similar to: ANOVA 1 too few degrees of freedom

Hi all, ########################################## dof=c(1,2,4,8,16,32) Q5=matrix(rt(100,dof),100,6,T,dimnames=list(NULL,dof)) par(mfrow=c(2,6)) apply(Q5,2,hist) myf=function(x){ qqnorm(x);qqline(x) } apply(Q5,2,myf) ########################################## These looks ok. However, I would like to achieve more. Apart from using a loop, is there are fast way to 'add' the titles to be

Hello Everyone Both the MCMCpack and the bayesm libraries allow us to make draws from the Inverse Wishart distribution. But I wanted to find out how exactly is the Inverse Wishart distribution parameterized in these libraries. The reason I ask is the following: Now its generally standard to express Inverse Wishart as IW(0.5 * DOF,0.5* Scale). (DOF-> Degree of freedom, Scale -> Scale

Hello! I have a question about the factanal function. This function returns at the end test statistics like this: Test of the hypothesis that 4 factors are sufficient. The chi square statistic is 4.63 on 2 degrees of freedom. The p-value is 0.0988 Is it possible to get the chi square statistic and the p-value as variables, not the text on the screen? An object of class "factanal"

Hi there, Does anyone know how to explicitly refer to the p-value of thet test that the chosen number of factors is significant in a factor analysis. It's not in the list of values for the factanal command output yet it is printed out with the results. Thanks in advance. Wayne Dr Wayne R. Jones Statistician / Research Analyst KSS Group plc St James's Buildings 79 Oxford Street

I need to fit a t copula with fixed degree of freedom let's say 4. I do not want to estimate the dof together with correlation matrix optimally. Instead fix the dof to 4 and only estimate the correlation matrix in the optimization routine. Is anyone aware of such estimation method in R. The packages and functions that I know of can't do this estimation. I searched online but

Hi, I''m posting a question hoping someone will know the answer off hand thereby reducing my search time. :-) With USDT probes, the tracepoint is only installed by libdtrace itself, never by the drti ioctl. So whenever I run a program with an USDT probe, no tracepoint is installed. Only after I run the dtrace command the tracepoint is actually installed on the victim process. My question

Hi, I want to compute the quantiles of Chi^2 distributions with different degrees of freedom like x<-cbind(0.005, 0.010, 0.025, 0.05, 0.1, 0.5, 0.9, 0.95, 0.975, 0.99, 0.995) df<-rbind(1:100) m<-qchisq(x,df) and hoped to get back a length(df) times length(x) matrix with the quantiles. Since this does not work, I use x<-c(0.005, 0.010, 0.025, 0.05, 0.1, 0.5, 0.9, 0.95, 0.975,

--=-hiYzUeWcRJ/+kx41aPIZ Content-Type: text/plain; charset="UTF-8" Content-Transfer-Encoding: 8bit Hi, on March 10 I filed a wishlist bug report asking for the inclusion of some changes to factanal() and the associated print method. The changes were originally proposed by John Fox in 2005; they make print.factanal() display factor correlations if factanal() is called with rotation =

Hello, R users, I have two factors (treat, section) anova design experiment where there are 3 replicates. The objective of the experiment is to test if there is significant difference of yield between top (section 9 to 11) and bottom (section 9 to 11) of the fruit tree under treatment. I found that there are interaction between two factors. I wonder if I can contrast means from levels of

Dear R-list, I have a partly comma separated partly underscore separated string that I am trying to parse into R. Furthermore I have a bunch of them, and they are quite long. I have now spent most of my Sunday trying to figure this out and thought I would try the list to see if someone here would be able to get me started. My data structure looks like this, (in a example.txt file) Subject

Hello, R experts, I have a list called dataHP which has 30 elements (m1, m2, ..., m30). Each element is a 7x6 matrix holding yield data from two factors experimental design, with treatment in column, position in row. For instance, the element 20 is: dataHP[[20]] col1 col2 col3 trt1 trt2 trt3 [1,] 22.0 20.3 29.7 63.3 78.5 76.4 [2,]

Dear Thomas Lumley, and R-help list members, I have read your article "Network meta-analysis for indirect treatment comparisons" (Statist Med, 2002) with great interest. I found it very helpful that you included the R code to replicate your analysis; however, I have had a problem replicating your example and wondered if you are able to give me a hint. When I use the code from the

Dear, I have a dataset with 4 subjects (see ID in example), and 4 treatment (see TRT in example) which are tested on 2 locations and in 3 blocs. By using Lattice dotplot, I made a graph that shows the raw data per location and per bloc. In that graph, I would like to have a reference line per bloc that refers to the first treatment (T1). However, I can not find how to do that. I can make

Hi, I'm trying to fit a marginal model via GEE but I'm getting strange results and few problems. If I set the working correlation as exchangeable I'm getting the same fitting when I set as independent. Comparing to SAS results it shouldn't happen. If I try to use another working correlation (like AR-M or stat_M_dep), R just exits without giving any error message. Another doubt

Dear R - Users I have some problems fitting a linear mixed effects model using the lme function (nlme library). A sample data is as shown at the bottom of this mail. I fit my linear mixed model using the following R code: bmr <-lme (outcome~ -1 + as.factor(endpoint)+ as.factor(endpoint):trt, data=datt, random=~-1 + as.factor(endpoint) + as.factor(endpoint):trt|as.factor(Trial),

I am trying to define groupings from levels of factor variables and this the warning message that R give "& not meaningful for factors". The nature of my task is this. I have a variable stage which has the levels (1B, 2A, 2B) - these are the AJCC TNM stages of cancer, and another variable diameter with factor levels ("=< 4", "4 - 6.5, > 6.5; limit values are

I am confused whether Student's sleep data "show the effect of two soporific drugs" or Control against Treatment (one drug). The reason is the next: > require(stats) > data(sleep) > attach(sleep) > extra[group==1] numeric(0) > group [1] Ctl Ctl Ctl Ctl Ctl Ctl Ctl Ctl Ctl Ctl Trt Trt Trt Trt Trt Trt Trt Trt Trt [20] Trt Levels: Ctl Trt > sleep$group [1] 1 1 1 1 1

Hello, I have a problem with creating an identity matrix for glmnet by using the contrasts function. I have a factor with 4 levels. When I create dummy variables I think there should be n-1 variables (in this case 3) - so that the contrasts would be against the baseline level. This is also what is written in the help file for 'contrasts'. The problem is that the function

Hello, I probably have a syntax error in trying to generate an expected survival curve from a weighted cox model, but I can't see it. I used the help sample code to generate a weighted model, with the addition of a "weights=albumin" argument (I only chose albumin because it had no missing values, not because of any real relevance). Below are my code with the resulting error

Hi there, The following data is obtained from a long-term experiments. > mydata <- read.table(textConnection(" + y year Trt + 9.37 1993 A + 8.21 1995 A + 8.11 1999 A + 7.22 2007 A + 7.81 2010 A + 10.85 1993 B + 12.83 1995 B + 13.21 1999 B + 13.70 2007 B + 15.15 2010 B + 5.69 1993 C + 5.76 1995 C + 6.39 1999