search for: subjectives

I get the following message when using the reshape2 package line > tDat.m<- melt(Dataset) Using Item, Subject as id variables > tDatCast<- acast(tDat.m,Subject~Item) Aggregation function missing: defaulting to length Note Problem Statement- convert dataframe Subject Item Score 1 Subject 1 Item 1 1 2 Subject 1 Item 2 0 3 Subject 1 Item 3 1 4 Subject 2 Item 1 1 5

I'm implementing a custom bootstrap resampling procedure in R. This procedure resamples clusters of data points obtained by different subjects in an experiment. Since the bootstrap samples need to have the same size as the original dataset, `target.set.size`, I select speakers compute their data point contributions to make sure I have a set of the right size. set.seed(1)

I din't have the patience to go through your missive in detail, but do note that it is not reproducible, as you have not provided a "data" object. You **are** asked to provide a small reproducible example by the posting guide. Of course, others with more patience and/or more smarts may not need the reprex to figure out what's going on. But if not ... Cheers, Bert Bert Gunter

Hello, I was going to use lmer() on this data, but it seemed easier -- and more importantly, more meaningful -- to just analyze smaller sections of it individually. I'd like to ask for help to see if I'm analyzing the separate parts correctly. Each part is the same, and they all look like this: ______________________________________________________________ question 1 question 2

Hi I would like to transform a data frame like Subject Item Score Subject 1 Item 1 1 Subject 1 Item 2 0 Subject 1 Item 3 1 Subject 2 Item 1 1 Subject 2 Item 2 1 Subject 2 Item 3 0 .... *to * Subject Item1 Item2 Item3 .....Item N Subject1 1 0 1 Subject2 1 1 0 ........ SubjectP.. Apologize for the simple nature of my query but I am stuck.

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Hi everyone, I'm sure this is simple, but I can't seem to figure this out. Situation. 3 different groups of subjects each submit n X n matrices of scores. What I want to do is aggregate each group of scores into a summary n X n matrix. I need the result to be a matrix so that I can calculate a dissimilarity structure on it. So I thought I would create a multi-dimensional array and

================================================= This is an automated summary of the status of the R-bugs repository. Note that this may be neither complete nor perfectly correct at any given instance: Not all bugs are reported, and some reported bugs may have been fixed, but the repository not yet updated. Some bug fixes are difficult to verify because they pertain to specific hardware or

================================================= This is an automated summary of the status of the R-bugs repository. Note that this may be neither complete nor perfectly correct at any given instance: Not all bugs are reported, and some reported bugs may have been fixed, but the repository not yet updated. Some bug fixes are difficult to verify because they pertain to specific hardware or

================================================= This is an automated summary of the status of the R-bugs repository. Note that this may be neither complete nor perfectly correct at any given instance: Not all bugs are reported, and some reported bugs may have been fixed, but the repository not yet updated. Some bug fixes are difficult to verify because they pertain to specific hardware or

================================================= This is an automated summary of the status of the R-bugs repository. Note that this may be neither complete nor perfectly correct at any given instance: Not all bugs are reported, and some reported bugs may have been fixed, but the repository not yet updated. Some bug fixes are difficult to verify because they pertain to specific hardware or

Any advice, tips, clues or pointers to resources on how best to speed up or, better still, avoid the loops in the following example code much appreciated. My actual dataset has several tens of thousands of rows and lots of columns, and these loops take a rather long time to run. Everything else which I need to do is done using vectors and those parts all run very quickly indeed. I spent quite a

Dear R users, I have copied for following table from an article on "Using confidence intervals in within-subject designs": Subject 1sec 2sec 5sec 1 10 13 13 12.00 2 6 8 8 7.33 3 11 14 14 13.00 4 22 23 25 23.33 5 16 18 20 18.00 6 15 17 17 16.33 7 1 1 4 2.00 8 12 15 17 14.67 9 9 12 12 11.00 10 8 9 12 9.67 I rearranged the data this way:

I am trying to render a file from Subject resource in a User resource view. I am getting error: undefined method `each'' for nil:NilClass. Apparently @subject is nil but not sure how to fix this... Here is User resourve view (users/show.html.erb) <%= render ''subjects/index'' %> Here is subjects_controller def show @subject = Subject.find(params[:id]) ...

Hi! I noticed the following problem in dovecot-1.2-sieve-0.1.14: The following vacation causes trouble with the Subject line: if not exists ["List-Id", "List-Post"] { vacation :days 7 :addresses ["test at netcologne.de"] :subject "=?utf-8?b?w4TDlsOc?= sadasd" "Bin gerade nicht hier."; } As you can see, the Subject is already MIME encoded

================================================= This is an automated summary of the status of the R-bugs repository. Note that this may be neither complete nor perfectly correct at any given instance: Not all bugs are reported, and some reported bugs may have been fixed, but the repository not yet updated. Some bug fixes are difficult to verify because they pertain to specific hardware or

================================================= This is an automated summary of the status of the R-bugs repository. Note that this may be neither complete nor perfectly correct at any given instance: Not all bugs are reported, and some reported bugs may have been fixed, but the repository not yet updated. Some bug fixes are difficult to verify because they pertain to specific hardware or

Hi All, I was wondering if someone could help me to solve this issue with lmer. In order to understand the best mixed effects model to fit my data, I compared the following options according to the procedures specified in many papers (i.e. Baayen <http://www.google.it/url?sa=t&rct=j&q=&esrc=s&source=web&cd=1&ved=0CDsQFjAA

I've got a data frame that looks like this: subject foo bar 2 1.7 3.2 2 2.3 4.1 3 7.6 2.3 3 7.1 3.3 3 7.3 2.3 3 7.4 1.3 5 6.2 6.1 5 3.4 6.9 ... That is, I've got multiple rows per subject. I need to compute summaries within categories where the subject has the same number

I have a data set like the following: subject visit x1 1 1 0.5 1 2 1.2 1 3 0.7 2 1 0.4 2 2 0.6 2 3 1.0 ..... where x1 is the interval between the two visits. Now I want to calculate the cumulative intervals since the beinging, for example subject visit x1 cum 1 1 0.5 0.5 1 2 1.2 0.5+1.2 1 3 0.7 0.5+1.2+0.7 2 1 0.4 0.4 2 2 0.6 0.4+0.6 2 3 1.0 0.4+0.6+1.0 ..... is there an easy to generate the