A graph != A table. I'm talking about a page full of summary statistics and advanced statistics, with lots of cross categories on the top and left margin of the table, as opposed to a visual display with x-axis and y-axis, which is totally different.
(An example of how this is done in another language is available at http://fivetimesfaster.blogspot.com ) For an AE table, you have an N and % column for every treatment group, and for all patients combined. On the right side, a categorical p-value (chi-sq or Fisher's) for every preferred term (every row! forget multiple testing issues, this is what the boss is asking for(it's ad-hoc safety analysis)) There's a row for grand total N for each group. A row for N and % of patients with any event (regardless of body system and preferred term) For each body system, there's a section of rows that include: A row for N and % of patients with any event (this body system) A row for N and % of patients who do NOT have an event( this body system) And , of course, within body system, a row for each preferred term (again N and % for each group , and also the p-value) Body system and preferred term are, of course broad medical category and specific medical category. In the Pharma industry, they use the SAS programming language. Each table often needs several hundred lines of code. Essentially it's a combination of analysis and (visual)-reporting mixed together, with some prerequisite data transformation. (And yes, with this new language, it can be done in under 20 lines of code). I have not seen people discuss attempts to do such things with the R programming language, and how successful such attempts have been. How hard is it, how much code is it? In general, we are talking about a variety of complex, somewhat-nonhomogeneous statistical tables with a variety of different row sections and row categories, and different column sections and column categories, and a mixture of summary statistics and advanced statistics (p-value , least square mean, etc), and sometimes statistics from different statistical procedures on the same page. Robert Wilkins ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
