[R] Urgent - I really need some help lme4 model avg Estimates

[Bert Gunter]

... perhaps also worth mentioning:

"The combination of some data and an aching desire for an answer does
not ensure that a reasonable answer can be extracted from a given body
of data. "
-- John Tukey

-- Bert

On Tue, Mar 27, 2012 at 7:55 PM, Dragonwalker
<dragonwalkerart at hotmail.com> wrote:
> Hello all,
> If someone could take a little time to help me then I would be very
> grateful.
> I studied piping plovers last summer. I watched each chick within a brood
> for 5 minutes and recorded behaviour, habitat use and foraging rate.
> There were two Sites, the first with 4 broods and the second with 3 broods.
> http://r.789695.n4.nabble.com/file/n4511178/Table_PP_Maslo_et_al.png As the
> data within a brood is non-independent and the fact that there were so few,
> then conventional statistical tests were of little use. I therefore spent a
> couple of months looking at mixed-models to allow me to use all the data for
> each day and use (1|Brood) as a random effect.
>
> At first i struggled with what models meant, but last week they 'sort of '
> clicked and realised how to run them and how to weigh which models were the
> best (using AICc).
> As I had a number of factors/covariates that I wanted to look at I learned
> to use the dredge command in the MuMIn package from an a priori global model
> and decided to model average the models with a delta<2.
>
> I have two main questions:
> I was looking at similar research that also looked at models and they also
> came up with model average estimates and CIs for each variable and factor.
> They ended up with one table showing the top so many models with their AICc,
> delta and weights and then another table showing the model average Estimates
> and CIs for each factor and co-variate and also the Intercept.   Each
> category within each variable was shown (I have attached an image of the
> table - the heading does not seem to match what is shown however).
> Their explanation of the variables was as follows:
> "A second model including these variables and wind speed reported a DAICc
> score <2; therefore, we model- averaged the parameter estimates included in
> these 2 best models (Table 3). Of the 5 habitats in which we observed
> plovers feeding, effect size was highest at artificial tidal ponds (5.52),
> followed by the intertidal zone (3.97). Positive effects of ephemeral pools
> (2.65) and bay shores (2.32) on adult foraging rates were 48% and 42% lower
> than artificial ponds,
> respectively. Conversely, sand flats (-2.30) had an equal but opposite
> effect on foraging rate, when compared to bay
> shores. The results also indicated that foraging rate was highest for adults
> during the post-breeding stage. In addition,
> vehicles had a 2.3 times larger effect on foraging adults than people.
> Finally, foraging rates during low tide were
> higher than at high tide by a factor of 2.5, as would be expected."
>
> As you can see, their explanation seems to suggest that all values are
> comparable e.g. vehicles and people.
>
> When I ran the model average I also got an Intercept estimate but only the
> second and beyond categorical Estimates were shown (e.g. if one factor was
> high tide, low tide, then only the estimate for low tide was shown,
> obviously an estimate of difference between the two).
> I asked on stats.stackexchange and they suggested just adding -1 to the end
> of the model, but although this worked, the estimates became much bigger to
> compensate for there being no intercept and although the difference between
> the Estimates were the same for 'within factor', the 'among factor'
> variables seemed to change (bigger differences between), along with the
> p-values for each group. In addition there was, of course, no intercept.
>
> I am therefore wondering whether anyone knows how I may be able to preserve
> the initial Estimates but still get the missing values (obviously the other
> researchers seemed to have done this as they still have an intercept and
> comparable estimates).
>
> This is my most important issue right now, but if someone has a moment,
> could you also tell me whether I should use the p-values as well, or should
> i just stick with explaining the magnitude of the effects, their direction
> and their Relative Importance. i want to keep it at a level that I can
> understand.
>
> Thank you in advance. I know everyone is busy but I would be very grateful
> for a prompt response if at all possible.
>
> Sincerely.
>
> --
> View this message in context: http://r.789695.n4.nabble.com/Urgent-I-really-need-some-help-lme4-model-avg-Estimates-tp4511178p4511178.html
> Sent from the R help mailing list archive at Nabble.com.
>
> ______________________________________________
> R-help at r-project.org mailing list
> https://stat.ethz.ch/mailman/listinfo/r-help
> PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
> and provide commented, minimal, self-contained, reproducible code.



-- 

Bert Gunter
Genentech Nonclinical Biostatistics

Internal Contact Info:
Phone: 467-7374
Website:
http://pharmadevelopment.roche.com/index/pdb/pdb-functional-groups/pdb-biostatistics/pdb-ncb-home.htm