S3 print method for the class graph_report — print.graph

A printed graph_report displays the initial graph, p-values and significance levels, rejection decisions, and optional detailed test results.

Usage

# S3 method for class 'graph_report'
print(x, ..., precision = 4, indent = 2, rows = 10)

Arguments

x: An object of class graph_report to print.
...: Other values passed on to other methods (currently unused)
precision: An integer scalar indicating the number of decimal places to to display.
indent: An integer scalar indicating how many spaces to indent results.
rows: An integer scalar indicating how many rows of detailed test results to print.

Value

An object x of class graph_report, after printing the report of conducting a graphical multiple comparison procedure.

References

Bretz, F., Posch, M., Glimm, E., Klinglmueller, F., Maurer, W., and Rohmeyer, K. (2011). Graphical approaches for multiple comparison procedures using weighted Bonferroni, Simes, or parametric tests. Biometrical Journal, 53(6), 894-913.

Examples

# A graphical multiple comparison procedure with two primary hypotheses (H1
# and H2) and two secondary hypotheses (H3 and H4)
# See Figure 1 in Bretz et al. (2011).
hypotheses <- c(0.5, 0.5, 0, 0)
transitions <- rbind(
  c(0, 0, 1, 0),
  c(0, 0, 0, 1),
  c(0, 1, 0, 0),
  c(1, 0, 0, 0)
)
g <- graph_create(hypotheses, transitions)

p <- c(0.018, 0.01, 0.105, 0.006)
alpha <- 0.025
graph_test_shortcut(g, p, alpha)
#> 
#> Test parameters ($inputs) ------------------------------------------------------
#>   Initial graph
#> 
#>   --- Hypothesis weights ---
#>   H1: 0.5
#>   H2: 0.5
#>   H3: 0.0
#>   H4: 0.0
#> 
#>   --- Transition weights ---
#>      H1 H2 H3 H4
#>   H1  0  0  1  0
#>   H2  0  0  0  1
#>   H3  0  1  0  0
#>   H4  1  0  0  0
#> 
#>   Alpha = 0.025
#> 
#>                           H1    H2    H3    H4
#>   Unadjusted p-values: 0.018 0.010 0.105 0.006
#> 
#>   Test types
#>   bonferroni: (H1, H2, H3, H4)
#> 
#> Test summary ($outputs) --------------------------------------------------------
#>   Hypothesis Adj. P-value Reject
#>           H1        0.020   TRUE
#>           H2        0.020   TRUE
#>           H3        0.105  FALSE
#>           H4        0.020   TRUE
#> 
#>   Final updated graph after removing rejected hypotheses
#> 
#>   --- Hypothesis weights ---
#>   H1: NA
#>   H2: NA
#>   H3:  1
#>   H4: NA
#> 
#>   --- Transition weights ---
#>      H1 H2 H3 H4
#>   H1 NA NA NA NA
#>   H2 NA NA NA NA
#>   H3 NA NA  0 NA
#>   H4 NA NA NA NA
#>