Helper function for make_table2.cumcount

table2_helper_cumcount(
  fit_models,
  effect_measure_type = "CD",
  count_round = 1,
  count_time = NULL,
  alpha = 0.05,
  ref = 1,
  boot_method = "normal",
  caption = "",
  table_footer = ""
)

Arguments

fit_models

a list of fit cumcount objects

effect_measure_type

A string identifying the type of effect measure to be computed from among the following options for a given method.

cumrisk: "RD" (risk difference), "RR" (risk ratio), "logRR" (logarithm of the risk ratio), or "AR" (attributable risk)
cumcount: "CD" (count difference) or "CR" (count ratio)

Note that when a given input results object was created using bootstrap estimation and boot_method is "log-normal", then only effect measures with support on the positive real line can be used (i.e. "RR" or "CR"). See the Cumulative risk effect measure types and Cumulative count effect measure types sections for the definitions of the various effect measures.

count_round

The number of significant digits used for rounding the count

count_time

The desired time at which to extract the the cumulative count and count difference. If NULL, uses the median time in the cumcount object.

alpha

The desired nominal significance level of the confidence intervals.

ref

The index of the treatment group to use as the reference for effect measure calculations, where groups are ordered lexicographically by their labels (default ref = 1).

boot_method

The specific bootstrap approach used to compute confidence intervals, for both the cumulative risk or count estimates and the effect measures. Options are "normal" (default; normal approximation on the original scale), "log-normal" (normal approximation on the log scale), "percentile" (percentile-based approach using quantiles of the bootstrap distribution), and "basic" (basic bootstrap using the reflection method). When a given input results object was created without using bootstrap estimation then the value of boot_method is ignored. Note that when a given input results object was created using bootstrap estimation and boot_method is "log-normal", then only effect measures specified via effect_measure_type with support on the positive real line can be used.

caption

Text that will be added above the top left of the table, ie a title to the table

table_footer

Additional footer information accepts html formatting

Value

The resulting table as data.frame which can be passed to table rendering functions such as datatable or kable.

Author

M. Alan Brookhart & Robert A. Overman