| gglogisticexpdist {ggquickeda} | R Documentation |
Create a logistic fit plot
Description
Produces a logistic fit plot with a facettable exposures/quantiles/distributions in ggplot2
Usage
gglogisticexpdist(
data = effICGI,
response = "response",
endpoint = "Endpoint",
DOSE = "DOSE",
color_fill = "DOSE",
exposure_metrics = c("AUC", "CMAX"),
exposure_metric_split = c("median", "tertile", "quartile", "none"),
exposure_metric_soc_value = -99,
exposure_metric_plac_value = 0,
exposure_distribution = c("distributions", "lineranges", "none"),
dose_plac_value = "Placebo",
xlab = "Exposure Values",
ylab = "Probability of Response",
prob_text_size = 5,
prob_obs_bydose = TRUE,
N_text_size = 5,
binlimits_text_size = 5,
binlimits_ypos = 0,
binlimits_color = "gray70",
dist_position_scaler = 0.2,
dist_offset = 0,
lineranges_ypos = 0.2,
lineranges_dodge = 0.15,
yproj = TRUE,
yproj_xpos = 0,
yproj_dodge = 0.2,
yaxis_position = c("left", "right"),
facet_formula = NULL,
theme_certara = TRUE
)
Arguments
data |
Data to use with multiple endpoints stacked into Endpoint(endpoint name), response 0/1 |
response |
name of the column holding the values response 0/1 |
endpoint |
name of the column holding the name/key of the endpoint default to |
DOSE |
name of the column holding the DOSE values default to |
color_fill |
name of the column to be used for color/fill default to DOSE column |
exposure_metrics |
name(s) of the column(s) to be stacked into |
exposure_metric_split |
one of "median", "tertile", "quartile", "none" |
exposure_metric_soc_value |
special exposure code for standard of care default -99 |
exposure_metric_plac_value |
special exposure code for placebo default 0 |
exposure_distribution |
one of distributions, lineranges or none |
dose_plac_value |
string identifying placebo in DOSE column |
xlab |
text to be used as x axis label |
ylab |
text to be used as y axis label |
prob_text_size |
probability text size default to 5 |
prob_obs_bydose |
observed probability by dose |
N_text_size |
N responders/Ntotal by exposure bin text size default to 5 |
binlimits_text_size |
5 binlimits text size |
binlimits_ypos |
binlimits y position default to 0 |
binlimits_color |
binlimits text color default to "gray70" |
dist_position_scaler |
space occupied by the distribution default to 0.2 |
dist_offset |
offset where the distribution position starts 0 |
lineranges_ypos |
where to put the lineranges -1 |
lineranges_dodge |
lineranges vertical dodge value 1 |
yproj |
project the probabilities on y axis |
yproj_xpos |
y projection x position 0 |
yproj_dodge |
y projection dodge value 0.2 |
yaxis_position |
where to put y axis "left" or "right" |
facet_formula |
facet formula to be use otherwise |
theme_certara |
apply certara colors and format for strips and default colour/fill |
Examples
# Example 1
library(ggplot2)
effICGI <- logistic_data |>
dplyr::filter(!is.na(ICGI))|>
dplyr::filter(!is.na(AUC))
effICGI$DOSE <- factor(effICGI$DOSE,
levels=c("0", "600", "1200","1800","2400"),
labels=c("Placebo", "600 mg", "1200 mg","1800 mg","2400 mg"))
effICGI$STUDY <- factor(effICGI$STUDY)
effICGI$ICGI2 <- effICGI$ICGI
effICGI <- tidyr::gather(effICGI,Endpoint,response,ICGI,ICGI2)
gglogisticexpdist(data = effICGI |>
dplyr::filter(Endpoint=="ICGI"),
response = "response",
endpoint = "Endpoint",
exposure_metrics = c("AUC"),
exposure_metric_split = c("quartile"),
exposure_metric_soc_value = -99,
exposure_metric_plac_value = 0,
exposure_distribution ="distributions",
yproj_xpos = -15,
yproj_dodge = 10,
dist_position_scaler = 0.1,
dist_offset = -0.1)
# Example 2
gglogisticexpdist(data = effICGI |>
dplyr::filter(Endpoint=="ICGI"),
response = "response",
endpoint = "Endpoint",
exposure_metrics = c("CMAX"),
exposure_metric_split = c("tertile"),
exposure_metric_soc_value = -99,
exposure_metric_plac_value = 0,
exposure_distribution ="lineranges",
lineranges_ypos = -0.2,
lineranges_dodge = 0.4,
prob_obs_bydose = TRUE,
yproj_xpos = -5,
yproj_dodge = 5,
dist_position_scaler = 0.1)
## Not run:
#' # Example 3
library(ggh4x)
gglogisticexpdist(data = effICGI |>
dplyr::filter(Endpoint=="ICGI"),
response = "response",
endpoint = "Endpoint",
DOSE = "DOSE",
exposure_metrics = c("AUC"),
exposure_metric_split = c("quartile"),
exposure_distribution ="distributions",
exposure_metric_soc_value = -99,
exposure_metric_plac_value = 0,
dist_position_scaler = 0.15)+
facet_grid2(Endpoint~expname+DOSE2,scales="free",
margins = "DOSE2",strip = strip_nested())
# Example 4
effICGI$SEX <- as.factor(effICGI$SEX)
gglogisticexpdist(data = effICGI |>
dplyr::filter(Endpoint=="ICGI"),
response = "response",
endpoint = "Endpoint",
DOSE = "DOSE",
color_fill = "SEX",
exposure_metrics = c("AUC"),
exposure_metric_split = c("quartile"),
exposure_distribution ="distributions",
exposure_metric_soc_value = -99,
exposure_metric_plac_value = 0,
lineranges_ypos = -0.2,
yproj_xpos = -10,
yproj_dodge = 20,
prob_text_size = 6,
binlimits_text_size = 6,
N_text_size = 4,
dist_position_scaler = 0.15)+
ggplot2::scale_x_continuous(breaks = seq(0,350,50),
expand = ggplot2::expansion(add= c(0,0),mult=c(0,0)))+
ggplot2::coord_cartesian(xlim = c(-30,355))+
ggplot2::facet_grid(Endpoint~expname+color_fill2, margins ="color_fill2" )
#Example 4b
effICGI$SEX <- as.factor(effICGI$SEX)
gglogisticexpdist(data = effICGI |>
dplyr::filter(Endpoint =="ICGI"),
response = "response",
endpoint = "Endpoint",
color_fill = "SEX",
exposure_metrics = c("AUC"),
exposure_metric_split = c("quartile"),
exposure_metric_soc_value = -99,
exposure_metric_plac_value = 0,
dist_position_scaler = 1, dist_offset = -1 ,
yproj_xpos = -20 ,
yproj_dodge = 20 ,
exposure_distribution ="lineranges")
#Example 5
gglogisticexpdist(data = effICGI |> dplyr::filter(Endpoint=="ICGI"),
response = "response",
endpoint = "Endpoint",
DOSE = "DOSE",
exposure_metrics = c("AUC"),
exposure_metric_split = c("quartile"),
exposure_distribution ="distributions",
exposure_metric_soc_value = -99,
exposure_metric_plac_value = 0,
dist_position_scaler = 0.15)+
facet_grid(Endpoint~expname+exptile,scales="free",
margins = "exptile")
#Example 6
a <- gglogisticexpdist(data = effICGI, #
response = "response",
endpoint = "Endpoint",
DOSE = "DOSE",yproj_dodge = 36,
exposure_metrics = c("AUC"),
exposure_metric_split = c("quartile"),
exposure_distribution ="lineranges",
exposure_metric_soc_value = -99,
exposure_metric_plac_value = 0) +
facet_grid(Endpoint~expname,switch = "both")
b <- gglogisticexpdist(data = effICGI, #
response = "response",
endpoint = "Endpoint",
DOSE = "DOSE",yproj_dodge = 2,
exposure_metrics = c("CMAX"),
exposure_metric_split = c("quartile"),
exposure_distribution ="lineranges",
exposure_metric_soc_value = -99,
exposure_metric_plac_value = 0,
yaxis_position = "right")+
facet_grid(Endpoint~expname,switch = "x")+
theme(strip.text.y.right = element_blank(),
strip.background.y = element_blank())
library(patchwork)
(a | b ) +
plot_layout(guides = "collect")&
theme(legend.position = "top")
## End(Not run)