I am trying to model an existing meta-analysis to examine alternative hypotheses (e.g., doing a random-effects analysis), as well as re-sampling techniques. There are over 2,000 subjects, but the data is fairly simple: a binary outcome, success or failure, linked with a score (0-10) on a structured assessment. I have the frequencies of success or failure for each score, nested within each study. I am looking for a easier way to create the dataset rather than keying it in, or using the rep function multiple times.
I would like each row to look something like this: Study_ID, Test_Result[0-10], Outcome[0 or 1] For example, let's say I just had two studies and two test levels (1 or 2): study 1 has 35 successes, and 85 failures for score of "1"; for a score of "2," 46 successes and 83 failures. In study 2, for a score of "1" there are 78 successes, 246 failures; for a score of "2," 45 successes and 96 failures. Using just the frequencies provided, how could I most easily create a data frame with the several hundred lines of data? Thanks in advance, -- View this message in context: http://r.789695.n4.nabble.com/Populate-data-frame-for-meta-analysis-tp4710450.html Sent from the R help mailing list archive at Nabble.com. ______________________________________________ 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.