Extracts the square root of the dispersion parameter(s) from an object of
class galamm, returned from galamm. In the case of
conditionally Gaussian responses, this is the residual standard deviation.
When there are multiple dispersion parameters, e.g., with mixed response
type models, the square root of all of them are returned in a numeric vector.
Usage
# S3 method for class 'galamm'
sigma(object, ...)Arguments
- object
An object of class
galamm, returned fromgalamm.- ...
Optional parameters passed on to other methods. Currently not used.
See also
Other details of model fit:
VarCorr(),
coef.galamm(),
confint.galamm(),
deviance.galamm(),
factor_loadings.galamm(),
family.galamm(),
fitted.galamm(),
fixef(),
formula.galamm(),
llikAIC(),
logLik.galamm(),
nobs.galamm(),
predict.galamm(),
print.VarCorr.galamm(),
ranef.galamm(),
residuals.galamm(),
response(),
vcov.galamm()
Examples
# Linear mixed model with heteroscedastic residuals
mod <- galamm(
formula = y ~ x + (1 | id),
weights = ~ (1 | item),
data = hsced
)
# Extract residual standard deviation.
sigma(mod)
#> [1] 0.9796427
# The residual standard deviation applies to the base case. The variance
# function shown in the model output shows the estimated multiplier for
# various grouping levels:
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
#>
#>