bp_center {bp} | R Documentation |
Measures of Center (bp_center)
Description
Calculate the mean and median at various levels of granularity based on what is supplied (ID, VISIT, WAKE, and / or DATE) for either SBP, DBP, or both.
Usage
bp_center(
data,
inc_date = FALSE,
subj = NULL,
bp_type = c("both", "sbp", "dbp"),
add_groups = NULL,
inc_wake = TRUE
)
Arguments
data |
Required argument. Pre-processed dataframe with SBP and DBP columns
with optional ID, VISIT, WAKE, and DATE columns if available.
Use |
inc_date |
Optional argument. Default is FALSE. As ABPM data typically
overlaps due to falling asleep on one date and waking up on another, the |
subj |
Optional argument. Allows the user to specify and subset specific subjects
from the |
bp_type |
Optional argument. Determines whether to calculate center for SBP values or DBP values, or both. For both SBP and DBP ARV values use bp_type = 'both', for SBP-only use bp_type = 'sbp, and for DBP-only use bp_type = 'dbp'. If no type specified, default will be set to 'both' |
add_groups |
Optional argument. Allows the user to aggregate the data by an
additional "group" to further refine the output. The supplied input must be a
character vector with the strings corresponding to existing column names of the
processed |
inc_wake |
Optional argument corresponding to whether or not to include |
Value
A tibble object with a row corresponding to each subject, or alternatively a row corresponding to each date if inc_date = TRUE. The resulting tibble consists of:
-
ID
: The unique identifier of the subject. For single-subject datasets, ID = 1 -
VISIT
: (If applicable) Corresponds to the visit # of the subject, if more than 1 -
WAKE
: (If applicable) Corresponds to the awake status of the subject (0 = asleep | 1 = awake) -
SBP_mean
/DBP_mean
: Calculates the mean of systolic blood pressure readings for the specified time granularity. -
SBP_med
/DBP_med
: Calculates the median of systolic blood pressure readings for the specified time granularity. -
N
: The number of observations for that particular grouping. Ifinc_date = TRUE
,N
corresponds to the number of observations for that date. Ifinc_date = FALSE
, N corresponds to the number of observations for the most granular grouping available (i.e. a combination ofID
,VISIT
, andWAKE
) Any add_groups variables supplied to function argument will be present as a column in the resulting tibble.
Examples
# Load data
data(bp_hypnos)
data(bp_jhs)
# Process bp_hypnos
hyp_proc <- process_data(bp_hypnos, sbp = "SYST", dbp = "DIAST", date_time = "date.time",
id = "id", wake = "wake", visit = "visit", hr = "hr", pp ="pp", map = "map", rpp = "rpp")
# Process bp_jhs data
jhs_proc <- process_data(bp_jhs, sbp = "Sys.mmHg.", dbp = "Dias.mmHg.", date_time = "DateTime",
hr = "Pulse.bpm.")
# BP Center Calculation
bp_center(hyp_proc, subj = c(70417, 70435))