hello, everyone: I am conducting t test between drug and control for about 50,000 gene using the following syntax (treatment is factor):
result<- lapply(split(data, data$gene),function(x) lm(value~treatment,x) however, the result is a list and i do not know whether more model fitting statistics (like p value of t test) is included in "result" or not. If i print the first element of resut i got the followings: > result[1] $`1007_s_at` Call: lm(formula = logvalue ~ treatment, data = x) Coefficients: (Intercept) treatmentveh 8.9403 0.3232 > summary(result[1]) Length Class Mode 1007_s_at 13 lm list > So my question is whether more fitting statistics (other than coefficient estimation, like p value) are included in the "result". If yes, how can I parse them into a data frame so that i can output those statistics into a .csv file that can be shared with my clients. If not, how can I modify the code so that more stat can be computed and stored? any constructive suggestions are welcome. -- View this message in context: http://r.789695.n4.nabble.com/how-to-parse-out-fitting-statistics-and-write-them-into-a-data-frame-tp2075707p2075707.html Sent from the R help mailing list archive at Nabble.com. ______________________________________________ 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.