similar to: simple question about contrasts, lm and factors

dear list, i am using a multifactorial design with two treatments (factor A: drugs, three levels; factor B: theraphy, two levels) and a time factor (three levels, different timepoint). hypothetically, i measured the same subjects for all treatements and timepoints, so its a repeated measurement design. now i ran an anova in R and also some Tukey post-hoc tests using glht. but what i am actually

All, How does one extract the level-1 variance from a model fit via lmer()? In the code below the level-2 variance component may be obtained via subscripting, but what about the level-1 variance, viz., the 3.215072 term? (actually this term squared) Didn't see anything in the archives on this. Cheers, David > fm <- lmer( dv ~ time.num*drug + (1 | Patient.new), data=dat.new )

All, I'm trying to plot an all.effects() object, as shown in the help for all.effects and also Crawley's R book (p.178, 2007). The data has a repeated measures structure, but I'm using all.effects for the simple lm() fit here. Below is a reproducible example that yields the error message. fm.ex = lm(dv ~ time.num*drug*X, data = dat.new) fm.effects = all.effects(fm.ex, xlevels =

Code: > options("contrasts") $contrasts factor ordered "contr.treatment" "contr.poly" I want to change the first entry ONLY, without retyping "contr.poly". How do I do it? I have tried various possibilities and cannot get anything to work. I found out that the response to options("contrasts") has class

Full_Name: Dav Clark Version: 2.0.1 OS: OS X 10.3 Submission from: (NULL) (128.122.87.35) When the timepoints that reshape uses (in direction="long") are negative or fractional, the time label is assigned incorrectly. It is easier to give an example than to describe the problem abstractly: Assume you have a data.frame header with values related to peri-stimulus time like this:

Hi, i do have a dataframe representing data from a repeated experiment. PID is a subject identifier, Time are timepoints in an experiment which was repeated twice. For each subject and all three timepoints there are 2 sets of four values. df <- data.frame(PID = c(rep("A", 12), rep("B", 12), rep("C", 12)), Time = rep(c(0, 0, 0, 0, 30, 30, 30,

Dear R Community, I am trying to create an heatmap for the following set of data: ##example of data matrix o4 V1 V2 V3 V4 V5 V6 V7 V8 V9 V10 V11 V12 V13 V14 V15 V16 V17 V18 green 27 28 29 29 28 28 26 25 25 23 23 22 22 21 21 22 22 22 yellow 6 8 8 7 7 7 6 6 6 7 7 7 6 6 6 6 6 5 red 15 15 15 15 15 15 14 13 12 11 12 10 9 8 7 6 8 9 pink

Hi Folks, I have repeated measures for data on association time (under 2 acoustic condtions) in male and female frogs as they grow to adulthood (6 timepoints). Thus, two within-subject variables (Acoustic Condition: 2 levels, Timepoint: 6 levels) and one between-subject variable (Sex:male or female). I am pretty sure my distributions depart from normality but I would first like to simply run a

Hi, I'm having difficulty importing my textfile that looks something like this: #begin text file Timepoint 1 ObjectNumber Volume SurfaceArea 1 5.3 9.7 2 4.9 8.3 3 5.0 9.1 4 3.5 7.8 Timepoint 2 ObjectNumber Volume SurfaceArea 1 5.1

Hi, I posted the message below last week, but no answers, so I'm giving it another attempt in case somebody who would be able to help might have missed it and it has now dropped off the end of the list of mails. I am fairly new to R and still trying to figure out how it all works, and I have run into a few issues. I apologize in advance if my questions are a bit basic, I'm also no

Hello, I have a number of files output1.dat, output2.dat, ... , output20.dat, each of which monitors several variables over a fixed number of timepoints. From this I want to create a data frame which contains the mean value between all files, for each timepoint and each variable. The code below works, but it seems like I should be able to do the second part without a for loop. I played

dear list, i am running a within-design ANOVA with 4 factors (4,4,2 and 2 levels each). the last one is a time factor comprising two different treatment timepoints. i fit a mixed-effects model using lme and apply the anova function to the outcome. according to this analysis, there are highly significant main effect on the first and the time factor. i then checked the boxplots for the two 4-level

Hi, I cannot find a 'vectorized' solution to this 'for loop' kind of problem. Do you see a vectorized, fast-running solution? Objective: Take the value of X at each timepoint and calculate the corresponding value of Y. Leading 0's and all 1's for X are assigned to Y; otherwise Y is incremented by the number of 0's adjacent to the last 1. The frequency and

I have two points of collection across 20 subjects (pre and post for each), so 20 pairs of data points. I would like to plot the actual raw data points for each subject for both pre and post and connect lines between these two points (20 in all) to depict real change between the two timepoints. I have tried using stripchart which adequately plots the two lines of subject data points. Attempting

Dear all R users, I want to realize 800 000 ANOVAS and to store Sum of Squares of the effects. Here is an extract of my table data Product attribute subject rep t1 t2 t3 … t101 P1 A1 S1 R1 1 0 0 … 1 I want to realize 1 ANOVA per timepoint and per attribute, there are 101 timepoints and 8 attributes so I want to realize 808 ANOVAS. This will be an ANOVA with two factors : Here is one example:

Dear R Users, Am using lm() with contrasts as below. If I skip the contrasts() statement, I get the coefficient names to be > names(results$coef) [1] "(Intercept)" "VarAcat" "VarArat" "VarB" which are much more meaningful than ones based on integers. Can anyone tell me how to get R to keep the coefficient names based on the factor levels

(R.1.9.1; win2000) Since it's about the tenth time I had to write an "if" around this to catch the error ... Let's look at the line myfit<-lm(res~groupvar,data=Data) Here res is of numeric type and groupvar is a factor. On first sight, it would be logical that if groupvar had only one (single) level we would get: Error in "contrasts<-"(`*tmp*`, value =

Dear all, I would like to find a linear regression model for a rather large dataset (27 independent variables). However, when I run lm the following error is reported: > out <- lm(Result ~ AppealA + AppealsB + AppealC + AppealD + AppealE + Apply + ApplyAmount + Aprove + Closecase + Decidelocally + Healthassessment + HealthassessmentHealth + Postponedecision + Propertyassessment +

Hi all, I wonder if there is any way to calculate a moving average on an irregular time series, or use the rollapply function in zoo? I have a set of dates where I want to check if there has been an event 14 days prior to each time point in order to mark these timepoints for removal, and can't figure out a good way to do it. Many thanks in advance! Gustaf Example data:

Dear list members, I have a 2-factor ANOVA where the summary.lm output looks like this (using treatment contrasts): Value Std. Error t value Pr(>|t|) (Intercept) 0.0389 0.0220 1.7695 0.0817 as.factor(Block)1 0.0156 0.0066 2.3597 0.0215 as.factor(Block)2 -0.0018 0.0037 -0.4857 0.6289 as.factor(Block)3 -0.0007 0.0026 -0.2812 0.7795