Summarize IPD Fit — summary.ipd • ipd

Produces a summary of the IPD method/model combination.

Usage

# S3 method for class 'ipd'
summary(object, ...)

Arguments

object: An object of class ipd.
...: Additional arguments to be passed to the summary function.

Value

A list containing:

coefficients: Model coefficients and related statistics.
performance: Performance metrics of the model fit.
...: Additional summary information.

Examples


#-- Generate Example Data

set.seed(2023)

dat <- simdat(n = c(300, 300, 300), effect = 1, sigma_Y = 1)

head(dat)
#>            X1          X2         X3         X4          Y  f      set
#> 1 -0.08378436  1.42014307 -0.1615291 -0.2004525 -0.2871755 NA training
#> 2 -0.98294375 -1.30333434 -1.0273652 -1.6867582  0.3242501 NA training
#> 3 -1.87506732  0.05942012 -1.0964411 -0.0696362 -2.2601440 NA training
#> 4 -0.18614466 -1.30651333 -0.2979100  1.4198123  1.1182872 NA training
#> 5 -0.63348570  0.32404466 -1.0075244 -0.4614362 -1.5729777 NA training
#> 6  1.09079746  0.11532808 -0.6296308 -0.4045431  0.1953583 NA training

formula <- Y - f ~ X1

#-- Fit IPD

fit <- ipd(formula, method = "postpi_analytic", model = "ols",

  data = dat, label = "set")

#-- Summarize Output

summ_fit <- summary(fit)

summ_fit
#> 
#> Call:
#>  Y - f ~ X1 
#> 
#> Method: postpi_analytic 
#> Model: ols 
#> Intercept: Yes 
#> 
#> Coefficients:
#>             Estimate Std.Error Lower.CI Upper.CI
#> (Intercept)  0.79053   0.10833  0.57821   1.0029
#> X1           0.98330   0.10148  0.78441   1.1822