similar to: regression summary results pvalues and coefficients into a excel

Hello, I'm very new to R so my apologies if I'm making an obvious mistake. I have a data frame with ~170k rows and 14 numeric variables. The first 2 of those variables (let's call them group1 and group2) are used to define groups: each unique pair of (group1,group2) is a group. There are roughly 50k such unique groups, with sizes varying from 1 through 40 rows each. My objective is

Hi, How do I generate bootstrap p-values for goodness of fit test. Thank you in advance for your help, Juliet [[alternative HTML version deleted]]

dear all- If I have a vector of numbers (not necessarily normally distributed) how can I get the p-value of a number in this distribution. I am interested in the "inverse" of 'quantile' . thank you- Maya

Dear R users, I have developed a model I have compared several options of obtaining p-values for poisson lmer model including Marlov chain monty carlo methods, single term deletions and summary. > > However, I encountered several problems that can be classified as > (1) the p values from the summary command are total different from those derived from Marlov chain monty carlo methods >

Hello list, I have a similar issue as this post http://tolstoy.newcastle.edu.au/R/e6/help/09/04/11438.html#options2 and I used the suggestion provided by Jorge with modifications to my data do.call(c,lapply(your_list_with_the_t_tests,function(x) x$p.value)) but I am getting the following error after excuting the code B<-by(eo,eo$PlateID, function(.sub) t.test(mcp1~Self_T1D,data=.sub,

Hi all, I have some microarray data on 40 samples that fall into two groups. I have a value for 480k probes for each of those samples. I performed a t test (rowttests) on each row(giving the indices of the columns for each group) then used p.adjust() to adjust the pvalues for the number of tests performed. I then selected only the probes with adj-p.value<=0.05. I end up with roughly 2000

Hi all, My data genes [,1] [,2] [,3] [,4] [1,] 25 72 23 55 [2,] 34 53 41 33 [3,] 26 43 26 44 [4,] 36 64 64 22 [5,] 47 72 67 34 stu<-t.test(genes[,1:2],genes[,3:4]) > stu$p.value [1] 0.4198002 i get 1 pvalue for the entire col1:col2 Vs col3:col4. I am trying to get 5 p values for the 5 rows i have. I am trying to avoid a for loop coz my

On 23.11.2012, at 15:12, john skaller <skaller at users.sourceforge.net> wrote: > > On 23/11/2012, at 5:46 PM, Sean Silva wrote: > >> Adding LLVMdev, since this is intimately related to the optimization passes. >> >>> I think this is roughly because some function level optimisations are >>> worse than O(N) in the number of instructions. >>