2001 JSM. 

8. Stufken, J. (2000). Book Review of "Design and Analysis of Experiments", by Angela Dean and Daniel Voss. Journal of the American Statistical Association 95, 679.

9. Stufken, J. (1994). Book Review of "Taguchi Methods: A hands-on approach", by G. S. Peace. Technometrics 36, 121-122.

10. Stufken, J. (1990). Contribution to the discussion of "The non-orthogonal design of experiments" by R. Mead. Journal of the Royal Statistical Society A 153, 195.

11. Hedayat, A., and Stufken, J. (1989). On the maximum number of factors in two construction methods for orthogonal arrays. In: Statistical Data Analysis and Inference (Proceedings of a conference in honor of C. R. Rao, Neuchâtel, Switzerland, August 21-24, 1989), Y. Dodge, ed., pp. 33-40. North-Holland, Amsterdam. 

12. Stufken, J. (1988). Book Review of "Optimal paired comparison designs for factorial experiments", by E. E. M. van Berkum. Journal of the American Statistical Association 83, 909.

13. Hedayat, A., and Stufken, J. (1988). Two-symbol orthogonal arrays. In: Optimal Design and Analysis of Experiments (Proceedings of the First International Conference-Workshop on Optimal Design and Analysis of Experiments, Neuchâtel, Switzerland, July 25-28, 1988), Y. Dodge, V. V. Fedorov, and H. P. Wynn, eds., pp. 47-58. North-Holland, Amsterdam.

14. Hedayat, A., Rao, C.R., and Stufken, J. (1988). Designs for survey sampling avoiding contiguous units. In: Handbook of Statistics 6: Sampling , P. R. Krishnaiah and C. R. Rao, eds., pp. 575-583. North-Holland, Amsterdam.

15. Hedayat, A., and Stufken, J. (1986). Fractional factorial designs in the form of incomplete orthogonal arrays. In: Statistical Designs: Theory and Practice (Proceedings of a conference in honor of Walter T. Federer), Charles E. McCullogh, Steven J. Schwager, George Casella, and Shayle R. Searle, eds., pp. 101-115. Cornell University Press, Ithaca, N.Y.