Summarizes the results of a model fit by the lme() function of the
nlme package.
Arguments
- model
name of
lme()model object.- dig
number of decimals to print in output.
Value
Output summary of lme() model object.
Details
Summarizes the results of a model fit by the lme() function of the
nlme package. Includes summary of parameters, pseudo-r-squared, and
whether model is positive definite.
Examples
# Fit Model
library("nlme")
model <- lme(distance ~ age + Sex, data = Orthodont, random = ~ 1 + age)
# Model Summary
summary(model)
#> Linear mixed-effects model fit by REML
#> Data: Orthodont
#> AIC BIC logLik
#> 449.2339 467.8116 -217.6169
#>
#> Random effects:
#> Formula: ~1 + age | Subject
#> Structure: General positive-definite, Log-Cholesky parametrization
#> StdDev Corr
#> (Intercept) 2.7970227 (Intr)
#> age 0.2264274 -0.766
#> Residual 1.3100398
#>
#> Fixed effects: distance ~ age + Sex
#> Value Std.Error DF t-value p-value
#> (Intercept) 17.635200 0.8862449 80 19.898788 0.000
#> age 0.660185 0.0712532 80 9.265338 0.000
#> SexFemale -2.145492 0.7574539 25 -2.832504 0.009
#> Correlation:
#> (Intr) age
#> age -0.838
#> SexFemale -0.348 0.000
#>
#> Standardized Within-Group Residuals:
#> Min Q1 Med Q3 Max
#> -3.08141704 -0.45675583 0.01552695 0.44704158 3.89437694
#>
#> Number of Observations: 108
#> Number of Groups: 27
lmeSummary(model)
#> [[1]]
#> [,1]
#> modelPosDef "Positive Definite: Yes"
#> modelFit "Pseudo R-square: 0.868"
#>
#> [[2]]
#> Value Std.Error DF t-value p-value
#> (Intercept) 17.635 0.886 80 19.899 0.000
#> age 0.660 0.071 80 9.265 0.000
#> SexFemale -2.145 0.757 25 -2.833 0.009
#>
