r2_nakagawa | R Documentation |
Compute the marginal and conditional r-squared value for mixed effects models with complex random effects structures.
r2_nakagawa(
model,
by_group = FALSE,
tolerance = 1e-05,
ci = NULL,
iterations = 100,
ci_method = NULL,
verbose = TRUE,
...
)
model |
A mixed effects model. |
by_group |
Logical, if |
tolerance |
Tolerance for singularity check of random effects, to decide
whether to compute random effect variances for the conditional r-squared
or not. Indicates up to which value the convergence result is accepted. When
|
ci |
Confidence resp. credible interval level. For |
iterations |
Number of bootstrap-replicates when computing confidence intervals for the ICC or R2. |
ci_method |
Character string, indicating the bootstrap-method. Should
be |
verbose |
Toggle warnings and messages. |
... |
Arguments passed down to |
Marginal and conditional r-squared values for mixed models are calculated
based on Nakagawa et al. (2017). For more details on the computation of
the variances, see ?insight::get_variance
. The random effect variances are
actually the mean random effect variances, thus the r-squared value is also
appropriate for mixed models with random slopes or nested random effects
(see Johnson, 2014).
Conditional R2: takes both the fixed and random effects into account.
Marginal R2: considers only the variance of the fixed effects.
The contribution of random effects can be deduced by subtracting the
marginal R2 from the conditional R2 or by computing the icc()
.
A list with the conditional and marginal R2 values.
Hox, J. J. (2010). Multilevel analysis: techniques and applications (2nd ed). New York: Routledge.
Johnson, P. C. D. (2014). Extension of Nakagawa and Schielzeth’s R2 GLMM to random slopes models. Methods in Ecology and Evolution, 5(9), 944–946. \Sexpr[results=rd]{tools:::Rd_expr_doi("10.1111/2041-210X.12225")}
Nakagawa, S., and Schielzeth, H. (2013). A general and simple method for obtaining R2 from generalized linear mixed-effects models. Methods in Ecology and Evolution, 4(2), 133–142. \Sexpr[results=rd]{tools:::Rd_expr_doi("10.1111/j.2041-210x.2012.00261.x")}
Nakagawa, S., Johnson, P. C. D., and Schielzeth, H. (2017). The coefficient of determination R2 and intra-class correlation coefficient from generalized linear mixed-effects models revisited and expanded. Journal of The Royal Society Interface, 14(134), 20170213.
model <- lme4::lmer(Sepal.Length ~ Petal.Length + (1 | Species), data = iris)
r2_nakagawa(model)
r2_nakagawa(model, by_group = TRUE)
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