[please keep r-sig-mixed-models in the Cc: list when replying] What is V1, what level does it vary at (among vs within participants), and what are you interested in comparing/testing with this model? Note that Barr et al 2013's "keep it maximal" protocol would suggest that you fit (item|Participant) (but ... without factor-analytic models or some form of regularization this will never actually be practical, as you'd be trying to estimate a 28x28 covariance matrix (= 378 parameters) from 53 participants ... you usually have to choose from some more restricted set of choices [independence, compound symmetry, etc.] On Wed, Jan 22, 2020 at 12:36 PM Souheyla GHEBGHOUB
<souheyla.ghebghoub at gmail.com> wrote:
Hi Ben, I am not comparing between participants, it is a within group design, each participant answered 28 items My model is glmer ( score~ V1 + (1|Participant) + (1|item) ?? Thank you, Sou On Wed, 22 Jan 2020 at 16:21, Ben Bolker <bbolker at gmail.com> wrote:
It's going to depend on whether the parameters you're trying to estimate are capturing processes that vary at the level of participants or at the level of observations. For example, if you wanted to compare trends over time among groups of participants, each measured multiple times (i.e. a random-slopes model with a fixed-effect interaction between treatment and slope) you'd need to consider the number of participants. (In a sense the answer to this question goes back to the classical experimental design bestiaries of nested vs randomized block vs split-plot vs ... and deciding what the "denominator degrees of freedom" are supposed to be in each case/for each test of interest). On Wed, Jan 22, 2020 at 9:45 AM Thierry Onkelinx via R-sig-mixed-models <r-sig-mixed-models at r-project.org> wrote:
Dear Sou, I'd suggest at least 10-15 observation per **parameter**. Categorical variables with more than two levels require more than one parameter. An interaction between two continuous variable requires 3 parameters (2 main effect + 1 interaction). Don't forget to count the hyperparameters of the random effects. Best regards, Thierry ir. Thierry Onkelinx Statisticus / Statistician Vlaamse Overheid / Government of Flanders INSTITUUT VOOR NATUUR- EN BOSONDERZOEK / RESEARCH INSTITUTE FOR NATURE AND FOREST Team Biometrie & Kwaliteitszorg / Team Biometrics & Quality Assurance thierry.onkelinx at inbo.be Havenlaan 88 bus 73, 1000 Brussel www.inbo.be /////////////////////////////////////////////////////////////////////////////////////////// To call in the statistician after the experiment is done may be no more than asking him to perform a post-mortem examination: he may be able to say what the experiment died of. ~ Sir Ronald Aylmer Fisher The plural of anecdote is not data. ~ Roger Brinner 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 /////////////////////////////////////////////////////////////////////////////////////////// <https://www.inbo.be> Op wo 22 jan. 2020 om 14:55 schreef Souheyla GHEBGHOUB < souheyla.ghebghoub at gmail.com>:
Hi,
In Field (2012) we need 10-15 *participants* per variable for regression,
in Levshina (2015) we need 10-15 *observations* per variable.
Is it participant or observation? I am so confused as I have 53
participants and 1484 observations.
Thank you,
Sou
PhD in Education
University of York
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