search for: effct

Displaying 5 results from an estimated 5 matches for "effct".

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1999 May 15
2
vsize and nsize
I am running R version ??? under Redhat 5.2. It seems as though the --nsize object has no effct on the size of the allocated Ncells as determined using gc(). Yes, I have that much data.... That is if I envoke R with R --vsize 100 --nsize 5000000 then type gc() I get free total Ncells 92202 200000 Vcells 12928414 13107200 Thanks Tony Long Ecology and Evolutionary Biology Steinhaus...
2011 Apr 22
1
Survival analysis: same subject with multiple treatments and experience multiple events
Hi there, I need some help to figure out what is the proper model in survival analysis for my data. Subjects were randomized to 3 treatments in trial 1, some of them experience the event during the trial; After period of time those subjects were randomized to 3 treatments again in trial 2, but different from what they got in 1st trial, some of them experience the event during the 2nd trial (I
2009 Dec 01
1
LMER: How to specify Random Effects
I saw different specifications for Random Effects and I'm confused about the use of "/" and the use of "(0+...|)" . Let say we have a nested structure where some countries have some several plants in different states and we measure the reaction to a drug. The list of Countries = USA, France, Italy The States for USA = Michigan, Florida, California The States for France
2011 Feb 21
2
self.prepend_view_path - am I missing something
I have an app that varies its content based upon the domain from which it is being accessed. Some of the domain characteristics are supported in the model but it is easier varying static text in the views and then sharing the form templates via partials etc. Rails 2.3.10 and looking at the documentation at
2007 Jul 21
0
Binomial multi-level (hierarchical) modelling [partly stats question, not completely R related]
...s=total, data=d1) But I don't think I am using this properly and can't seem to determine the variance due to the different hierarchical terms. Can one use the interaction of country*region instead of using a mixed model (where presumably country would be a fixed effect and region a random effct?) Any pointers much appreciated! Many thanks, Mark P.S. while experimenting while creating the line: > me1 <- lmer(prop ~ country + (1|region) + (0+country|region), family='binomial', weights=total, data=d1) I accidentally pressed <RETURN> and issued the following command:...