[R-sig-ME] Using lme4 with very limited number of observations makes sense?

[Ken Beath]

Having repetititions as a random effect seems unusual, as it doesn't
satisfy the assumptions, and estimating with only 7 groups may have
problems. I would look at it as a fixed effect, and possibly it would be
found that teh ordering does not have an effect. Averaging can be OK but
can also have all sorts of problems when the number of responses
varies.With the fixed effect there are 6 additional parameters but almost 7
times as much data,

What is more worrying is (1+condition|subject) + (1+context|subject) which
seems to include the 1|subject random effect twice.
(1+context+condition|subject)
may avoid the problems but will have a correlation between the random
effects for context and condition that you may not want. Probably you do
want them, but if you don't I'm not certain how to get rid of them.

Starting off with 3 way interactions like PATvsCTR * condition * context
can be a problem if there is not a lot of data. Try to get something
simpler like main effects only working and then try something more
complicated.



On 28 April 2015 at 23:38, Massimiliano Mario Iraci <
massimiliano.iraci at unisalento.it> wrote:

> Dear all,
>
> my name is Massimiliano Iraci, I am a PhD student at the University of
> Salento (Lecce, Italy) and University of Cologne (Germany). My PhD is on
> Phonetics and Phonology and I am working on the kinematics of speech in
> Parkinson's Disease.
>
> I am very fresh with statistics and recently I am even switching from SPSS
> to R, especially working with linear mixed models (lme4 package).
> Unfortunately I am having some doubts about the use of this model with my
> data.
>
> In my field, the data acquisition is much complicated because of the
> instruments, so eventually I always have few data for few subjects. So, in
> order to power-up my data, I am used to record more (5-7) repetitions of
> any item of interest.
>
> So, for instance, if I want to focus on the displacement of the lower lip
> during the production of a bilabial speech gesture, I consider the
> voiced/unvoiced condition, in 2 contexts (singleton/geminate). Thus I will
> have 7 repetitions of the same item x 2 conditions (voiced/unvoiced) x 2
> contexts (singleton/geminate) x 10 subjects (5 pathological + 5 controls).
> I fit the model as follows:
> lip_displacement ~ PATvsCTR * condition * context + (1|repetitions) +
> (1+condition|subject) + (1+context|subject)
>
> I must highlight that:
> - I don't have always 7 repetitions for any item: some subjects were able
> to produce 5, some 6, some 7 differing from item to item (so generally
> number of "same items" range from 5 to 7);
> - 'repetitions' is a variable reporting the cardinal number associated to
> the chronological order of the repetitions recorded (so ranging from 1 to
> 7)
>
> This fit very often generates several errors and warnings ("large
> eigenvalue ratio"; "degenerate Hessian with 1 negative eigenvalues"; etc.)
> and if plotting the distribution of fitted/residuals I see stripes clearly
> because of the repetitions.
>
> Finally the questions are:
> - could the repetitions be a problem for the model? Could it better to
> work with an average of the repetitions in order to have only 1 value for
> each item?
> - if the previous is true, does it make sense to compare such a limited
> number of values in such a limited number of subjects with this model?
>
> I am sorry for my limited knowledge in statics. I would be really grateful
> if you could help me to shed light on the problem. Thank you very much in
> advance for your help.
>
> I look forward to hearing from you.
> Kind regards,
>
> Massimiliano
>
>
>
> ===============================================================
>
> Massimiliano Mario Iraci
> PhD student
>
> CRIL (Intedisciplinary Center for Research on Language) &
> DReAM (Laboratory of Research Applied to Medicine)
> University of Salento & Local Health Service (ASL Lecce)
> c/o Vito Fazzi Hospital
> Piazza Filippo Muratore - 73100 - Lecce (Italy)
>
> web: http://www.cril.unisalento.it/en/staff_details.php?id=123
> tel: 0039 - 0832 335008
>
> _______________________________________________
> R-sig-mixed-models at r-project.org mailing list
> https://stat.ethz.ch/mailman/listinfo/r-sig-mixed-models
>



-- 

*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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