effects and usefulness of the antibody used for titer scoring. 'AntibodyTiters' visualizes
antibody titers of all or selected patients. This package also produces empty excel files
in a specified format, in which users can fill in experimental data for visualization.
Excel files with toy data can also be produced, so that users can see how it is visualized
before obtaining real data. The data should contain titer scores at pre-vaccination, after-
1st shot, after-2nd shot, and at least one additional sampling point. Patients with
missing values can be included. The first three sampling points will be plotted discretely,
whereas those following the after-2nd shot will be plotted on a continuous time scale

Title: A-Optimal Block Designs for Comparing Test Treatments with
Authors@R: c(person("Baidya Nath", "Mandal", email = "mandal.stat@gmail.com", role = c("aut", "cre")),person("Sukanta", "Dash", role = "aut"),person("Rajender", "Parsad", role = "aut"))
Author: Baidya Nath Mandal [aut, cre], Sukanta Dash [aut], Rajender Parsad [aut]
Maintainer: Baidya Nath Mandal <mandal.stat@gmail.com>
Description: A collection of functions to construct A-optimal block designs for comparing test treatments with one or more control(s). Mainly A-optimal balanced treatment incomplete block designs, weighted A-optimal balanced treatment incomplete block designs, A-optimal group divisible treatment designs and A-optimal balanced bipartite block designs can be constructed using the package. The designs are constructed using algorithms based on linear integer programming. To the best of our knowledge, these facilities to construct A-optimal block designs for comparing test treatments with one or more controls are not available in the existing R packages. For more details on designs for tests versus control(s) comparisons, please see Hedayat, A. S. and Majumdar, D. (1984) <doi:10.1080/00401706.1984.10487989> A-Optimal Incomplete Block Designs for Control-Test Treatment Comparisons, Technometrics, 26, 363-370 and Mandal, B. N. , Gupta, V. K., Parsad, Rajender. (2017) <doi:10.1080/03610926.2015.1071394> Balanced treatment incomplete block designs through integer programming. Communications in Statistics - Theory and Methods 46(8), 3728-3737.