search for: subgroupings

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'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

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

Unable to resolve error in seq.default(which(text == "")[1] + 1, length(text), 1): wrong sign in 'by' argument I am trying to run this code get.msg <- function(path) { con <- file(path, open = "rt", encoding = "latin1") text <- readLines(con) # The message always begins after the first full line break msg <- text[seq(which(text ==

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("", "", "", "",

I would like to be able to use lme to fit random effect models In which some but not all of the random effects are constrained to be independent. It seems as thought the pdMat options in lme are a promising avenue. However, none of the existing pdMat classes seem to allow what I want. As a specific example, I would like to fit a random intercept/slope mixed model to longitudinal observations in

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,

Hi, Is there is any way in ruby on rails where we show all my groups there subgroups with check boxes in tree structure way? e.g group A | ----Group A.1 | ----Group A.2 | ---------Group A.2.1 All with check boxes and subgroup opens when click on root ? -- Posted via

On Wed, May 27, 2015 at 05:08:25PM -0400, Daniel Kahn Gillmor wrote: > On Tue 2015-05-26 15:39:49 -0400, Mark D. Baushke wrote: > > Hi Folks, > > > > The generator value of 5 does not lead to a q-ordered subgroup which > > is needed to pass tests in > > > > http://csrc.nist.gov/publications/nistpubs/800-56A/SP800-56A_Revision1_Mar08-2007.pdf > > I

On Fri 2015-06-12 01:52:54 -0400, Mark D. Baushke wrote: > I have communicated with Allen Roginsky on this topic and I have been given permission to post his response. > > In this message below, the 'vendor' was Darren Tucker's generated prime > that used a generator value of 5. > > -- Mark > > From: "Roginsky, Allen" <allen.roginsky at

Hi there, Could someone help me with the following programming problem..? I have written a function that works for my intended purpose, but it is quite closely tied to a particular dataframe and the names of the variables in this dataframe. However, I'd like to use the same function for different dataframes and variables. My problem is that I'm not quite sure how to tell my function in

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

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

Dear list, I have a data frame with one column (group) and want to add a second column (sub) with a serial number that says to which subgroup a cell belongs. A subgroup contains the consecutive rows of the same group. The number of a subgroup is based on its position in the table. The first subgroup of A's and B's should have nr A1 and B1, the second nr A2 and B2, etc.. I hope the

# 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

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,

I would very much like to apply "subgroup discovery" techniques to some of the data I am analyzing at this moment. Subgroup discovery is an interesting approach and is quite well known in the Data Mining community, though in essence it is a purely statistical approach. To read an introductory article see "Subgroup discovery and visualization methods"

Dear Colleagues, I am looking for a package or previous implemented R to subgroup and exaustively divide a vector of squence into 2 groups. For example: 1, 2, 3, 4 I want to have a group of 1, (2,3,4) (1,2), (3,4) (1,3), (2,4) (1,4), (2,3) (1,2,3), 4 (2,3), (1,4) ... Can someone help me as how to implement this? I get some imaginary problem when the sequence becomes large. Thanks much in

Hi, I have data that looks like this: ASA1 ASA2 C1_C2 C M 9.0225 S S 2.4315 M C 3.4894 M S 4.5282 C M 1.3183 C S 1.3735 S C 1.0488 S M 7.948 M C 4.5827 I need to plot Boxplots for a given ASA1 (either C,S, or M) with respect to C1_C2. However, instead of one boxplot I want to plot