similar to: abline by groups

Dear R users, i'm using a custom function to fit ancova models to a dataset. The data are divided into 12 groups, with one dependent variable and one covariate. When plotting the data, i'd like to add separate regression lines for each group (so, 12 lines, each with their respective individual slopes). My 'model1' uses the group*covariate interaction term, and so the coefficients

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

Hi, I am trying to use xyplot to plot the relationship between size and day (y~x) by a food factor that has two levels, low and high. I have 3 reps per factor/day. I want the plots from each food treatment on the same axiss, so I used this code: xyplot(Size ~ Day, groups = Food, data = louis.data.means,col=1, pch=c(1,17), panel=function(x,y,groups,...){ panel.superpose(x,y,groups,...)

I am trying to plot an interaction in a multilevel model. Here is some sample data. In the following example, it is longitudinal (i.e., repeated measures), so the outcome, score (at each of the three time points), is nested within the individual. I am interested in the interaction between gender and happiness predicting score. id <- c(1,1,1,2,2,2,3,3,3) age <-

Dear R community, I would wish to color the background of my histogram differently to the left and right of an abline... Can you please help? Thankin you, Georg. **************************** Georg Ehret JHU Baltimore - USA [[alternative HTML version deleted]]

Hi folks Run; > ToothGrowth > attach(ToothGrowth) > toothgrowth=lm(len~dose) adding abline: > abline(toothgrowth) I got it done adding single abline. How to add more ablines on the same diagram? I found following thread, applying "mapply" command; Plotting multiple ablines http://www.mail-archive.com/r-help@r-project.org/msg51543.html mapply(abline, (converge$kY +

Hi all, I have this code I want to add two ablines like this abline(h=2400, lty=3, col="lightgrey") abline(h=400, lty=3, col="lightgrey") But doesnt wotk. I alo try to set ylim from 0 to max "Foa"+1000 but I?m not able ?Is it posible? require(latticeExtra) require(ggplot2) require(reshape2) suppressPackageStartupMessages(require(googleVis)) require(quantmod)

Hi all, I'm attempting to make a quite-specific plot where the axes cross at the origin and with gridlines for guidance. I've been using ablines to create the reference lines because I want a lot of control as to where they are placed on the axis. This command works very well for such control. However... These ablines don't seem to work when I specify the origin as 0,0. They go

Hello R experts I have two linear regressions for sexes (Male, Female, Unknown). All have a good correlation between body length (response variable) and head length (explanatory variable). I know it is not recommended, but for a good practical reason (the purpose of study is to find a single conversion factor from head length to body length), the regressions need to go through the origin (0

Hello, I am VERY new to R, just picking it up infact. I have got my head around the basics of ANOVA with post hoc tests but I am struggling with regression, especially with ANCOVAs. I have two sets of data, one of type A, one of type B. Both have been placed in a wind tunnel and sampled every week. The co variate is of course the days since the start. An example is day A B 0 10.0 10.0 7 9.0

Good morning, I have some problem adding ablines in Rstudio. The lines drew by the software doesen?t match with the added values, what can I do? pfaOK<-qcc(D[!trial], sizes=size[!trial], type="p", nsigmas=2, data.name="Polli positivi al Campylobacter") pfaOK1<-qcc(D[!trial], sizes=size[!trial], type="p", data.name="Polli positivi al Campylobacter")

dear all, I want to perform a posthoc test for my ANCOVA: a1<-aov(seeds~treatment*length) With summary(glht(a1, linfct = mcp(treatment = "Tukey"))) R tells me: "covariate interactions found -- please choose appropriate contrast" How do I build these contrasts? Ideally, I would like to have the posthoc test for the ANCOVA including a block-effect

Hello, I have a problem with using the following design with ANCOVA in R. There are two groups (control + treatment), each with ten subjects. The subjects show a response that is monitored over time (four time points). For a single given subject, the response can be analysed with linear regression with time as the independent variable. The question is, how does the response differ between the

Consider the following plot that shows separate regression lines ~ age for each subject in the Pothoff-Roy Orthodont data, with separate panels by Sex: library(nlme) #plot(Orthodont) xyplot(distance ~ age|Sex, data=Orthodont, type='r', groups=Subject, col=gray(.50), main="Individual linear regressions ~ age") I'd like to also show in each panel the pooled OLS

The messages are visible in 2.6.0dev The same commands in 2.4.1 work without warning messages. I am using the HH_1.18-1 from R_2.4.1 with both R versions and not the current HH_2.1-3 version$version.string installed.packages()[c("grid","lattice", "HH"),3] ## library(HH) library(lattice, lib.loc="C:/PROGRA~1/R/R-2.4.1/library") hotdog <-

Hi, want to shade the area between dotted lines: x=c(1,5);y=c(1,5) plot(y~x, type='n') abline(v=c(2,3), lty=2) sometnig simple needed. tried with polygon.... thx, robert -- View this message in context: http://r.789695.n4.nabble.com/shade-area-between-ablines-tp2537352p2537352.html Sent from the R help mailing list archive at Nabble.com.

I have stumbled across something in the Lattice package that is vexing me. Consider the code below: __________________________________________________________ library(lattice) myData <- expand.grid(sub = factor(1:16), time = 1:10) myData$observed <- rnorm(nrow(myData)) myData$fitted <- with(myData, ave(observed, sub, FUN = mean)) myData$event.time <- with(myData, ave(observed, sub,

Could you please help me on the following ANCOVA issue? This is a part of my dataset: sampling dist h 1 wi 200 0.8687212 2 wi 200 0.8812909 3 wi 200 0.8267464 4 wi 0 0.8554508 5 wi 0 0.9506721 6 wi 0 0.8112781 7 wi 400 0.8687212 8 wi 400 0.8414646 9 wi 400 0.7601675 10 wi 900 0.6577048 11 wi 900

Dear r helpers, I would like to look at the interaction between two two-level factors, one between and one within participants, after accounting for any variance due to practice (31 trials in each of two blocks) in the task. It seems to require treating practice as a covariate. All the examples I noticed for handling covariates (i.e. ANCOVA, including the ones in Faraway's "Practical

Hi all: I have a question about multi-comparison. The data is in the attachment. My purpose: Compare the predicted means of the 3 methods(a,b,c) pairwisely. I have 3 ideas: #idea1 result_aov<-aov(y~ method + x1 + x2) TukeyHSD(result_aov) diff lwr upr p adj b-a 0.845 0.5861098 1.1038902 0.0000001 c-a 0.790 0.5311098 1.0488902 0.0000002 c-b -0.055 -0.3138902