[R-sig-ME] glmmTMB- fitting splines

dani orchidn @ending from live@com
Tue May 22 18:29:07 CEST 2018


Hi David,


Thanks. I am not sure Hmisc works with random effects - I will check it out, though.


Best,

D


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________________________________
From: Farrar, David <Farrar.David at epa.gov>
Sent: Tuesday, May 22, 2018 5:59 AM
To: dani; John Maindonald
Cc: r-sig-mixed-models at r-project.org
Subject: RE: [R-sig-ME] glmmTMB- fitting splines

I think I used functions from Hmisc, the last time I did regression splines.
(I did not use penalized splines - I specified enough knots to give an appropriate range of shapes, and used the default knot placements.)
David

-----Original Message-----
From: R-sig-mixed-models [mailto:r-sig-mixed-models-bounces at r-project.org] On Behalf Of dani
Sent: Monday, May 21, 2018 10:41 PM
To: John Maindonald <john.maindonald at anu.edu.au>
Cc: r-sig-mixed-models at r-project.org
Subject: Re: [R-sig-ME] glmmTMB- fitting splines

Hi John,

Thank you so much! This is very helpful! I managed to run it  but I am not sure how to interpret the results as I get this:


# Conditional model:
#                                                    Estimate Std. Error z value Pr(>|z|)
# (Intercept)                             -8.40461    1.58077  -5.317 1.06e-07 ***
# splines::ns(newage, 2)1     -1.89262    0.57246  -3.306 0.000946 ***
# splines::ns(newage, 2)2      0.10296    0.47268   0.218 0.827575


I am not sure what to make of the two different spline results.

Best regards,

D

________________________________
From: John Maindonald <john.maindonald at anu.edu.au>
Sent: Monday, May 21, 2018 7:10 PM
To: dani
Cc: r-sig-mixed-models at r-project.org
Subject: Re: [R-sig-ME] glmmTMB- fitting splines

There is an example at http://www.rpubs.com/johnhm/Overdispersed
See Section 2.2 .


John Maindonald             email: john.maindonald at anu.edu.au<mailto:john.maindonald at anu.edu.au>

On 22/05/2018, at 11:36, dani <orchidn at live.com<mailto:orchidn at live.com>> wrote:




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