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For all analyses, participant ID (including intercept) was modelled as a random factor.
In these two cases, the results are reported for GLMMs that do not include slope as a random factor.
Data was analysed using linear mixed effect models with cow as a random factor: *P < 0.05, **P < 0.01.
To adjust for repeated measurements in all other analysis we included animal ID as a random factor in a mixed model using the MIXED procedure in SAS.
The model included interactions and Participant was used as a random factor.
To avoid pseudoreplications, identification of the photo was included as a random factor in the model.
Participants were specified as a random factor to control for their associated intraclass correlation.
Tree was included as a random factor.
The 20 maternal trees were used as a random factor.
We tested the covariance of age as a random factor.
Individual was always set as a random factor.
More suggestions(17)
as a random intercept
as a random coil
as a random sampling
as a random choice
as a random mutation
as a big factor
as a likely factor
as a random event
as a random walk
as a random test
as a differentiating factor
as a central factor
as a categorical factor
as a pivotal factor
as a constant factor
as a political factor
as a random effect
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