Displaying 5 results from an estimated 5 matches for "subj2".
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2013 Jun 07
1
Function nlme::lme in Ubuntu (but not Win or OS X): "Non-positive definite approximate variance-covariance"
...data=mydat1)
When I check the approximate variance-covariance matrix, I get:
> fm0$apVar
[1] "Non-positive definite approximate variance-covariance"
*However*, if I do the same on a Windows or a Mac OS X machine, I get:
> fm0$apVar
reStruct.subj1 reStruct.subj2 reStruct.subj3 reStruct.subj1
reStruct.subj1 1.952757e-01 3.130089e-01 5.766955e-01 -0.1034862377
reStruct.subj2 3.130089e-01 5.703211e-01 9.864047e-01 -0.1937902915
reStruct.subj3 5.766955e-01 9.864047e-01 1.861434e+00 -0.3303689957
reStruct.subj1 -1.034862e-01 -1.937903e-01...
2007 May 17
2
How to select specific rows from a data frame based on values
...-4 to +4, and I want to subset this data frame so that in the
resulting new dataframe, values of _all_ of these variables should
range between -3 and +3.
Let's say I have the following dataframe (it's a toy example with 4
individuals and 5 variables):
subj1 <- cbind(-4, -3, -1, -5, -7)
subj2 <- cbind(-2, -1, -1, -2, +2)
subj3 <- cbind(+2, +1, +2, +1, +2)
subj4 <- cbind(-4, -1, -2, +2, +1, +1)
mydf <- as.data.frame(rbind(subj1, subj2, subj3, subj4))
>From mydf, I want to generate a new dataframe (let's call it mydf1)
which will have records of only subj2 and subj3 i...
2011 Dec 23
1
Long jobs completing without output
...s,
Brendan Halpin
- code ---------------------------------------------------------------
library(arm)
library(foreign)
mlm <- read.dta("../workingdata.dta")
attach(mlm)
gender <- as.factor(stu_gend)
yr <- year - 1998
failure <- (lmer(fail ~
1 + cao + subj1 + subj2 + subj3 + gender + yr + ageentry + as.factor(yrs5)
+ modsize + meancao + depfemr + (1|deptno) + (1|modinst) + (1|ulid) ,
na.action = na.exclude, family = binomial (link="logit")))
display(failure, digits=5, detail=TRUE)
-----------------------------------...
2004 Jan 15
1
nlme vs aov with Error() for an ANCOVA
...action-time 'rt'. For
'rt' I have repeated measurements, since each subject did 12 different
tasks.
-> so it can be seen as an ANCOVA
subject age.group bold rt
subj1 0 0.08 0.234
subj1 0 0.05 0.124
..
subj1 0 0.07 0.743
subj2 0 0.06 0.234
subj2 0 0.02 0.183
..
subj2 0 0.05 0.532
subjn 1 0.09 0.234
subjn 1 0.06 0.155
..
subjn 1 0.07 0.632
I decided to use the nlme library:
patrizia.lme <- lme(bold ~ rt*...
2007 Apr 13
2
replicates in repeated ANOVA
...Group = factor(c(rep("Treat",18),rep("Control",18))))
> rt.df
rt rep prepost subj Group
1 287 rep1 pre subj1 Treat
2 283 rep2 pre subj1 Treat
3 261 rep3 pre subj1 Treat
4 298 rep1 post subj1 Treat
5 302 rep2 post subj1 Treat
6 280 rep3 post subj1 Treat
7 211 rep1 pre subj2 Treat
8 272 rep2 pre subj2 Treat
9 222 rep3 pre subj2 Treat
10 285 rep1 post subj2 Treat
11 253 rep2 post subj2 Treat
12 252 rep3 post subj2 Treat
13 266 rep1 pre subj3 Treat
14 252 rep2 pre subj3 Treat
15 287 rep3 pre subj3 Treat
16 266 rep1 post subj3 Treat
17 255 rep2 post subj3 Treat...