similar to: tree structure in rails?

Dear R-ers, In my question there are no statistics involved - it's all about data manipulation in R. I am trying to write a code that should replace what's currently being done in SAS and SPSS. Or, at least, I am trying to show to my colleagues R is not much worse than SAS/SPSS for the task at hand. I've written a code that works but it's too slow. Probably because it's

Hello. I know how to make a bar plot in which a numeric y variable is plotted against some grouping variable X (say, groups A, B, C) when this grouping variable is subdivided into each of two subgroups; so the bars would be: (group A subgroup 1) beside (group A subgroup 2), then (group B subgroup 1) beside (group B subgroup 2), and so on. This is done using the beside=TRUE argument in the

Ruby''s simple_format method is not working for spaces. so how to add and what to add in simple format method code so it also work for spaces? -- Posted via http://www.ruby-forum.com/. --~--~---------~--~----~------------~-------~--~----~ You received this message because you are subscribed to the Google Groups "Ruby on Rails: Talk" group. To post to this group, send email to

Hello, I'm using the rmeta package to perform a meta analysis using summary statistics rather than raw data, and would like to analyze the effects in three different subgroups of my data. Furthermore, I'd like to plot this on one forest plot, with corresponding summary weighted averages of the effects displayed beneath each subgroup. I am able to generate the subgroup analyses by simply

I have a nice hierarchical table structure like this: divisions has_many groups groups belongs_to division has_many subgroups subgroups belongs_to group has_many units units belongs_to subgroup I have a report which is based on units, but i want to be able to filter the units by which subgroup, or which group, or which division. I also want to sort them by division.name,then group.name,

Dear R-users, I want to multiple impute missing scores, but only for a few subgroups in my data (variable 'subgroups': only impute for subgroups 2 and 3). Does anyone knows how to do this in MICE? This is my script for the multiple imputation: imp <- mice(data, m=20, predictorMatrix=pred, post=post, method=c("", "", "", "",

Hi, I have a data.frame with many variables for which I am performing the mean by subgroup, for a pair of variables at a time, where one of them for each pair defines the subgroup. The subgroups in the x$cm1 are 0, 1 and 2. x ph1 cm1 0.2345 2 1.2222 1 2.0033 0 0.0000 2 1.0033 1 0.2345 0 1.2222 2 2.0033 0 0.0000 1 1.0033 2 > meanbygroup <- as.vector(with(x, by(x$ph1, x$cm1, mean)))

Dear Members of the R-Help, While using a R function - 'aggregate' that you developed, I become to have a question. In that function, > aggregate(x, by, FUN, ..., simplify = TRUE) I was wondering about what type of FUN I should write if I want to get "the most frequent value of the subgroup" as a summary statistics of the subgroups. I will appreciate if I can get

Hi All, Is there a feasibility for creating subgroups on the Puppet Dashboard? Basically the requirement is that we have a huge number of VMs running designated services. Some of VMs having the same service may yet have different properties configured on them. We are exploring the feasibility of having these properties managed through puppet. Currently all these VMs are put into a single

With this mail I would like to make a proposal to add additional informations to the core and plugin metadata files. Currently these tags are already handled in the ccs configuration system. Ccs automatically adds this informations to the core/plugin option set, but I think that it would make more sense to add this to the official files, to allow similar features in other configuration

Using the survival library, it is possible to get a plot of all the subjects in a sample and it is possible to get a plot of all subgroups in the same plot. How does one get a separate plot for each subgroup? plot(survfit(Surv(time,death==1)~group),col=1:10) The above results in a hideous graphic representation. I would prefer to specify par(mfrow = c(2, 5)) and have each plot separately --

I have the following formula for a linear model: z <- lm(y~x + factor(a) + factor(b), data=NT2010) where a (groups) and b (Sub-groups) are categorical variables (factors), x is a continuous covariate, and y the response variable. Since b is nested within a, the formula can also be written as: z <- lm(y~x + factor(a) + factor(a)/factor(b), data=NT2010) and the same output is achieved

Hi folks, I have a dataframe df.vars with the follwing structure: var1 var2 var3 group Group is a factor. Now I want to standardize the vars 1-3 (actually - there are many more) by class, so I define z.mean.sd <- function(data){ return.values <- (data - mean(data)) / (sd(data)) return(return.values) } now I can call for each var z.var1 <- by(df.vars$var1, group,

# Dear all, # how to replace values in x by means in subgroups created in ... # replace only these values where y=0 in continous sequence # replace by mean calculated locally for each subgroup created by # continous sequence of 0,0,0 in parallel y vector, i.e. # where there is continous sequence of 0 in data frame vector y # but we do not replace values in x[i], if y[i]!=0 # we do not want

On Wed 2015-05-27 05:23:41 -0400, Hubert Kario wrote: > On Tuesday 26 May 2015 15:10:01 Daniel Kahn Gillmor wrote: >> On Tue 2015-05-26 14:02:07 -0400, Hubert Kario wrote: >> > OEIS A014233 >> >> Hm, this is a sequence, but not an algorithm. It looks to me like it is >> not exhaustive, just a list of those integers which are known to have >> the stated

I'm sure there's a simple way to do this, but I can only think of complicated ones. I have a number of character vectors that look something like this: "12 78 23 9 76 43 2 15 41 81 92 5(92 12) (81 78 5 76 9 41) (23 2 15 43)" I wish to get it into a list of numerical vectors like this: $Group [1] 12 78 23 9 76 43 2 15 41 81 92 5 $Subgroup1 [1] 92 12 $Subgroup2 [1] 81 78 5

Hi all, LLVM needs a solution to the long-standing problem that the IR is unable to express certain semantics expected by high-level programming languages that target GPUs. Solving this issue is necessary both for upstream use of LLVM as a compiler backend for GPUs and for correctly supporting LLVM IR <-> SPIR-V roundtrip translation. It may also be useful for compilers targeting

Dear users of metafor, I am working on a meta-analysis using the metafor package. I have a excel csv database that I am working with. I am interested in pooling the effect measures for a particular subgroup (European women) in this csv database. I am conducting both sub-group and meta-regression. In subgroup-analyses, I have stratified the database to create a separate csv file just for European

I tried to post this a few times last week and it seems to have got stuck somehow so I'm trying from a different email in the hope that works. If somehow this has appeared on the list 20 tiems and I never saw any of them I apologize ;-) I'm basically an R-newbie. But I am VERY computer literate. But this has me stumped... All the examples for using the rmeta package to create a

Dear everybody, I have the following challenge. I have a data set with 2 subgroups, dates (days), and corresponding values (see example code below). Within each subgroup: I need to aggregate (sum) the values by week - for weeks that start on a Monday (for example, 2008-12-29 was a Monday). I find it difficult because I have missing dates in my data - so that sometimes I don't even have the