check_design() validates whether an analysis fits the narrow branching
workflow implemented by statsguider. The function checks the presence of
required columns, infers simple data properties, and reports issues and
warnings before recommendation or execution.
Usage
check_design(
data,
outcome,
group = NULL,
id = NULL,
goal = c("difference", "association", "adjusted_effect", "time_to_event", "agreement",
"equivalence"),
outcome_type = c("auto", "continuous", "binary", "nominal", "ordinal", "count"),
paired = c("no", "yes"),
repeated = c("no", "yes"),
adjust = c("no", "yes")
)Arguments
- data
A
data.frame.- outcome
Name of the outcome column.
- group
Optional name of the group column.
- id
Optional name of the subject identifier column.
- goal
One of
"difference","association","adjusted_effect","time_to_event","agreement", or"equivalence".- outcome_type
One of
"auto","continuous","binary","nominal","ordinal", or"count".- paired
"yes"or"no".- repeated
"yes"or"no".- adjust
"yes"or"no".