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Print method for summary GALAMM fits

Usage

# S3 method for class 'summary.galamm'
print(x, digits = max(3, getOption("digits") - 3), ...)

Arguments

x

An object of class summary.galamm returned from summary.galamm.

digits

Number of digits to present in outputs.

...

Further arguments passed on to other methods. Currently used by stats::printCoefmat for printing approximate significance of smooth terms.

Value

Summary printed to screen. Invisibly returns the argument x.

References

Bates DM, Mächler M, Bolker B, Walker S (2015). “Fitting Linear Mixed-Effects Models Using Lme4.” Journal of Statistical Software, 67(1), 1–48. ISSN 1548-7660, doi:10.18637/jss.v067.i01 .

See also

summary.galamm() for the summary function and print() for the generic function.

Other summary functions: anova.galamm(), plot.galamm(), plot_smooth.galamm(), summary.galamm()

Author

Some of the code for producing summary information has been derived from the summary methods of mgcv (author: Simon Wood) and lme4 (Bates et al. 2015) (authors: Douglas M. Bates, Martin Maechler, Ben Bolker, and Steve Walker).

Examples

# Linear mixed model with heteroscedastic residuals
mod <- galamm(
  formula = y ~ x + (1 | id),
  weights = ~ (1 | item),
  data = hsced
)

summary(mod)
#> GALAMM fit by maximum marginal likelihood.
#> Formula: y ~ x + (1 | id)
#>    Data: hsced
#> Weights: ~(1 | item)
#> 
#>      AIC      BIC   logLik deviance df.resid 
#>   4126.3   4151.7  -2058.1   4116.3     1195 
#> 
#> Scaled residuals: 
#>     Min      1Q  Median      3Q     Max 
#> -5.6545 -0.7105  0.0286  0.6827  4.3261 
#> 
#> Random effects:
#>  Groups   Name        Variance Std.Dev.
#>  id       (Intercept) 0.9880   0.9940  
#>  Residual             0.9597   0.9796  
#> Number of obs: 1200, groups:  id, 200
#> 
#> Variance function:
#>     1     2 
#> 1.000 1.995 
#> 
#> Fixed effects:
#>             Estimate Std. Error t value  Pr(>|t|)
#> (Intercept)   0.1289     0.0992   1.299 1.938e-01
#> x             0.7062     0.1213   5.822 5.819e-09
#> 
#>