Message-ID: <AANLkTimUe9yFhrcFWbNSFP0dmahJcvMMajrnLxsK=p-G@mail.gmail.com>
Date: 2010-11-17T19:23:05Z
From: Andrew Dolman
Subject: declaring the variables
In-Reply-To: <AANLkTinb=4QNuANDa43aBubNQDQNrvcbpiWd3C3a_d7p@mail.gmail.com>
Woops, sorry, yes glmer.
andydolman at gmail.com
On 17 November 2010 20:21, Douglas Bates <bates at stat.wisc.edu> wrote:
> There is a function glmm in the repeated package but I think the
> function meant here is glmer in the lme4 package, not glmm.
>
> On Wed, Nov 17, 2010 at 1:11 PM, Andrew Dolman <andydolman at gmail.com> wrote:
>> lmer or glmm, the distinction (from a user point of view) is like lm
>> vs glm. If you are using a Gaussian model then either will work. If
>> you want to use a non-gaussian model then you will need to use glmm.
>>
>>
>>
>> andydolman at gmail.com
>>
>>
>>
>> On 17 November 2010 19:50, Michael Larkin <mlarkin at rsmas.miami.edu> wrote:
>>> Awesome!? All three of you have been extremely helpful.? Thanks!
>>>
>>>
>>>
>>> I have a couple of follow-up questions.
>>>
>>>
>>>
>>> When I log transformed my catch data to make it normally (gaussian)
>>> distributed.? Therefore, I do have normally distributed random error terms.
>>> I will log transform the catch before I apply the model.
>>>
>>>
>>>
>>> I will do the declaring steps suggested by Petar where I declare the
>>> variables (Angler = factor, Season=factor, and tide phase = numeric).
>>>
>>>
>>>
>>> So by using (1 | Angler) in the model for my angler variable (i.e. Joe
>>> Smith, John Doe, ect) it makes this variable have a random intercept?
>>>
>>>
>>>
>>> My last question, from reading your emails I should pursue the glmm instead
>>> of the lmer function because of the random nature of my angler variable?
>>>
>>>
>>>
>>> Mike
>>>
>>>
>>>
>>>
>>>
>>>
>>
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>>
>