Displaying 5 results from an estimated 5 matches for "392.5".
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3.2.5
2009 Apr 30
1
Overlaying graphs from different datasets with ggplot
Dear R-users,
I recently began using the ggplot2 package and I am still in the process of
getting used to it.
My goal would be to plot on the same grid a number of curves derived from
two distinct datasets. The first dataset (called molten.data) looks like
this :
Column names : Perc, Week, Weight
P10 21 333.3554
P90 21 486.0480
P10 22 452.6347
P90 22 563.8263
P10 23 575.0960
P90
2009 Oct 19
1
Reposting various problems with two-way anova, lme, etc.
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
2009 Oct 15
0
Two way anova repeated measures and post hoc testing - several questions
Hi,
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 statistics wizard, so part of my problem my be a more
fundamental lack of knowledge in the field.
I have a dataset that looks something like this:
Week Subj Group Readout
0 1 A 352.2
1 1 A
2013 Aug 30
3
Memory usage bar plot
Hi,
I haven't tried the code yet. Is there a way to parse this data
using R and create bar plots so that each program's 'RAM used' figures are
grouped together.
So 'uuidd' bars will be together. The data will have about 50 sets. So if
there are 100 processes each will have about 50 bars.
What is the recommended way to graph these big barplots ? I am looking
2011 Nov 11
2
Estimating IRT models by using nlme() function
Hi,
I have a question about estimating IRT models by using nlme, not just rasch
model, but also other models.
Behavior Research Methods
<http://www.springerlink.com/content/1554-351x/> Volume
37, Number 2 <http://www.springerlink.com/content/1554-351x/37/2/>, 202-218,
DOI: 10.3758/BF03192688
Using SAS PROC NLMIXED to fit item response theory models (2005). Ching-Fan