similar to: Finding Interaction and main effects contrasts for two-way ANOVA

Hello, I have two data frames, NameAndConc.df and WhichOnes.df. NameAndConc.df has two columns, the first column is the names of some material, and the second column is the concentration of active ingredient. > NameAndConc.df name conc 1 material1 0.8 2 material2 0.5 3 material3 0.4 WhichOnes.df has two columns, each of which specifies which material. > WhichOnes.df

I am having trouble getting standard errors for contrasts using se.contrast() in what appears to be a simple case to me. The following test example illustrates my problem: Lab <- factor(rep(c("1","2","3"),each=12)) Material <- factor(rep(c("A","B","C","D"),each=3,times=3)) Measurement <-

Dear all, I'm looking for primary help at aggregating table() results and at writing a loop (if useful) My dataset ( http://goo.gl/gEPKW ) is composed of 23k rows, each one representing a point in the space of which we know the land cover over 10 years (column y01 to y10). I need to analyse it with a temporal sliding window of 5 years (y01 to y05, y02 to y06 and so forth) For each period

Hi all, I've been running loglinear models for three-way tables: one of the variables having three levels, and the other two having two levels each. An example looks like below: > yes.no <- c("Yes","No") > switch <- c("On","Off") > att <- c("BB","AA","CC") > L <- gl(2,1,12,yes.no) > T <-

Hi, all There are 62 samples in my data and I tested 3 times for each one, then I want to use ICC(intraclass correlation) from irr package to test the consistency among the tests. *combatexpdata_p[1:62] is the first text results and combatexpdata_p[63:124] * is the second one and *combatexpdata_p[125:186]* is the third. Here is the result:

Hi... In Stata, there is the ability to display scatter plots with data points at the same (x,y) location, using the 'jitter' command of the twoway scatter stata command. Anyone know of a way that I can do the equivalent thing in R? For non-Stata readers, if jitter is enabled in stata, and n-points would be at the same (x,y) location, the points are offset a bit (according to

Sanjay, I'm looking at some missed optimizations caused by D70246. Here's a test case: define <4 x float> @f(i32 %t32, <4 x float>* %t24) { .entry: %t43 = insertelement <3 x i32> undef, i32 %t32, i32 2 %t44 = bitcast <3 x i32> %t43 to <3 x float> %t45 = shufflevector <3 x float> %t44, <3 x float> undef, <4 x i32> <i32 0, i32 undef,

Hi R Users, I have a dataframe like this: id x rho A 1 0.1 B 20 0.5 C 2 0.9 ... I want to do a scatter plot of "x" versus "rho" but for each point on the scatter plot I want the corresponding entry for "id" instead of points. In STATA I can do so by twoway (scatter x rho, mlabel(id)) How can I do the same in R? I am sure there is some simple way to do

I see we're missing an isel pattern for add producing carry and doing a memory RMW. I'm going to see if adding that helps anything. ~Craig On Mon, Feb 27, 2017 at 8:47 PM, Nirav Davé via llvm-dev < llvm-dev at lists.llvm.org> wrote: > Yes. I'm seeing that as well. Not clear what's going on. > > In any case it looks to be unrelated to the alias analysis so barring

I've been searching for an answer to this for a while but no joy. I have a simple 2-way ANOVA with an interaction. I'd like to determine the power of this test for each factor (factor A, factor B, and the A*B interaction). How can I do this in R? I used to do this with "proc Glmpower" in SAS, but I can find no analogue in R. [[alternative HTML version deleted]]

Hi, In SPlus there is a function called "twoway" for median polishing gridded data. Is there an equivalent function in R? I have been searching for it in R help without much success. Your help is much appreciated. Cheers Sorn [[alternative HTML version deleted]]

Hello, I want to know if there are some functions or packages to solve differential and integral equation using R. Thanks. Shao chunxuan. [[alternative HTML version deleted]]

Hi, everyone: I ask for help about translating a stata program into R. The program perform cross validation as it stated. #1. Randomly divide the data set into 10 sets of equal size, ensuring equal numbers of events in each set #2. Fit the model leaving out the 1st set #3. Apply the fitted model in (2) to the 1st set to obtain the predicted probability of a prostate cancer diagnosis. #4. Repeat

Hello. I'm having problems at instruction selection with my back end with the following basic-block due to a vector add with immediate constant vector (obtained by vectorizing a simple C program doing vector sum map): vector.ph: ; preds = %vector.memcheck50 %.splatinsert = insertelement <8 x i64> undef, i64 %i.07.unr, i32 0

Has anyone ever setup Asterisk to pass Feature Group D access while using a CIC code for outbound calls? If so can you please email the configuration you have done? I have tried to get this up and running but with no luck. I have also contacted support and I cant seem to get this going. Thanks in Advance, Jason Miller

https://bugzilla.netfilter.org/bugzilla/show_bug.cgi?id=554 ------- Additional Comments From fhagur@gmail.com 2007-04-17 05:04 MET ------- I have been wondering about this bug and had similar problems myself here in my Debian system, linux-kernel 2.6.18 iptables 1.3.6. I too saw that some packets became transmitted illegally through the ppp0 interface, when they just shoudn't. What I

Hi helpeRs. When I do two-ways tables dimnames in columns are almost left-adjusted: <- factor(rbinom(30,1,.3),labels=c("first","second")) > b <- a > table(a,b) b a first second first 21 0 second 0 9 If I do a oneway table however, dimnames are right-adjusted: table(a) a first second 21 9 Actually I must admit I

Hi I'd really like to get a bar plot showing the means of my anova data. I have looked everywhere and can only seem to find instructions for 2 way anova's. I basically want to look at the mean condition of my subjects spilt by age, sex and year (as a factor rather than a continuous variable, hence Anova and not Ancova). and want to show it firstly as a bar graph with standard error. I

Hi, I have two different imaging modalities (for the identification of areas of infarcted myocardium) that I need to compare regarding agreement and consistency. However, I don't think that methods like Cohen's Kappa, PCC, Bland-Altmann or ICC are sufficient here as there is not just a pairwise but also a spatial relationship between measured data points. For example if the results of the

Here are the functions documented in the Blue Book that I found missing in R (ignoring the ones which are obviously outdated). aggregate allocated amatch axes chull clorder cutree cycle date debugger dget discr faces interp l1fit labclust lag loglin monthplot mstree mulbar napsack odometer persp plclust plotfit rep.int restore rreg sabl sablplot set.seed smooth sort.list Stable stars