search for: 9.375

##I want to remove the rows where the row sums are zero and this is as far as I have gotten ffg <- (structure(list(CD = c(0, 0, 0, 0, 3.125, 0, 0, 0, 0, 1.6, 3.125, 0, 0, 6.25, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3.125, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1.6, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1.6, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3.125, 0, 0, 0, 0, 0, 0, 0, 0,

Hi all Consider the classic data below from Darwin on the heights of 15 pairs of zea mays (corn) plants either cross-fertilized or self-fertilized, where the goal is to see if it makes a difference. > head(ZeaMays) pair pot cross self diff 1 1 1 23.500 17.375 6.125 2 2 1 12.000 20.375 -8.375 3 3 1 21.000 20.000 1.000 4 4 2 22.000 20.000 2.000 5 5 2 19.125

I have used lme() on data from a between-within subjects experiment. The correct ANOVA table is known because this is a textbook example (Experimental Design by Roger Kirk Chapter 12: Split-Plot Factorial Design). The lme() F-values differ from the known results. Please help me understand why. d<-read.table("kirkspf2.dat",header=TRUE) for(j in 1:4) d[,j] <- factor(d[,j]) ### Make

Dear R help; I'll preface this by saying that the example I've provided below is pretty long, turgid, and otherwise a deep dive into a series of functions I wrote for a simulation study. It is, however, reproducible and self-contained. I'm trying to do my first simulation study that's quite big, and so I'll say that the output of this simulation as I'd like it to be is

I want to take the first row of each unique ID value from a data frame. For instance > ddTable <- data.frame(Id=c(1,1,2,2),name=c("Paul","Joe","Bob","Larry")) I want a dataset that is Id Name 1 Paul 2 Bob > unique(ddTable) Will give me all 4 rows, and > unique(ddTable$Id) Will give me c(1,2), but not accompanied by the name column.