similar to: bug with subset and plot?

There is a difference in the p- value from 0.000 and 0.012 when I am using SPSS. 0.000 when I am using the independent variable as scaled 0.012 if I am using the variable as ordinal. The independent variable is ordinal but it seems that R is using the variable as an scaled, because the P- Value is computed with 4.66e-06 so I am not sure which description I am misunderstanding: SPSS;:

I'm using the excellent --link-dest option on rsync to do every-day full backups of a number of servers. These servers share most of the file-system content, but of course has some variations. In order to reduce the space used for each backup, I was thinking about linking all files in the backups to their hash in a separate directory, allowing only one storage of each file-value, reducing

I've used Anova() from the car package to get marginal (aka type II) sum-of-squares and tests for linear models with categorical variables. Is it possible to get marginal SSs also for continuous variables, when the model includes powers of the continuous variables? For instance, if A and B are categorical ("factor"s) and x is continuous ("numeric"), Anova (lm (y ~ A*B +

Hi! I'm doing: etni <- subset(etni, NAMECOM!="Maniquisito") where etni is a data.frame, NAMECOM a factor and "Maniquisito" labels a row that I want to delete. The problem is that while the row is deleted, the factor level is still there (I can see "Maniquisito" if I do levels(etni$NAMECOM) ). I know I can get the appropriate levels by:

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I find that after subsetting (you may prefer "conditional selection") a data frame and assigning it to a new object, the str(new object) reflects the original data frame, not the new one: A <- rnorm(20) B <- factor(rep(c("t", "g"), 10)) C <- factor(rep(c("h", "l"), 10)) D <- data.frame(A, B, C) str(D) # reports correctly E <-

Hi all, I am struggling to work out how to use the rownames from an edited dataframe rather than the row names from the original dataframe. In my data set i'm trying to extract several rows of data on particular individuals, i don't doubt i'm using the long way round but what i have in the way of a script is this: ##selecting the IDs from the dataframe individually

Dear list, subset has a 'drop' argument that I had often mistaken for the one in [.factor which removes unused levels. Clearly it doesn't work that way, as shown below, d <- data.frame(x = factor(letters[1:15]), y = factor(LETTERS[1:3])) s <- subset(d, y=="A", drop=TRUE) str(s) 'data.frame': 5 obs. of 2 variables: $ x: Factor w/ 15 levels

Hello, I?m using zero-inflated Poisson regression via the zeroinfl() function to analyze data on seed-set of plants, but for some reason, I don?t seem to be getting the output for all three levels of my two categorical predictors. More about my data and model: My response variable is the number of viable seeds (AVInt), and my two categorical predictors are elevation (Elev) and Treatment

Hello, I've tried to analyze some data with a CMH test. My 3 dimensional contingency tables are 2x2xN where N is usually between 10 and 100. The problem is that there may be 2 strata with opposite counts (the 2x2 contigency table for these are reversed), producing opposite odds ratios that cancle out in the overall statistics. These opposite counts are very important for my analysis, since

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

Hello, I'm just getting in to R, been reading manuals (thanks to all who provided pointers to good docs!), and messing with different commands. I'd appreciate a little help with this exploration, and I hope that my question is relatively easy to answer (probably, there's a simple way to do what I'm working toward). R's statistical functions are coming along easily enough,

Hello, I'd like to ask, how to adjust the space between symbol/line and text in a legend. My legend() is build like that legend(xmax-netzdiff/11, # shouldn't matter here ifelse(ydiff>=0, # ymin-6.5*(netzdiff/11), # ymax-netzdiff/11), # c("stehender Stamm","Windwurf",

Hi, I use ks.test or lillie.test to verify a normal distribution. It's performed for a group My users use SigmaStat software and a One Way ANOVA on several groups In the result page there is a probability value to determine if Normality test is failed or passed So, how can i retrieve this probability value on several groups? Is there another function in R to verify normality on several

Hi R helpers! I have used a glht as a post-hoc test on an lmer with: -2 treatments (A & B) -1 categorical explanatory variable (song type) -1 response variable (latency to respond) I wanted to make comparisons between the categorical variables depending on treatment. At the moment the glht simply returns comparisons of each of the (3) categorical explanatory variables with each other

Hi to all I need a string like temp <- paste("m1","m2","m3",sep=",") But i must know how many items are in the string,afterwards the other option would be to use a vector temp <- c("m1","m2","m3") No problem to get the count of items but I must get afterwards the string "m1,m2,m3" No problem to build the

Hi to all, test <- data.frame("X"=c(1:4),"Y"=c(5:8),"Z"=c(8:11)) test <- test[,-2] Is there a way to specify the col name "Y" to delete instead the number? Kind regards Knut

Is there any function to show the points like this example of SPSS? http://biostatistic.de/temp/reg.jpg The point size should represent the number of data at this point. with regards Knut Krueger

Hi to all, does anybody knows whether there is a package to plot those http://www.equine-science.de/temp/graph.jpg graphs. the thickness of the points and/or the lines should be represent the numbers of behaviours With kind regards Knut

. I am looking for a histogram or box plot with the adding normal distribution curve I think that must be possible, but I am not able to find out how to do. Regards Knut