Displaying 4 results from an estimated 4 matches for "study1dat".
2006 Apr 22
1
Missing values detected when there are no missing values
...iables looked like I ran the summary command. One variable had a
large number of missing values 54/92. For some reason, all subsequent 74
variables are reported as having 92 NA values, irrespective of whether the
original csv variable was complete or not.
Below are the commands I ran:
> study1dat <- read.csv("c:\\study1r.csv",header=T)
> attach(study1dat)
> names(study1dat)
> summary(study1dat)
The second puzzling issue, is that one variable with no missing values is
reported in R as having 3 missing values, whereas there are no missing
values in the csv file.
Th...
2006 Jun 18
1
how to successfully remove missing values for a repeated measures analysis
...ists of 92 rows (1 row per participant) x 186 variables.
The steps of the analysis undertaken are outlined below (#). Any assistance
is appreciated in relation to how to remove the missing values so the
analysis is run. Feedback regarding the prior steps is also welcomed .
Bob Green
#Step 1
study1dat <- read.csv("c:\\study1.csv",header=T)
attach (study1dat)
outcome <- c(t1frq, t2frq,t3frq,t4frq)
grp <- factor( rep(group, 2,length=368) )
time <- gl(4,92,length=368)
subject <- gl(92,1,length=368)
data.frame(subject, grp, time, outcome)
# there are 3 missing values in $o...
2006 May 08
1
performing functions on variables of different length
...s appeared to
have the same number of values . However, when I ran the length command
this wasn't the case:
length(outcome)
[1] 368
> length(grp)
[1] 184
> length(subject)
[1] 92
> length(time)
[1] 184
Below is the syntax I have been using and the date frame that I generated -
study1dat <- read.csv("c:\\study1rb.csv",header=T)
attach (study1dat)
outcome <- c(t1freq, t2freq,t3freq,t4freq)
grp <- factor( rep(group, 2) )
time <- gl(4, 46)
subject <- gl(46,1,92)
data.frame(subject, grp, time, outcome)
subject grp time outcome
1 1 0 1...
2006 May 02
0
Enquiry regarding Apply
I want to compute a new variable (newvar) based on the values of two other
variables (t1freq, t2freq).The two variables (t1freq,t2freq) are contained
in a dataframe - study1dat <- read.csv("c:\\study1rb.csv",header=T) .
I gather this computation can be done using Apply and I have run the
following example from the help menu
## Compute row and column sums for a matrix:
x <- cbind(x1 = 3, x2 = c(4:1, 2:5))
dimnames(x)[[1]] <- letters[1:8]...