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Stratified Survival Table

Source: R/Table_StratifiedSurvival.R
Table_StratifiedSurvival.Rd

R's test of the curves the stratified survival chart opens on, as a table: a row for the log-rank test, with its counts and p-value, then a row for each group's median survival, in the legend's order, and one for the hazard ratio, each with its interval. A cut's hazard ratio is the higher group's over the lower's, and is named so. The numbers are Analyze_Survival()'s on the rows the chart draws.

Usage

Table_StratifiedSurvival(
  dfResults,
  dfParticipants = NULL,
  lSettings = list(),
  dfOutcomes = NULL
)

Arguments

dfResults

data.frame Long-format results, one row per participant, biomarker and visit. Column names are supplied by lSettings; the defaults expect USUBJID/TEST/STRESN/VISIT/VISITNUM/STRESU, the columns of Synthetic_Results.

dfParticipants

data.frame One row per participant, or NULL. With it the chart has filters, offers its category columns to the Groups control, and its numbers can be cut. Default: NULL.

lSettings

list bio.viz stratified survival settings, as Widget_StratifiedSurvival() takes them, and title, subtitle and footnotes. Default: list().

dfOutcomes

data.frame The outcomes table, as Widget_StratifiedSurvival() takes it. A table needs one.

Value

A data.frame of text: Statistic, Method, Estimate, Counts, p-value and Note, with the attributes of Table_GroupComparison().

Titles and footnotes

As for Visualize_StratifiedSurvival(): {endpoint}, {group}, {n}, {filters}, {date} and {version}.

Display rules

A p-value is written to three decimals, p < 0.001 below that and p > 0.999 above, never with stars. Every row is labelled exploratory, with its adjustment named when it has one. An estimate is written to four significant digits with its confidence interval. A statistic R did not compute has no p-value, and its note is R's reason.

See also

Visualize_StratifiedSurvival() and Widget_StratifiedSurvival().

Other tables: Table_AssociationScatter(), Table_BiomarkerScreen(), Table_CorrelationMatrix(), Table_CrossTab(), Table_GroupComparison(), Write_RTF()

Examples

Table_StratifiedSurvival(
  Synthetic_Results,
  Synthetic_Participants,
  lSettings = list(
    endpoint = "EFS",
    group_by = list(measure = "CRP", visit = "Baseline", cut = "median")
  ),
  dfOutcomes = Synthetic_Outcomes
)
#>                                         Statistic
#> 1                                   Log-rank test
#> 2                                Median (≤ 2.783)
#> 3                                Median (> 2.783)
#> 4 Hazard ratio, high over low (> 2.783 / ≤ 2.783)
#>                                              Method
#> 1                                     Log-rank test
#> 2 Kaplan-Meier, survfit() with the log-log interval
#> 3 Kaplan-Meier, survfit() with the log-log interval
#> 4                 Cox proportional hazards, coxph()
#>                                              Estimate
#> 1                                                    
#> 2 23.32, 95% confidence interval 17.32 to not reached
#> 3          8.28, 95% confidence interval 5.24 to 9.71
#> 4        3.523, 95% confidence interval 2.43 to 5.107
#>                             Counts   p-value                     Note
#> 1 > 2.783 n = 100, ≤ 2.783 n = 100 p < 0.001 Exploratory, unadjusted.
#> 2                                                                    
#> 3                                                                    
#> 4