S3 print method for the class updated_graph

A printed updated_graph displays the initial graph, the (final) updated graph, and the sequence of intermediate updated graphs after hypotheses are deleted (if available).

Usage

# S3 method for class 'updated_graph'
print(x, ..., precision = 6, indent = 2)

Arguments

x

An object of the class updated_graph 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.

Value

An object x of the class updated_graph, after printing the updated graph.

References

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

See also

print.initial_graph() for the print method for the initial graph.

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)

# Delete the second and third hypotheses in the "unordered mode"
graph_update(g, delete = c(FALSE, TRUE, TRUE, FALSE))
#> Initial and final graphs -------------------------------------------------------
#> 
#> 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
#> 
#> Updated graph after deleting hypotheses 2, 3
#> 
#> --- Hypothesis weights ---
#> H1: 0.5
#> H2:  NA
#> H3:  NA
#> H4: 0.5
#> 
#> --- Transition weights ---
#>     H1 H2 H3 H4
#>  H1  0 NA NA  1
#>  H2 NA NA NA NA
#>  H3 NA NA NA NA
#>  H4  1 NA NA  0

# Equivalent way in the "ordered mode" to obtain the updated graph after
# deleting the second and third hypotheses
# Additional intermediate updated graphs are also provided
graph_update(g, delete = 2:3)
#> Initial and final graphs -------------------------------------------------------
#> 
#> 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
#> 
#> Updated graph after deleting hypotheses 2, 3
#> 
#> --- Hypothesis weights ---
#> H1: 0.5
#> H2:  NA
#> H3:  NA
#> H4: 0.5
#> 
#> --- Transition weights ---
#>     H1 H2 H3 H4
#>  H1  0 NA NA  1
#>  H2 NA NA NA NA
#>  H3 NA NA NA NA
#>  H4  1 NA NA  0
#> 
#> Deletion sequence ($intermediate_graphs) ---------------------------------------
#> 
#>   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
#> 
#>     Step 1: Updated graph after removing hypothesis 2
#> 
#>     --- Hypothesis weights ---
#>     H1: 0.5
#>     H2:  NA
#>     H3: 0.0
#>     H4: 0.5
#> 
#>     --- Transition weights ---
#>        H1 H2 H3 H4
#>     H1  0 NA  1  0
#>     H2 NA NA NA NA
#>     H3  0 NA  0  1
#>     H4  1 NA  0  0
#> 
#>       Step 2: Updated graph after removing hypotheses 2, 3
#> 
#>       --- Hypothesis weights ---
#>       H1: 0.5
#>       H2:  NA
#>       H3:  NA
#>       H4: 0.5
#> 
#>       --- Transition weights ---
#>          H1 H2 H3 H4
#>       H1  0 NA NA  1
#>       H2 NA NA NA NA
#>       H3 NA NA NA NA
#>       H4  1 NA NA  0
#> 
#>   Final updated graph after removing deleted hypotheses
#> 
#>   --- Hypothesis weights ---
#>   H1: 0.5
#>   H2:  NA
#>   H3:  NA
#>   H4: 0.5
#> 
#>   --- Transition weights ---
#>      H1 H2 H3 H4
#>   H1  0 NA NA  1
#>   H2 NA NA NA NA
#>   H3 NA NA NA NA
#>   H4  1 NA NA  0
#>