similar to: How to run mixed model with related independent variables

Dear R experts, I have plot the PDF of t distribution with df = 74. curve(dt(x,df=74),from=-4, to=4) how can I shade the area under curve (for example, col="red") from t=+- 1.996? Thank you. Regards, CH -- CH Chan Research Assistant - KWH http://www.macgrass.com

Hi, I have the following dataset and I would like to create a dotplot with confidence limits: CAT1 CAT2 MEAN Lower Upper 1 1 1 0.619 0.392 0.845 2 1 10 1.774 1.030 2.518 3 1

Hello List, i have been agonizing over this for days, any reply would be greatly appreciated! Situation:___________________________________ My original dataset is a .csv dataset (w/ 2M records) with 4 variables: job_id (Primary key, won't be used for analysis, just used for join tables), sector_id (categorical variable, for 19 industry sectors), sqft (con't variable for square

I've only recently started using R. One of the problems I come up against is after having extracted a large dataset (>5M rows) out of database, I realize I need another variable. In this case I have data frame with dates. I want to find the minimum date for each value of x1 and add that minimum date to my data.frame. > randomdf <- function(p) { data.frame(x1=sample(1:10^4, 10^p,

Dear all, I have the following dataset: each row corresponds to count of forest floor small mammal captured in a plot and vegetation characteristics measured at that plot > sotr plot cnt herbc herbht 1 1A1 0 37.08 53.54 2 1A3 1 36.27 26.67 3 1A5 0 32.50 30.62 4 1A7 0 56.54 45.63 5 1B2 0 41.66 38.13 6 1B4 0 32.08 37.79 7 1B6 0 33.71 30.62

* * Hi , Can anyone help me please with this problem?* * *CASE-I* all_raw_data_NAomitted is my data frame.It has columns with names i1 ,i2, i3,i4…, till i15.It has 291 rows actually ,couldn’t show here. The data frame looks like this:-- i1 i2 i3 i4 i5 i6 i7 i8 i9 i10 i11 i12 i13 i14 i15 2 2 2 2 2 2 2 2 2 2 2 1 2 2 3 2 3 2 2 2 2 3 2 2 3 3

When I was studying the function cut I found this example: > x <- rep(0:8, tx0) > x [1] 0 0 0 0 0 0 0 0 0 1 1 1 1 2 2 2 2 2 2 3 3 3 3 3 4 4 4 5 5 5 5 5 5 5 5 5 5 6 [39] 6 6 6 6 7 7 7 8 8 8 8 8 > cut(x, b = 8) [1] (-0.008,0.994] (-0.008,0.994] (-0.008,0.994] (-0.008,0.994] (-0.008,0.994] [6] (-0.008,0.994] (-0.008,0.994] (-0.008,0.994] (-0.008,0.994] (0.994,2] [11] (0.994,2]

[markdown format] I'm glad to introduce you the new package aVirtualTwins. This package is an adaptation of VirtualTwins method of subgroup identification from [Foster, J. C., Taylor, J. M.G. and Ruberg, S. J. (2011)](http://onlinelibrary.wiley.com/doi/10.1002/sim.4322/abstract). ### Explanation Virtual Twins has been created to find subgroup of patients in a random clinical trial with

[markdown format] I'm glad to introduce you the new package aVirtualTwins. This package is an adaptation of VirtualTwins method of subgroup identification from [Foster, J. C., Taylor, J. M.G. and Ruberg, S. J. (2011)](http://onlinelibrary.wiley.com/doi/10.1002/sim.4322/abstract). ### Explanation Virtual Twins has been created to find subgroup of patients in a random clinical trial with

Dear R-help, I'd like ask for your opinion on choosing the "right" strategy for a particular dataset. We conducted 24-hour electric field measurements on 90 subjects. They are grouped by job (2 categories) and location (3 categories). There are four exposure metrics assigned to each subject. An excerpt from the data: n job location M OA UE all 0 job1 dist_200 0.297 0.072 0.171

Hi- I am having trouble with the syntax of looping through the rows and columns of a data frame. I have a table with 17 observations for 84 lines at n=5-10 per line. So the table is ~700x17. I want to pull out the median and stdev for each line and put it in a dataframe with rowname = linename. So I have tried the following.... #read in the table input.table <- read.table(file =

Dear all, Does any one knows why should I get the following error message, when trying to do a simple data.frame?? DataF<-data.frame(Subject,BiomR,Spp,Capas,Litter,Herbs,LitterD,MaxCanH,DDifS p,DSSp,Slope, CanDens,NearestSp) Erro em data.frame(Subject, BiomR, Spp, Capas, Litter, Herbs, LitterD, : arguments imply differing number of rows: 202, 0 The data I am using

Hi all. I am cleaning up (I hope) one of the nastier pieces of code in openssh: do_setusercontext which is/was a twisty maze of platform-specific nested ifdefs. I made a series of changes[1] where I moved each platform-specific piece into a portable-only file platform.c, which does not need to be kept in sync with OpenBSD. The changes did not (I hope!) change the semantics, but there's one

Dear folks, I have a question about the image() function in R. I found the following link talking about this but the replies didn't help with my situations. http://r.789695.n4.nabble.com/question-on-image-function-td839275.html#a839276 To be simple, I will keep using the example in the above link. Suppose the data are like x y mcpvalue 0.4603578

Dear friends, My dataset is like the following: x y mcpvalue 0.4603578 0.6247629 1.001 0.4603715 0.6247788 1.001 0.4603852 0.6247948 1.001 0.4110561 0.5664841 0.995 The x and y variables are unsorted. I use the function image(x,y,mcpvalue) to generate a plot, but the error is that "increasing 'x' and

Hello everyone, I use latex() (Hmisc) for report generation and thus have been affected by the problem with rounding decimals described, for example, in this post: http://thread.gmane.org/gmane.comp.lang.r.general/73287/focus=73287 In short, numbers often are printed with 15 or so decimals even if there far less significant digits. The problem has been confirmed by Frank Harrell and Thomas

Hi, Is it normal to get intercept in the list of covariates in the output of survreg function with standard error, z, p.value etc? Does it mean that intercept was fitted with the covariates? Does Value column represent coefficients or some thing else? Regards, ------------------------------------------------- tmp = survreg(Surv(futime, fustat) ~ ecog.ps + rx, ovarian,

Hi All, I am using the glm.nb function from the MASS package (current version) to fit and compare GLMs with negative binomial error distributions. My question is: what is the appropriate method to use in the anova function to compare models? If only one fitted object like m<-glm.nb(number<-p+sal+temp,data=data) is specified in the anova function (anova(m)), a fixed theta is used to

Estimad en s, quería realizar una consulta Dado un data frame llamado aves, como puedo sustiuir las variables area, dist y distm por sus logaritmos en base10 y volver a crear un data frame? Muchas gracias Saludos Susana [[alternative HTML version deleted]]

Hi, When I run the survfit function, I want to get the restricted mean value and the standard error also. I found out using the "print" function to do so, as shown below, print(km.fit,print.rmean=TRUE) Call: survfit(formula = Surv(diff, status) ~ 1, type = "kaplan-meier") records n.max n.start events *rmean *se(rmean) median 200.000