distribution.systematic(design, statistic, save = "no",
limit, data = read.table(file.choose(new = FALSE)),
starts = file.choose(new = FALSE))"AB", "ABA", "ABAB", "CRD" (completely randomized design), "RBD" (randomized block design), "ATD" (alternating treatments design), or "MBD""A-B", "B-A", and "|A-B|", which stand for the (absolute value of the) difference between csave="yes") or just see it as output in the R console (default: save="no").data argument, a window will pop up to ask in what file the data can be found. This text file containing the data should consist of two columns for single-case phase and alternation designs: the first with the condition labels and the second with the obtained scores.
For multiple-baseline designs it should consist of these two columns for EACH unit. This way, each row represents one measurement occasion. It is important not to label the rows or columns.
For multiple baseline designs, when using the default starts argument, second a window pops up in which is asked in what file the possible start points can be found. In this startpoint file, each row should contain all possibilities for one unit, separated by a tab. The rows and columns should not be labeled.
When choosing to save the randomization distribution to a file, next a window will pop up (for multiple baseline designs this is the third pop-up window, for all other designs it is the second window) to ask where to save it. This location can be an existing file, as well as a new file that can be created by giving a file name and the extension .txt. In this latter case a confirmation is required ("The file does not exist yet. Create the file?").pvalue.systematic to obtain the corresponding p-value for the exhaustive randomization distribution.
observed to calculate the observed test statistic.
distribution.random to generate the nonexhaustive randomization distribution and
pvalue.random to obtain the corresponding p-value.data(ABAB)
distribution.systematic(design = "ABAB", statistic = "AA-BB",
save = "no", limit = 4, data = ABAB)Run the code above in your browser using DataLab