bp_ts_plots {bp}

Blood Pressure Time Series Plots

Description

Blood Pressure Time Series Plots

Usage

bp_ts_plots(
  data,
  index = NULL,
  subj = NULL,
  first_hour = 0,
  rotate_xlab = FALSE,
  wrap_var = NULL,
  wrap_row = NULL,
  wrap_col = NULL,
  method = NULL,
  formula = NULL
)

Arguments

data

User-supplied data set containing blood pressure data. Must contain a Systolic blood pressure (SBP), Diastolic blood pressure (DBP) and an ID column. Data must also have either a DATE_TIME or DATE column, unless an index column is specified for the x axis. An index column trumps DATE_TIME and DATE if specified.

index

An optional user-specified column denoting x-axis values (other than DATE_TIME or DATE columns). index argument must be a character denoting a column in the supplied data. This argument is useful in the event the data has no corresponding date/time value, but rather an index of values such as (reading #1, #2, #3, etc. or office visit #1, #2, etc. as examples) If NULL, the function will look for DATE_TIME or DATE columns to reference. If index is character, it will be coerced to factor.

subj

Optional argument. Allows the user to specify and subset specific subjects from the ID column of the supplied data set. The subj argument can be a single value or a vector of elements. The input type should be character, but the function will comply with integers so long as they are all present in the ID column of the data.

first_hour

Optional argument denoting a value corresponding to the first hour of the x-axis for the hour plots. Only applicable to data sets that contain a DATE_TIME column. It is often easier to visualize a BP time series not from 0 - 23 hours but rather an order that begins or ends with waking up such as first_hour = 6 which will sequence the hours from 6am (6, 7, ..., 23, 0, ..., 4, 5). The default value for first_hour is set at 0

rotate_xlab

An optional logical argument to rotate the x axis labels 90 degrees. The default value is set to FALSE.

wrap_var

An optional character argument indicating a column by which to "wrap" the data. This function utilizes ggplot2's facet_wrap function to split plots according to some extraneous variable (such as gender, smoking status, awake/asleep, etc.).

wrap_row

An optional argument specifying how many rows to wrap the plots if wrap_var is specified.

wrap_col

An optional argument specifying how many columnss to wrap the plots if wrap_var is specified.

method

(ggplot2 plotting arguments) Smoothing method (function) to use. Default is NULL, but also accepts a character vector "lm", "glm", "gam", "loess". NULL implies that the smoothing method will be chosen automatically based on the size of the largest group.

See https://ggplot2.tidyverse.org/reference/geom_smooth.html for more details.

formula

(ggplot2 plotting arguments) Formula to use in smoothing function. Default is NULL implying y ~ x for fewer than 1,000 observations and y ~ x(x, bs = "cs") otherwise.

See https://ggplot2.tidyverse.org/reference/geom_smooth.html for more details.

Value

If the data does not contain a DATE_TIME column, a single list will be returned with the time-dependent plots for each subject ID. If the data does contain a DATE_TIME column (and index is not specified), a list of two lists will be returned for each subject ID: one corresponding to the time-dependent plots (according to the DATE_TIME values), and another plot corresponding to the HOUR plots which show repeated measurements of BP values throughout a 24-hour period. The index of the output therefore corresponds to whether there is only the time-dependent plot type (the former situation) or there are both time-dependent and hourly plot types (the latter situation).

Examples

# Pregnancy Data Set

# bp_preg requires the use of the index argument since there are no DATE or
# DATE_TIME columns available
data_preg <- bp::bp_preg
data_preg$Time_Elapsed <- factor(data_preg$Time_Elapsed,
     levels = c("Booking", "0", "30", "60", "90", "120", "150", "180", "210", "240"))

bp::bp_ts_plots(data_preg, index = 'time_elapsed', subj = 1:3)


# JHS Data Set

# bp_jhs returns two lists since there is a DATE_TIME column: one for
# DATE_TIME and one for HOUR
data_jhs <- bp::process_data(bp::bp_jhs,
                                    sbp = 'sys.mmhg.',
                                    dbp = 'dias.mmhg.',
                                     hr = 'pulse.bpm.',
                              date_time = 'datetime')

bp::bp_ts_plots(data_jhs)


# HYPNOS Data Set

# bp_hypnos wraps the plots by the visit # since each subject was recorded over
# the course of two office visits
data_hypnos <- bp::process_data(bp::bp_hypnos,
                                          sbp = 'syst',
                                          dbp = 'diast',
                                    date_time = 'date.time')

bp::bp_ts_plots(data_hypnos, wrap_var = 'visit', subj = '70435')