This isn't an R code question and you posted in HTML, but briefly: Simulate data that could arise from your study, including missing and outliers, then write code that runs th analyses. Put the code in an open-science archive.
Then run it as is when you actually have the data. There will probably be some hiccups depending on how good your simulation is, but that's the in-principle solution. On Mon, May 11, 2020 at 11:10 AM karl adenener <adene...@hotmail.com> wrote: > > It would be a dream, there would be a R-based software, which I configure > according to my study (type of data, limits for meaningful measurements, > handling of outliers and missing measurements, test method etc.), which then > reads my original measurement data and after some computing time the software > provides me with the statistical analysis. All steps of the evaluation have > to be defined before the start of the study and cannot be changed after the > start of the study. > > Where could problems arise? > Does anyone know of a suitable R-Package or software? > Does anyone have the time and inclination to create a flexibly customizable > package? > > greetings > Adenener > > [[alternative HTML version deleted]] > > ______________________________________________ > R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see > 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. -- Patrick S. Malone, Ph.D., Malone Quantitative NEW Service Models: http://malonequantitative.com He/Him/His ______________________________________________ R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see 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.
