similar to: transposition problem

Hello everybody! I?m working with a dataset from eleven field trails on barley fertilization. I use R 1.6.2 (Windows) It is quite easy to fit aov() objects to the dataset. The call: > (l1t4y.aov <- aov(Yield ~ Trial + Treatment, data=led1t4b)) Results in an object with this anova table: Df Sum Sq Mean Sq F value Pr(>F) Trial 10 121423585 12142358 63.499

I am using R in my undergraduate engineering statistics courses, in which I am currently discussing one-way analysis of variance. Many of the data sets for the exercises or examples give the data in the form on one column per treatment level. To use the aov or lm functions such data should be converted to one column with all the response observations and a companion column with indicators of the

Dear R-Community! The example "oats" in MASS (2nd edition, 10.3, p.309) is calculated for aov and lme without interaction term and the results are the same. But I have problems to reproduce the example aov with interaction in MASS (10.2, p.301) with lme. Here the script: library(MASS) library(nlme) options(contrasts = c("contr.treatment", "contr.poly")) # aov: Y ~

Dear List, I have been using R to create an xyplot using the panel function within lattice libraries. This plot is based on the data supplied in R named 'Oats'. The graph represents oat yield by nitro level with an overlay of each variety of oats for each nitro level. I have three questions regarding this graph: 1) I cannot seem to specify the type of symbol used by the plot, even though

Dear R users, this is a follow up of this message http://tolstoy.newcastle.edu.au/R/e6/help/09/05/13897.html I'm reproducing the core of it for convenience. > // > / data(Oats, package = "MEMSS") / > / tp1.oats <- xyplot(yield ~ nitro | Variety + Block, / > / data = Oats, / > / panel = function(x, y, subscripts, ...) { /

Full_Name: Kevin Wright Version: 1.8.0 OS: Windows 95 Submission from: (NULL) (170.54.59.160) This bug also happens to me using R 1.9.0 on Windows 2000. Took me a long time to create a reproducible bug, but I think I have succeeded. I suspect my test function has a bug, but I don't see anything wrong. Plus, the bug only shows up when selecting certain filenames. Nearest I can speculate,

The following code produces a legend ("key") that mentions the unused levels of Block. library(MEMSS) xyplot(yield~nitro, subset=(Block=="I" | Block=="II"), data=Oats, group=Block, auto.key=T) and adding "drop.unused.levels=T" does not fix it. And in fact even the following does not solve the problem: xyplot(yield~nitro,

Hi, I'm experimenting with using (R)SQLite to do data management. Here are two little problems that I've encountered: 1. The presence of ',' in string values causes trouble since ',' is also the delimiter used in the SQL statement. 2. A newline '\n' line attached to the last string value of each row. Some examples: > library (RSQLite) Loading required

How to show panels for factor levels of conditioning variables which do have no values? E.g. there are panels for "Grand Rapids" when they have values: data( barley ) with( barley, dotplot(variety ~ yield | year * site, layout=c(6,2) ) ) There are no panels for "Grand Rapids" when there are no values for "Grand Rapids": my.barley <- subset( barley, ! ( site ==

Suppose I wanted to plot the barley data like this: dotplot(variety ~ yield | year+ site, barley, strip = strip.custom(style = 4)) The factor levels are far too long for that to be useful. I can overcome that problem if I shorten the levels like this: dotplot(variety ~ yield | year + site, barley, strip = strip.custom(style = 4, factor.levels =

x.fun <- function( formula, data ) dotplot( formula, data ) x.grp <- function( formula, groups, data ) dotplot( formula, groups, data ) data( barley ) > x.fun( variety ~ yield | site, data=barley ) # no problem > dotplot( variety ~ yield | site, groups=year, data=barley ) # no problem > x.grp( variety ~ yield | site, groups=year, data=barley ) object "year" not found

Hi, The following produces almost exactly what I needed. The problems are that the 'panel.dotplot' call (commented) generates the error 'Error in NextMethod("[") : argument "subscripts" is missing, with no default'. The other problem is that the colors alternate between the levels of the 'site' variable, rather than 'year'. barley$yield2

I am trying to do Tukey HSD comparisons on a repeated measures expt. I found the following example on r-help and quoted approvingly elsewhere. It is broken. Can anyone please tell me how to get it to work? I am using R 2.4.1. > require(MASS) ## for oats data set > require(nlme) ## for lme() > require(multcomp) ## for multiple comparison stuff > Aov.mod <- aov(Y ~ N + V +

Dear all, Consider a completely randomized block design (let's use data(Oats) irrespoctive of the split-plot design it was arranged in). Look: library(nlme) fit <- lme(yield ~ nitro, Oats, random = ~1|Block, method="ML") fit2 <- lm(yield ~ nitro + Block, Oats) anova(fit, fit2) gives this: Model df AIC BIC logLik Test L.Ratio p-value fit 1 4 624.3245

How can I add an extra column containing the rank to a ragged array indexed by more than one grouping factors? E.g. with the barley dataset: How can I to add an additional column ``rank'' containing the rank of the ``yield'' of the different varieties in relation to the indices ``year'' and ``site'' to the barley dataframe? I achieved to calculate the ranks with:

Folks at R help, I can't quite get the panel function to work the way I want within barchart. I guess I'm still not understanding how to piece together multiple panel arguments, especially when "groups" is specified. Example: I want to be able to add the value of "yield" to each section of each bar in this graph: barchart(yield ~ variety | site, data = barley,

Dear R-users, i encountered some problems when trying to adjust the line width of the axes and stripes in a plot created with ggplot2. I use the "barley" dataset of the lattice package to illustrate my problem: library(ggplot2) library(lattice) barley[["SD"]] <- 5 limits <- aes(ymax=barley$yield + barley$SD,ymin=barley$yield - barley$SD) p1 <-

When we call a lattice function such as xyplot, to what extent does the "data" designation cause the function to look inside the "data" for variables? In the examples below, the "subset" argument understands that "Variety" is a variable in the data. But the "scales" argument does not understand that "nitro" is a variable in the data.

I've generated a version of the classic dotplot of the barley data with library(lattice) data(barley) trellis.device("postscript", color=TRUE, file="barley2x3.ps") old.settings <- trellis.par.get() trellis.par.set("background", list(col = "white")) lset(list(superpose.symbol=list(pch=c(19, 1, 25, 2, 15, 22, 23),

I use lattice package and 'barchart' to build a chart. I have a problem with setting different x-axes. Some x categories are missing but they are display and I don't want. I use scales = list(y = "free",x="free") but it works only for y-axes. Simple example: package(lattice) barchart(yield ~ variety | site, data = barley, groups = year, layout = c(1,6),