Forest plot of a metapred fit — forest.metapred • metamisc

Draw a forest plot of the performance of an internally-externally cross-validated model. By default the final model is shown.

Usage

# S3 method for metapred
forest(x, perfFUN = 1, step = NULL, method = "REML", model = NULL, ...)

Arguments

x: A metapred fit object
perfFUN: Numeric or character. Which performance statistic should be plotted? Defaults to the first.
step: Which step should be plotted? Defaults to the best step. numeric is converted to name of the step: 0 for an unchanged model, 1 for the first change...
method: character string specifying whether a fixed- or a random-effects model should be used to summarize the prediction model performance. A fixed-effects model is fitted when using method="FE". Random-effects models are fitted by setting method equal to one of the following: "DL", "HE", "SJ", "ML", "REML", "EB", "HS", or "GENQ". Default is "REML".
model: Which model change should be plotted? NULL (default, best change) or character name of variable or (integer) index of model change.
...: Other arguments passed to plotting internals. E.g. title. See forest.default for details.

Author

Valentijn de Jong <Valentijn.M.T.de.Jong@gmail.com>

Examples

data(DVTipd)

# Internal-external cross-validation of a pre-specified model 'f'
f <- dvt ~ histdvt + ddimdich + sex + notraum
fit <- metapred(DVTipd, strata = "study", formula = f, scope = f, family = binomial)

# Display the model's external performance (expressed as mean squared error by default) 
# for each study
forest(fit)
#> Error in forest.default(fit): Must specify either 'vi', 'sei', or ('ci.lb', 'ci.ub') pairs.