Home   >   CSC-OpenAccess Library   >    Manuscript Information
A Method of Constructing Balanced Repeated Measurement Designs for First Order Residual Effects in Information Security
Chen-Chi Shing, Lee-Hur Shing
Pages - 59 - 69     |    Revised - 31-10-2022     |    Published - 01-12-2022
Volume - 16   Issue - 5    |    Publication Date - December 2022  Table of Contents
MORE INFORMATION
KEYWORDS
Balanced Repeated Measurement Design, Changeover Design, Carryover Design, Information Security, Balanced Incomplete Block Design.
ABSTRACT
Very few papers in information security fields discuss repeated measurement designs and analysis. Balanced repeated measurement designs for first order residual effects are used to estimate both treatment and residual effects more precisely.The treatments for these effects can be types of security controls. In this paper we address the need of repeated measurement designs and propose a method of constructing them using both complete and incomplete block designs.This paper attempts to clear up the definition of Balanced repeated measurement designs for first order residual effects designs (called BRM1) first given by Williams and the definition (called BRMP) given by Patterson. Some properties are also discussed how to use them in practice. Further research will be conducted for minimal and optimal repeated measurement designs in the information security field.
Fisher, P. (2019). Does repeated measurement improve income data quality?Oxford Bulletin of Economics and Statistics, 81(5), 989-1011.
Follmann, D. et al. (2020). Assessing durability of vaccine effect following blinded crossover in COVID-19 vaccine efficacy trials. NIH. https://pubmed.ncbi.nlm.nih.gov/33336213.
Gaitán-Rossi, P. et al. (2020). Food insecurity measurement and prevalence estimates during the COVID-19 pandemic in a repeated cross-sectional survey in Mexico. Cambridge University Press, 1-10.
Godzinski, A., Stroinski, A., Piatek, W. and Stroinski, A. (2022). Pattern recognition in games using process mining. International Symposium on Electrical, Electronics and Information Engineering, 42-45.
Hedayat, A. and Afsarinejad, K. (1973). Repeated measurement designs, I. International Symposium on Statistical Design and Linear Models. https://ani.stat.fsu.edu/techreports/M261.pdf.
Hedayat, A. and Afsarinejad, K. (1975). A survey of statistical design and linear models. Repeated Measurement Designs, I, 229 - 242.
Hedayat, A. and Afsarinejad, K. (1978). Repeated measurement designs, II".The Annals of Statistics, 6(3), 619-628.
Hinkelmann, K. and Kempthorne, O. (2014). Design and analysis of experiments: Introduction to experimental design. Wiley.
Ismail, M. et al. (2013).Newframework to detect and prevent denial of service attack in cloudcomputing environment.International Journal of Computer Science and Security, 6(4), 226-237.
Kempthorne, O. (1952). Design and analysis of experiments. Robert E. Krieger, 1952.
Lucas, H. (1957) "Extra-period Latin square change-over designs", Journal of Dairy science, 40, pp. 225-239.
Manrai, A. and Mandl, K. (2020) Escaping the COVID-19 testing paradox. SSRN. https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3612991.
McKay, H. and Wanless, I. (2005). On the number of Latin squares. Annals of Combinatorics, 9, 335-344.
McKay, H., McLeod, J. and Wanless, I. (2006). The number of transversals in a Latin square. Des Codes Crypt.
Patterson, H. (1950). The analysis of change-over trials. Journal of Agricultural Science, 40, 375-380.
Patterson, H. (1951). Change-over trials. Journal of the Statistical Society, B(13), 256-271.
Patterson, H. (1952). The construction of balanced designs for experiments involving sequences of treatments. Biometrika, 39, 32-48.
Patterson, H. and Lucas, H. (1950). Extra-period change-over designs. Biometrics, 15(1), 116-132.
Ren, M. et al. (2021). Contribution of temperature increase to restrain the transmission of COVID-19. Innovation, 2(1), 1-8.
Rosen, K. (2019). Discrete mathematics and its applications, McGraw-Hill.
Shing, M. et al. (2012). Analysis of n category privacy models. International Journal of Computer Science and Security, 6(5), 342-358.
Stufken, J. (1991). Some families of optimal and efficient repeated measurements designs. Journal of Statistical Planning and Inference, 27(1), 75-83.
Tippey, K., Ritchey, P. and Ferris, T. (2015). Crossover-repeated measures designs: Clarifying common misconceptions for a valuable human factors statistical technique. Proceedings of the Human Factors and ergonomics Society Annual Meeting, 59(1), 342-346.
Williams, E. (1949). Experimental designs balanced for the estimation of residual effects of treatments. Australian Journal of Science Research, A(2), 149-168.
Williams, E. (1950). Experimental designs balanced for pairs of residual effects. Australian Journal of Science Research, A(3), 351-363.
Yasin, A. and Nasra, I. (2016).Dynamicmulti levels Java code obfuscation technique. International Journal of Computer Science and Security, 10(4), 140-160.
Zhao, J., et al. (2019). Reporting and analysis of repeated measurements in preclinical animals experiments. PLOS ONE, 14(8). https://doi.org/10.1371/journal.pone.0220879.
Dr. Chen-Chi Shing
School of Computer Science and Information Systems, Radford University, Radford, VA 24142 - United States of America
cshing@radford.edu
Miss Lee-Hur Shing
Library Department, Virginia Tech, Blacksburg, VA 24061 - United States of America


CREATE AUTHOR ACCOUNT
 
LAUNCH YOUR SPECIAL ISSUE
View all special issues >>
 
PUBLICATION VIDEOS