[R-sig-ME] lme4: Parameter contrasts?

[Ken Beath]

A parametric bootstrap should be easy to achieve using the simulate method
and the parametric bootstrap from the boot package.

On 6 February 2015 at 12:28, Carpenter, Tom <tcarpenter at spu.edu> wrote:

> Thanks! I was also hoping there might be an easy way to bootstrap it.
>
> Tom Carpenter, Ph.D.
> Instructor of Psychology
> Seattle Pacific University
> 3307 3rd Ave W. Suite 107,
> Seattle, WA, 98119
> tcarpenter at spu.edu<mailto:tcarpenter at spu.edu>
> Office: (206) 281-2916
> Mobile: (206) 276-1541
> Fax: (206) 281-2695
>
> On Feb 5, 2015, at 5:43 AM, Steven J. Pierce <pierces1 at msu.edu<mailto:
> pierces1 at msu.edu>> wrote:
>
> You might want to check out whether the multcomp package would handle
> this. Bretz et al. (2010) describes use of the package.
>
> Bretz, F., Hothorn, T., & Westfall, P. (2010). Multiple comparisons using
> R. Boca Raton, FL: Chapman & Hall/CRC.
>
>
> Steven J. Pierce, Ph.D.
> Associate Director
> Center for Statistical Training & Consulting (CSTAT)
> Michigan State University
>
> -----Original Message-----
> From: Carpenter, Tom [mailto:tcarpenter at spu.edu]
> Sent: Wednesday, February 04, 2015 8:25 PM
> To: r-sig-mixed-models at r-project.org<mailto:
> r-sig-mixed-models at r-project.org>
> Subject: [R-sig-ME] lme4: Parameter contrasts?
>
> Hoping someone has some advice here. I recently made the switch from using
> HLM to lmer. I know that in HLM, you could do a parameter contrast (e.g.,
> contrast two fixed effects against each other and test the significance of
> the contrast). I was curious if anyone knows how to do this in R? I have
> run a model in lmer (with standardized predictors) and wish to see if one
> fixed effect is significantly larger (more predictive) than other fixed
> effect.
>
> If that is not possible in lme4, does anyone have any advice for how to
> bootstrap it? I?m fine letting the thing run overnight to get a 95% CI if
> anyone has any suggestions.
>
> Tom Carpenter, Ph.D.
> Instructor of Psychology
> Seattle Pacific University
> 3307 3rd Ave W. Suite 107,
> Seattle, WA, 98119
> tcarpenter at spu.edu<mailto:tcarpenter at spu.edu><mailto:tcarpenter at spu.edu>
> Office: (206) 281-2916
> Fax: (206) 281-2695
>
>
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-- 

*Ken Beath*
Lecturer
Statistics Department
MACQUARIE UNIVERSITY NSW 2109, Australia

Phone: +61 (0)2 9850 8516

Building E4A, room 526
http://stat.mq.edu.au/our_staff/staff_-_alphabetical/staff/beath,_ken/

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