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A graphical multiple comparison procedure is represented by 1) a vector of initial hypothesis weights hypotheses, and 2) a matrix of initial transition weights transitions. This function creates the initial graph object using hypothesis weights and transition weights.

Usage

graph_create(hypotheses, transitions, hyp_names = NULL)

Arguments

hypotheses

A numeric vector of hypothesis weights in a graphical multiple comparison procedure. Must be a vector of values between 0 & 1 (inclusive). The length should match the row and column lengths of transitions. The sum of hypothesis weights should not exceed 1.

transitions

A numeric matrix of transition weights between hypotheses in a graphical multiple comparison procedure. Must be a square matrix of values between 0 & 1 (inclusive). The row and column lengths should match the length of hypotheses. Each row (Transition weights leaving a hypothesis) can sum to no more than 1. The diagonal entries (Transition weights from a hypothesis to itself) must be all 0s.

hyp_names

(Optional) A character vector of hypothesis names. If not provided, names from hypotheses and transitions will be used. If names are not specified, hypotheses will be named sequentially as H1, H2, .......

Value

An S3 object of class initial_graph with a list of 2 elements:

  • Hypothesis weights hypotheses.

  • Transition weights transitions.

Validation of inputs

Inputs are also validated to make sure of the validity of the graph:

  • Hypothesis weights hypotheses are numeric.

  • Transition weights transitions are numeric.

  • Length of hypotheses and dimensions of transitions match.

  • Hypothesis weights hypotheses must be non-negative and sum to no more than 1.

  • Transition weights transitions:

    • Values must be non-negative.

    • Rows must sum to no more than 1.

    • Diagonal entries must be all 0.

  • Hypothesis names hyp_names override names in hypotheses or transitions.

References

Bretz, F., Maurer, W., Brannath, W., and Posch, M. (2009). A graphical approach to sequentially rejective multiple test procedures. Statistics in Medicine, 28(4), 586-604.

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.

See also

graph_update() for the updated graph after hypotheses being deleted from 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)
)
hyp_names <- c("H11", "H12", "H21", "H22")
g <- graph_create(hypotheses, transitions, hyp_names)
g
#> Initial graph
#> 
#> --- Hypothesis weights ---
#> H11: 0.5
#> H12: 0.5
#> H21: 0.0
#> H22: 0.0
#> 
#> --- Transition weights ---
#>      H11 H12 H21 H22
#>  H11   0   0   1   0
#>  H12   0   0   0   1
#>  H21   0   1   0   0
#>  H22   1   0   0   0

# Explicit names override names in `hypotheses` (with a warning)
hypotheses <- c(h1 = 0.5, h2 = 0.5, h3 = 0, h4 = 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, hyp_names)
#> Warning: Hypothesis names specified - overriding names in
#>                     `hypotheses` and `transitions`
g
#> Initial graph
#> 
#> --- Hypothesis weights ---
#> H11: 0.5
#> H12: 0.5
#> H21: 0.0
#> H22: 0.0
#> 
#> --- Transition weights ---
#>      H11 H12 H21 H22
#>  H11   0   0   1   0
#>  H12   0   0   0   1
#>  H21   0   1   0   0
#>  H22   1   0   0   0

# Use names in `transitions`
hypotheses <- c(0.5, 0.5, 0, 0)
transitions <- rbind(
  H1 = c(0, 0, 1, 0),
  H2 = c(0, 0, 0, 1),
  H3 = c(0, 1, 0, 0),
  H4 = c(1, 0, 0, 0)
)
g <- graph_create(hypotheses, transitions)
g
#> 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

# Unmatched names in `hypotheses` and `transitions` (with an error)
hypotheses <- c(h1 = 0.5, h2 = 0.5, h3 = 0, h4 = 0)
transitions <- rbind(
  H1 = c(0, 0, 1, 0),
  H2 = c(0, 0, 0, 1),
  H3 = c(0, 1, 0, 0),
  H4 = c(1, 0, 0, 0)
)
if (FALSE) { # \dontrun{
g <- graph_create(hypotheses, transitions)
} # }

# When names are not specified, hypotheses are numbered sequentially as
# H1, H2, ...
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)
g
#> 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