Investigating the fit of statistical models to data often involves selecting
the best fitting model amongst many competing models. This function helps
report indices of model fit for various models. Reports the type of
different R objects . For a list of supported objects, see
report()).
report_performance(x, table = NULL, ...)| x | The R object that you want to report (see list of of supported objects above). |
|---|---|
| table | A table obtained via |
| ... | Arguments passed to or from other methods. |
An object of class report_performance().
# \donttest{
library(report)
# GLMs
report_performance(lm(Sepal.Length ~ Petal.Length * Species, data = iris))
#> The model explains a statistically significant and substantial proportion of variance (R2 = 0.84, F(5, 144) = 151.71, p < .001, adj. R2 = 0.83)
report_performance(glm(vs ~ disp, data = mtcars, family = "binomial"))
#> The model's explanatory power is substantial (Tjur's R2 = 0.53)
# Mixed models
if (require("lme4")) {
model <- lme4::lmer(Sepal.Length ~ Petal.Length + (1 | Species), data = iris)
report_performance(model)
}
#> The model's total explanatory power is substantial (conditional R2 = 0.97) and the part related to the fixed effects alone (marginal R2) is of 0.66
# Bayesian models
if (require("rstanarm")) {
model <- stan_glm(Sepal.Length ~ Species, data = iris, refresh = 0, iter = 600)
report_performance(model)
}
#> The model's explanatory power is substantial (R2 = 0.61, 95% CI [0.53, 0.68], adj. R2 = 0.61)
# Structural Equation Models (SEM)
if (require("lavaan")) {
structure <- " ind60 =~ x1 + x2 + x3
dem60 =~ y1 + y2 + y3
dem60 ~ ind60 "
model <- lavaan::sem(structure, data = PoliticalDemocracy)
report_performance(model)
}
#> The model is not significantly different from a baseline model (Chi2(8) = 7.98, p = 0.435). The GFI (.97 > .95), AGFI (.91 > .90), NFI (.97 > .90), NNFI (.00 > .90), CFI (.00 > .90), RMSEA (.00 < .05), SRMR (.03 < .08), RFI (.95 > .90), IFI (.00 > .90) and PNFI (.52 > .50) suggest a satisfactory fit.
# }