Adds a Variable Flagging the Maximal / Minimal Value Within a Group of Observations
Source:R/derive_var_extreme_flag.R
derive_var_worst_flag.Rd
This function is deprecated. Please use slice_derivation()
/ derive_var_extreme_flag()
to derive extreme flags and adjust the order
argument.
Usage
derive_var_worst_flag(
dataset,
by_vars,
order,
new_var,
param_var,
analysis_var,
worst_high,
worst_low,
check_type = "warning"
)
Arguments
- dataset
Input dataset. Variables specified by
by_vars
,order
,param_var
, andanalysis_var
are expected.- by_vars
Grouping variables
Permitted Values: list of variables
- order
Sort order. Used to determine maximal / minimal observation if they are not unique, see Details section for more information.
- new_var
Variable to add to the
dataset
. It is set"Y"
for the maximal / minimal observation of each group, see Details section for more information.- param_var
Variable with the parameter values for which the maximal / minimal value is calculated.
- analysis_var
Variable with the measurement values for which the maximal / minimal value is calculated.
- worst_high
Character with
param_var
values specifying the parameters referring to "high". Usecharacter(0)
if not required.- worst_low
Character with
param_var
values specifying the parameters referring to "low". Usecharacter(0)
if not required.- check_type
Check uniqueness?
If
"warning"
or"error"
is specified, the specified message is issued if the observations of the input dataset are not unique with respect to the by variables and the order.Default:
"warning"
Permitted Values:
"none"
,"warning"
,"error"
Details
For each group with respect to the variables specified by the by_vars
parameter,
the maximal / minimal observation of analysis_var
is labeled in the new_var
column as "Y"
,
if its param_var
is in worst_high
/ worst_low
.
Otherwise, it is assigned NA
.
If there is more than one such maximal / minimal observation,
the first one with respect to the order specified by the order
parameter is flagged. The
direction of "worst" depends on the definition of worst for a specified parameters in the
arguments worst_high
/ worst_low
, i.e. for some parameters the highest value is the worst
and for others the worst is the lowest value.