dhewitt wrote:I know that Jeff Laake has provided a package RMark that links R and MARK. That's excellent, and if I'm reading the stars correctly, that will be the future.
Probably not. It would be 'the future' if everyone used R (in my Department, <5% of folks I can think of do...), and/or if it were 'generally' easier to use RMark as the interface to MARK (it is easier in some specific applications, but not at all for the MARK user at the beginning or intermediate level, since you're often simply substituting the visual complexity of building a DM graphically in MARK with the often obtuse and arcane conventions of the R language - it is not hard to come up with examples of RMark code - or R in general - which are virtually impenetrable to someone without a significant R background).
I can teach someone to use the 'classic' MARK interface even if they have no background in R (or any other statistical programming environment). Further, using the classical interface - especially the graphical DM - forces the user to actually think about what they're doing (you learn a heck of a lot more about linear models by actually confronting the DM directly, rather than through some 'canned' function). For highly experienced analysts (like Jeff, obviously), this isn't useful, and is in fact annoying - RMark lets you dispense with building the DM manually.
But, to learn to use RMark effectively, you need to learn to be fairly proficient in R. Perhaps that is value added, but it is an extra step.
RMark is outstanding - I use it fairly often. It is an extremely useful addition to the 'arsenal' for working with data from marked individuals.