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Line plot with optional table

Source: R/g_lineplot.R
g_lineplot.Rd

[Stable]

Line plot with optional table.

Usage 

g_lineplot(
  df,
  alt_counts_df = NULL,
  variables = control_lineplot_vars(),
  mid = "mean",
  interval = "mean_ci",
  whiskers = c("mean_ci_lwr", "mean_ci_upr"),
  table = NULL,
  sfun = s_summary,
  ...,
  mid_type = "pl",
  mid_point_size = 2,
  position = ggplot2::position_dodge(width = 0.4),
  legend_title = NULL,
  legend_position = "bottom",
  ggtheme = nestcolor::theme_nest(),
  xticks = NULL,
  xlim = NULL,
  ylim = NULL,
  x_lab = obj_label(df[[variables[["x"]]]]),
  y_lab = NULL,
  y_lab_add_paramcd = TRUE,
  y_lab_add_unit = TRUE,
  title = "Plot of Mean and 95% Confidence Limits by Visit",
  subtitle = "",
  subtitle_add_paramcd = TRUE,
  subtitle_add_unit = TRUE,
  caption = NULL,
  table_format = NULL,
  table_labels = NULL,
  table_font_size = 3,
  errorbar_width = 0.45,
  newpage = lifecycle::deprecated(),
  col = NULL,
  linetype = NULL,
  rel_height_plot = 0.5,
  as_list = FALSE
)

Arguments

df

(data.frame)
data set containing all analysis variables.

alt_counts_df

(data.frame or NULL)
data set that will be used (only) to counts objects in groups for stratification.

variables

(named character) vector of variable names in df which should include:

  • x (string)
    name of x-axis variable.

  • y (string)
    name of y-axis variable.

  • group_var (string or NULL)
    name of grouping variable (or strata), i.e. treatment arm. Can be NA to indicate lack of groups.

  • subject_var (string or NULL)
    name of subject variable. Only applies if group_var is not NULL.

  • paramcd (string or NA)
    name of the variable for parameter's code. Used for y-axis label and plot's subtitle. Can be NA if paramcd is not to be added to the y-axis label or subtitle.

  • y_unit (string or NA)
    name of variable with units of y. Used for y-axis label and plot's subtitle. Can be NA if y unit is not to be added to the y-axis label or subtitle.

  • facet_var (string or NA)
    name of the secondary grouping variable used for plot faceting, i.e. treatment arm. Can be NA to indicate lack of groups.

mid

(character or NULL)
names of the statistics that will be plotted as midpoints. All the statistics indicated in mid variable must be present in the object returned by sfun, and be of a double or numeric type vector of length one.

interval

(character or NULL)
names of the statistics that will be plotted as intervals. All the statistics indicated in interval variable must be present in the object returned by sfun, and be of a double or numeric type vector of length two. Set interval = NULL if intervals should not be added to the plot.

whiskers

(character)
names of the interval whiskers that will be plotted. Names must match names of the list element interval that will be returned by sfun (e.g. mean_ci_lwr element of sfun(x)[["mean_ci"]]). It is possible to specify one whisker only, or to suppress all whiskers by setting interval = NULL.

table

(character or NULL)
names of the statistics that will be displayed in the table below the plot. All the statistics indicated in table variable must be present in the object returned by sfun.

sfun

(function)
the function to compute the values of required statistics. It must return a named list with atomic vectors. The names of the list elements refer to the names of the statistics and are used by mid, interval, table. It must be able to accept as input a vector with data for which statistics are computed.

...

optional arguments to sfun.

mid_type

(string)
controls the type of the mid plot, it can be point ("p"), line ("l"), or point and line ("pl").

mid_point_size

(numeric(1))
font size of the mid plot points.

position

(character or call)
geom element position adjustment, either as a string, or the result of a call to a position adjustment function.

legend_title

(string)
legend title.

legend_position

(string)
the position of the plot legend ("none", "left", "right", "bottom", "top", or a two-element numeric vector).

ggtheme

(theme)
a graphical theme as provided by ggplot2 to control styling of the plot.

xticks

(numeric or NULL)
numeric vector of tick positions or a single number with spacing between ticks on the x-axis, for use when variables$x is numeric. If NULL (default), labeling::extended() is used to determine optimal tick positions on the x-axis. If variables$x is not numeric, this argument is ignored.

xlim

(numeric(2))
vector containing lower and upper limits for the x-axis, respectively. If NULL (default), the default scale range is used.

ylim

(numeric(2))
vector containing lower and upper limits for the y-axis, respectively. If NULL (default), the default scale range is used.

x_lab

(string or NULL)
x-axis label. If NULL then no label will be added.

y_lab

(string or NULL)
y-axis label. If NULL then no label will be added.

y_lab_add_paramcd

(flag)
whether paramcd, i.e. unique(df[[variables["paramcd"]]]) should be added to the y-axis label (y_lab).

y_lab_add_unit

(flag)
whether y-axis unit, i.e. unique(df[[variables["y_unit"]]]) should be added to the y-axis label (y_lab).

title

(string)
plot title.

subtitle

(string)
plot subtitle.

subtitle_add_paramcd

(flag)
whether paramcd, i.e. unique(df[[variables["paramcd"]]]) should be added to the plot's subtitle (subtitle).

subtitle_add_unit

(flag)
whether the y-axis unit, i.e. unique(df[[variables["y_unit"]]]) should be added to the plot's subtitle (subtitle).

caption

(string)
optional caption below the plot.

table_format

(named character or NULL)
format patterns for descriptive statistics used in the (optional) table appended to the plot. It is passed directly to the h_format_row function through the format parameter. Names of table_format must match the names of statistics returned by sfun function.

table_labels

(named character or NULL)
labels for descriptive statistics used in the (optional) table appended to the plot. Names of table_labels must match the names of statistics returned by sfun function.

table_font_size

(numeric(1))
font size of the text in the table.

errorbar_width

(numeric(1))
width of the error bars.

newpage

[Deprecated] not used.

col

(character)
color(s). See ?ggplot2::aes_colour_fill_alpha for example values.

linetype

(character)
line type(s). See ?ggplot2::aes_linetype_size_shape for example values.

rel_height_plot

(proportion)
proportion of total figure height to allocate to the line plot. Relative height of annotation table is then 1 - rel_height_plot. If table = NULL, this parameter is ignored.

as_list

(flag)
whether the two ggplot objects should be returned as a list when table is not NULL. If TRUE, a named list with two elements, plot and table, will be returned. If FALSE (default) the annotation table is printed below the plot via cowplot::plot_grid().

Value

A ggplot line plot (and statistics table if applicable).

Examples 


adsl <- tern_ex_adsl
adlb <- tern_ex_adlb %>% dplyr::filter(ANL01FL == "Y", PARAMCD == "ALT", AVISIT != "SCREENING")
adlb$AVISIT <- droplevels(adlb$AVISIT)
adlb <- dplyr::mutate(adlb, AVISIT = forcats::fct_reorder(AVISIT, AVISITN, min))

# Mean with CI
g_lineplot(adlb, adsl, subtitle = "Laboratory Test:")


# Mean with CI, no stratification with group_var
g_lineplot(adlb, variables = control_lineplot_vars(group_var = NA))


# Mean, upper whisker of CI, no group_var(strata) counts N
g_lineplot(
  adlb,
  whiskers = "mean_ci_upr",
  title = "Plot of Mean and Upper 95% Confidence Limit by Visit"
)


# Median with CI
g_lineplot(
  adlb,
  adsl,
  mid = "median",
  interval = "median_ci",
  whiskers = c("median_ci_lwr", "median_ci_upr"),
  title = "Plot of Median and 95% Confidence Limits by Visit"
)


# Mean, +/- SD
g_lineplot(adlb, adsl,
  interval = "mean_sdi",
  whiskers = c("mean_sdi_lwr", "mean_sdi_upr"),
  title = "Plot of Median +/- SD by Visit"
)


# Mean with CI plot with stats table
g_lineplot(adlb, adsl, table = c("n", "mean", "mean_ci"))


# Mean with CI, table and customized confidence level
g_lineplot(
  adlb,
  adsl,
  table = c("n", "mean", "mean_ci"),
  control = control_analyze_vars(conf_level = 0.80),
  title = "Plot of Mean and 80% Confidence Limits by Visit"
)


# Mean with CI, table, filtered data
adlb_f <- dplyr::filter(adlb, ARMCD != "ARM A" | AVISIT == "BASELINE")
g_lineplot(adlb_f, table = c("n", "mean"))