similar to: Analysis of Variance

Hi As I can't find an example of my data structure I'd like some advice on which is the most appropriate test for significant effects. If I should be using either lme or anova, is the relevant example below the best/correct way to do the test? The Data... 2 groups of patients (5 in GroupA, 7 in GroupB) 3 short acting drugs, (I'm not concerned with residual effects from the previous

Hi all, thank you for your patience. I am dealing with a large dataset detailing patients and medications Medications are hard to code, as they are (usually) meaningless unless matched with doses. I have a dataframe with vectors (Drug1, Drug2..... Drug 16) and individual patients are represented by rows. The vectors are actually factors, with 100s of possible levels (all the drugs the patient

Please help with this error message drugbook is an 885 x 32 dataframe >names(drugbook) [1] "DRUG1" "DRUG2" "DRUG3" "DRUG4" "DRUG5" [6] "DRUG6" "DRUG7" "DRUG8" "DRUG9" "DRUG10" [11] "DRUG11" "DRUG12"

Relative noob here, I have a data.frame and simply want to add an explicit column of names in column 1 of the form "trial_number01" for row 1, "trial_number02" for row 2 .... etc. It is simply for visual purposes and to explain data to others. I've tried Using row.names and other but still no luck, am sure it has been covered but I can't find it, can you please point

All, Is there an efficient way to apply say "mean" or "median" to a dataframe according to say all combinations of two variables in the dataframe? Below is a simple example and the outline of a "manual" solution that will work but is not very efficient (could also generalize this to a function). Searched the archives and docs but didn't see anything close to

Hi, I am running a mixed-effect model with a nested-random effect. I am interested in gut parasites in moose. I has three different type of treatment that I applied to moose which are from different "families". My response variable is gut parasites and the factors are moose families which is nested within treatment. My data is balanced. To answer this question, I used the lme function

Hello I simply want to plot two variables against one 'year' variable in qplot. Is any way of doing this without reshaping data in long format and using facet function afterwards? Thank you Denis

Hey all, I'm trying to replicate some plots with ggplot2. The problem is that I need to specify the color for every attribute (drug). If I use the code below the colors get automatically assigned but I need to plot drug1 in black drug2 in blue etc. How do I do that? q = qplot(days,vol,data = cellLine7064, color = drug, geom = c("line", "point")) best regards, Immanuel

All, When specifying colors to xyplot w/ a groups argument, using auto.key no longer maintains the colors properly. I've searched the docs and help but haven't found exactly what I need ... I saw a few examples in the archives involving par.settings but that doesn't seem to do it. I also saw some people using key instead of auto.key, but that didn't seem consistent. Is there a

Dear R-maillit, I have to perform a stastistical test to asses if two grug show the same or different effect on my prepartion. I tested on the same preparation only one drug and I have to use normalized data due to high variability in the control condictions. What type can I use? A non paramatric test right? And how can do it on R software? Thanks in advance Simone [[alternative HTML version

Hello fellow R-ers, I have spent some time on this and it is driving me NUTS! I am sure there is a solution, so please help. I am trying to create a function that will plot different lines for subsets of a dataset. For example, I am trying to look at different drug groups (drug2), let's say 1,2,3,4, and 5. The data has 2 different rates, college students and high school students (var names cs

I'm a journalist, wondering what questions to ask about a study that contrasted the impact on serum cholesterol of two drugs. This was a 40 dog study: 5 treatment blocks of 4 dogs each, randomized to: a control block, two blocks at different doses of drug1 and two at corresponding doses of drug2. Analysis was 2-factor repeated measures ANOVA on treatment group and sampling time. Linear

Hello, I have a question about the documentation of the Samba Howto's. Specifically, I am not able to understand how group mapping ties into LDAP. I believe I understand the concept of unix to windows group mapping as laid out in chapter 12 as it relates a tdbsam, but get confused when dealing with a ldapsam back-end. There is a note listed " When the passdb back-end uses LDAP

Hi, We were wondering how we could make a stacked frequency diagram such as this one: http://msemac.redwoods.edu/~darnold/math15/liz.pdf We don't necessarily need the shaded "balls", other characters would be fine, such as stacks of x's. David

Dear List, Here is an example of survival data in counting process format (detailed record of each day) > data[data$Id == 11,] # extracted one person's record Id Event Fup Start Stop sex Drug1 601 11 0 6 0 1 0 0 602 11 0 6 1 2 0 0 603 11 0 6 2 3 0 0 604 11 0 6 3 4 0 0 605 11 0 6 4 5 0 1 606

Hi, Typical things you read when new to stats are cautions about using a t-statistic when comparing independent samples. You are steered toward a pooled test or welch's approximation of the degrees of freedom in order to make the distribution a t-distribution. However, most texts give no information why you have to do this. So I thought I try a little experiment which is outlined here.

Hi Deepayan and everyone, I need to add a common legend to a group of latice graphs, I have tried different ways using viewport and grid.draw without success. Here is what I have: plot.new() library(grid) library('IDPmisc') print(plot1, split=c(1,1,2,4), more=TRUE) print(plot4, split=c(2,1,2,4), more=TRUE) print(plot2, split=c(1,2,2,4), more=TRUE) print(plot5, split=c(2,2,2,4),

Dear all, The following is a example that I run and hope to get a linear model. However, I find the lm() can not give correct coefficients for the linear model. I hope it's just my own mistake. Please help. TIA. Regards, Jinsong > x [1] 3.760216 3.997288 3.208872 3.985417 3.265704 3.497505 2.923540 3.193937 [9] 3.102787 3.419574 3.169374 2.928510 3.153821 3.100385 3.768770 3.610583

Hi, I just read the "Embedding R in Gnumeric" idea at http://www.r-project.org/SoC08/ideas.html. On my side, I intend to add as many statistics related plot types to the current gnumeric charting engine as possible. We already have boxplots and partial support for histograms. My immediate plans are to finish the histogram code and add probability plots

Background: OS: Linux Mandrake 10.1 release: R 2.0.0 editor: GNU Emacs 21.3.2 front-end: ESS 5.2.3 --------------------------------- Colleagues I am having some trouble extracting results from the function by, used to average variables in a data.frame first by one factor (depth) and then by a second factor (station). The real data.frame is quite large > dim(data.2001) [1] 32049 11 Here is a