search for: timef

...11","V13","V14","V15","V16","V17","V18","V19","V20","V21","V22","V23","V24","V25")) colnames(dta1)[1] = "schoolNR" dta2 = dta1[order(dta1$id),] head(dta2) timef = factor(dta2$time) summary(mdl1l <- lme(score~timef-1, dta2, ~timef-1|schoolNR/id,,,,"ML")) summary(mdl1g <- gls(score~timef-1, dta2, corCompSymm(, ~timef|schoolNR/id), varIdent(, ~1|id*timef),,"ML"))

...need to take the residual and multiply it with these like c(0.2235, 0.2235*1.3473, 0.2235*1.0195) or any other form that I dont know of? Thanks Toby Linear mixed-effects model fit by REML Data: dtaa AIC BIC logLik -788.783 -692.5656 409.3915 Random effects: Formula: ~timef - 1 | orgid Structure: General positive-definite, Log-Cholesky parametrization StdDev Corr timef1 0.04398482 timef1 timef2 timef2 0.07910354 1 timef3 0.03648411 1 1 Residual 0.22350583 Correlation Structure: General Formula: ~1 | orgid/id Parameter estimate(s): Cor...

Dear R-Users, I am currently working with LME to analyse repeated measures data. I encounter a problem when including both a random effect and a correlation structure with different grouping levels into the LME model. The error message is: Error in lme.formula(diameter ~ flowers*timef + competition*timef + population*timef, : Incompatible formulas for groups in "random" and "correlation". The syntax for the model I want to calculate is as follows: model<- lme(diameter ~ flowers*timef + competition*timef + population*timef, data= Timeseries,...

Can anyone help explain to me why the two codes below have different result? I thought I can use log(time)~. to replace log(time)~dist+climb+timef.I am using CVlm from DAAG package. I think nihills is preloaded with the package. Thanks in advance. > CVlm(df=nihills, form.lm=formula(log(time)~.),plotit="Observed",m=2)Analysis of Variance Table Response: log(time) Df Sum Sq Mean Sq F value Pr(>F) dist 1 6.34...

...ove redundant columns 1 through 6 and column 11 (which I won't need, since I know they are going to have the same value), I don't get the error: > hills2000 <- races2000[races2000$type == 'hill', -c(1:6,11)] > hills2000 dist climb time timef Tiso Carnethy 6.00 2500 0.7822222 0.9191667 [...] Cornalees 5.50 800 0.6183333 NA [...] What is causing the error with my original subsetting? I speculated it was related to the NA values, but there is an NA in the resulting hills2000, corresponding to the Corna...

I have a new device that takes measurements anywhere from every second, to every 15 minutes (depending on changes). The matrix has a date, time and Y column (Y is the measurement). For three days it is 25,000 rows. How do I average the measurements by every 30 minutes so my matrix is 48 rows per day? I have been working on this and cannot figure out a simple method. Any ideas? Thank you. ----- In

...; 1 through 6 and column 11 (which I won't need, since I know they are > going to have the same value), I don't get the error: > > > hills2000 <- races2000[races2000$type == 'hill', -c(1:6,11)] > > hills2000 > dist climb time timef > Tiso Carnethy 6.00 2500 0.7822222 0.9191667 > [...] > Cornalees 5.50 800 0.6183333 NA > [...] > > What is causing the error with my original subsetting? I speculated it > was related to the NA values, but there is an NA in the resulting &gt...