Try this: Lines <- "case var1 var2 var3 var4 1 9 9 13 11 2 15 9 15 13 3 na na 12 9 4 8 6 na na 5 14 10 na na 6 20 15 17 15 "
# replace with DF <- read.table("myfile.dat", header = TRUE, na.strings = "na") DF <- read.table(textConnection(Lines), header = TRUE, na.strings = "na") DF1 <- DF[-1] kor <- cor(DF1, use = "pairwise") kor lm(var1 ~ var2, DF) # a sample regression # mycoef calculates kth coefficient in regression of # ith variable on jth variable mycoef <- function(i, j, k) coef(lm(DF1[c(i, j)]))[k] idx <- 1:ncol(DF1) names(idx) <- names(DF1) intercepts <- outer(idx, idx, Vectorize(mycoef), 1) names(dimnames(intercepts)) <- c("y", "x") intercepts slopes <- outer(idx, idx, Vectorize(mycoef), 2) names(dimnames(slopes)) <- c("y", "x") slopes # another approach to the above # mycoef1 is like mycoef but has only one argument # and outputs all coefs, not just a specified one mycoef1 <- function(idx) coef(lm(DF1[idx])) out <- t(apply(expand.grid(y = idx, x = idx), 1, mycoef1)) colnames(out) <- c("y", "x", "intercept", "slope") out # To perform SQL operations on data frames # see sqldf home page at http://sqldf.googlecode.com # and also ?sqldf for many examples library(sqldf) sqldf("select avg(var1), avg(var2), avg(var3), avg(var4) from DF1") colMeans(DF1, na.rm = TRUE) # same On 8/20/07, Tom Willems <[EMAIL PROTECTED]> wrote: > hello R ussers, > > i have the same problem with my data, > for aal the different variables, i have the same number of cases, but the > are often out of detectionlimits so they produce "na's" . > so the data looks like this: > > case var1 var2 var3 var4 ... > 1 9 9 13 11 > 2 15 9 15 13 > 3 na na 12 9 > 4 8 6 na na > 5 14 10 na na > 6 20 15 17 15 .. > .. > > What i would like to do for data exploration, is to compare each possible > pair of variables, get their correlation coefficient, the intercept and > the slope of regression line. yet for every variable the messurements are > lnked thruogh theyr case. it is the same sample just a diferent test. > > Now i select a subsets of variables out of the original dataset, and use > : > value_x1 = subset(dataset_1,select=lg_value) > value_y1 =subset(dataset_2,select=lg_value) > > Then i to mold an lm model, inorder to get estimates for the slope ans > intercept > model_1 <- lm (value_y1[,1]~ value_x1[,1] ) > > This is what R tell's me: > "Error in model.frame(formula, rownames, > variables, varnames, extras, extranames, : > variable lengths differ (found for > 'value_x1[, 1]')" > > Is there perhapes a way of binding the selected subsets together, still > linked to their case, so that the na's can be discarded by R automaticaly? > I have been trying to use SQLiteDF and the other sql func's of R, but i > don't realy understand them. > If someone out there knows how to use sql, in R, i d be delited if he or > she could explain it to me, more understandible then the manuals i find on > the web. > Here is what io would want sql to do . > > > My data is in columns, one column holds all the case numbers, one the > messured values, one all the testtypes and one the timeperiod and then one > column for the lab's that preformed the test. is is stored in a txt file. > So it is a long 5 column data table. > Now is it possible to make a cross table holding the case nr's, and > timeperiod in 2 column's, and then have a different column for every test? > so if there are 4 tests and 4 lab's, it would give 16 columns. > I've tryed it in access, but it gave me andless loops of repeated values. > and creating new data files is dangerous, 'litle mistakes made while > copying ' or manipultaions made to one file and not to the other'. > . > > kind regards, > Tom > > > > Disclaimer: click here > [[alternative HTML version deleted]] > > ______________________________________________ > R-help@stat.math.ethz.ch 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. > ______________________________________________ R-help@stat.math.ethz.ch 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.