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Hello, I read a book about statistics in psychology. The authors use SPSS. They talk about post hoc tests after ANOVA finds significant effects: - Gabriel's procedure (for equal or slightly different sample sizes) - Hochberg's GT2 (for different sample sizes) - Games-Howell procedure (for populations with unequal variances) I could not find them in R. Do they not exist in R

Hello, I use t.test for normal distributed and wilcox.test for non-normal distributed samples. It is easy to write a function for t.test that calculates the effect size, because all parts of the formula are available from the t.test result: r = sqrt(t*t / (t*t + df)) However, for Wilcoxon tests, the formula for effect sizes is: r = Z / sqrt(N) I wonder how I can calculate the Z-score in R for

Hi, I produce a series of diagrams with R in order to include them in my documents (LaTeX). However, there is a white border around the diagrams. For some that do not have anything written at the very bottom, the white border is relatively large. The rather big space between figure and caption at the final document looks not nice. It would be best not to have any white border. I played with

Hi, I have a data frame named "questions" that I use to get a subset and then a table: failcondonly <- subset(questions, errorreason=="condition") failcondtab <- table(failcondonly$type, failcondonly$qid, exclude=c("ORGA", "skipped")) The failcondtab looks like this: 6 11 12 13 14 15 17 26 30 31 39 41 gave up 0 1 1 1 1 0 0 0 0 8 0

Hello, I have a table (1) of the form q1 q3 q4 q8 q9 A 5 2 0 1 3 B 2 0 2 4 4 I have another table (2): q1 q2 q3 q4 q5 q6 q7 q8 q9 C 10 7 4 2 6 9 3 1 2 I would like to divide the numbers in table (1) by the number of the appropriate column in table (2): q1 q3 q4 q8 q9 A 5/10 2/4 0/2 1/1 3/2 B 2/10 0/4 2/2 4/1 4/2

Hi all: I installed dovecot v1.0 (on Mac OS X) and want to connect to is on localhost via Pine or Alpine, but it fails. Pine's debug mode tells me the following: ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ Debug output of the Pine program (debug=2 debug_imap=4). Version 4.64 (OSX) [...] Terminal type: screen About to open folder "INBOX" inbox is: "INBOX" IMAP

Hi all: I have an example that shows my problem: > test <- data.frame(c("a", "b", "c")) > colnames(test) <- "mm" > sub <- subset(test, mm=="b") > sub$mm [1] b Levels: a b c > levels(sub$mm) [1] "a" "b" "c" How can I reduce the levels to exclusively those which