Title:	Produce Forest Plots to Visualize Covariate Effects
Version:	1.0.6
Description:	Produce forest plots to visualize covariate effects using either the command line or an interactive 'Shiny' application.
URL:	https://smouksassi.github.io/coveffectsplot/, https://github.com/smouksassi/coveffectsplot
BugReports:	https://github.com/smouksassi/coveffectsplot/issues
Depends:	R (≥ 4.0.0), data.table (≥ 1.9.8)
Imports:	colourpicker, egg, grid, ggplot2 (≥ 3.3.2), shiny, stats, utils
Suggests:	markdown, dplyr, tidyr, shinyjs, shinymeta, table1, clipr, formatR, MASS, knitr, rmarkdown, mrgsolve, GGally, ggridges, ggrepel, ggstance, patchwork, plotly, scales, shinyAce, Rcpp, gamlss.dist, ggdist, ggh4x, ggpmisc, quantreg
License:	MIT + file LICENSE
SystemRequirements:	pandoc with https support
LazyData:	true
VignetteBuilder:	knitr
RoxygenNote:	7.3.2
Encoding:	UTF-8
NeedsCompilation:	no
Packaged:	2025-01-12 13:10:17 UTC; smouksas
Author:	Samer Mouksassi [aut, cre], Benjamin Rich [aut], Dean Attali [ctb]
Maintainer:	Samer Mouksassi <samermouksassi@gmail.com>
Repository:	CRAN
Date/Publication:	2025-01-12 13:30:01 UTC

Correlated Covariates data

Description

A example dataset used to illustrate multivariate joint covariate effects.

Usage

covdatasim

Format

A dataset with 2000 rows and 5 variables

ID

Subject ID

AGE

Age in years

WT

Weight in kg

Sex

0=male; 1=female

ALB

Albumin in g/dL

Source

simulated based on a real dataset

The delta method

Description

This is a copy of msm deltamethod function with the modification to add an environment to make it usable within a function or within a shiny app. Delta method for approximating the standard error of a transformation g(X) of a random variable X = (x_1, x_2, \ldots), given estimates of the mean and covariance matrix of X.

Usage

deltamethod(g, mean, cov, ses = TRUE, envir = parent.frame())

Arguments

Details

The delta method expands a differentiable function of a random variable about its mean, usually with a first-order Taylor approximation, and then takes the variance. For example, an approximation to the covariance matrix of g(X) is given by

Cov(g(X)) = g'(\mu) Cov(X) [g'(\mu)]^T

where \mu is an estimate of the mean of X. This function uses symbolic differentiation via deriv.

A limitation of this function is that variables created by the user are not visible within the formula g. To work around this, it is necessary to build the formula as a string, using functions such as sprintf, then to convert the string to a formula using as.formula. See the example below.

If you can spare the computational time, bootstrapping is a more accurate method of calculating confidence intervals or standard errors for transformations of parameters. Simulation from the asymptotic distribution of the MLEs (see e.g. Mandel 2013) is also a convenient alternative.

Value

A vector containing the standard errors of g_1(X), g_2(X), \ldots or a matrix containing the covariance of g(X).

Author(s)

C. H. Jackson chris.jackson@mrc-bsu.cam.ac.uk

References

Oehlert, G. W. (1992) A note on the delta method. American Statistician 46(1).

Mandel, M. (2013) Simulation based confidence intervals for functions with complicated derivatives. The American Statistician 67(2):76-81.

Examples

## Simple linear regression, E(y) = alpha + beta x 
x <- 1:100
y <- rnorm(100, 4*x, 5)
toy.lm <- lm(y ~ x)
estmean <- coef(toy.lm)
estvar <- summary(toy.lm)$cov.unscaled * summary(toy.lm)$sigma^2

## Estimate of (1 / (alphahat + betahat))
1 / (estmean[1] + estmean[2])
## Approximate standard error
deltamethod (~ 1 / (x1 + x2), estmean, estvar) 

## We have a variable z we would like to use within the formula.
z <- 1
## deltamethod (~ z / (x1 + x2), estmean, estvar) will not work.
## Instead, build up the formula as a string, and convert to a formula.
form <- sprintf("~ %f / (x1 + x2)", z)
form
deltamethod(as.formula(form), estmean, estvar)

Horizontal key drawing functions from ggstance in case it is deprecated

Description

Horizontal key drawing functions from ggstance in case it is deprecated

Usage

draw_key_hpath(data, params, size)

draw_key_pointrangeh(data, params, size)

Arguments

Value

A grid grob.

Expand covariate values choices and reference values varying one at a time

Description

Expand covariate values choices and reference values varying one at a time

Usage

expand_modelframe(rv, covcol = "covname", ...)

Arguments

Value

A data.frame with combination of covariates

Examples

reference.values <- data.frame(WT = 85, ALB = 45, SEX = 0)   
covcomb <- expand_modelframe(
  WT  = c(56, 72, 98, 128), # P05, P25, P75, P95 # ref is P50
ALB = c(40, 50),          # P05, P95 # ref is P50
  SEX = c(1),               # Reference is for SEX=0 (female)
  rv = reference.values)
covcomb

Forest plot

Description

Produce forest plots to visualize covariate effects

Usage

forest_plot(
  data,
  facet_formula = "covname~paramname",
  xlabel = "",
  ylabel = "",
  x_facet_text_size = 13,
  y_facet_text_size = 13,
  x_facet_text_angle = 0,
  y_facet_text_angle = 0,
  x_facet_text_vjust = 0.5,
  y_facet_text_vjust = 0.5,
  x_facet_text_hjust = 0.5,
  y_facet_text_hjust = 0.5,
  x_facet_text_col = "black",
  y_facet_text_col = "black",
  xy_facet_text_bold = TRUE,
  x_label_text_size = 16,
  y_label_text_size = 16,
  legend_title_size = 12,
  break_ylabel = FALSE,
  y_label_text_width = 25,
  table_text_size = 7,
  table_text_colour_overwrite = FALSE,
  table_text_colour = "none",
  base_size = 22,
  theme_benrich = FALSE,
  table_title = "",
  table_title_size = 15,
  ref_legend_text = "",
  area_legend_text = "",
  interval_legend_text = "",
  interval_legend_title = "",
  shape_legend_title = "",
  legend_order = c("pointinterval", "ref", "area", "shape"),
  combine_area_ref_legend = TRUE,
  combine_interval_shape_legend = FALSE,
  legend_position = "top",
  show_ref_area = TRUE,
  ref_area = c(0.8, 1.25),
  ref_area_col = "#BEBEBE50",
  show_ref_value = TRUE,
  ref_value = 1,
  ref_value_col = "black",
  ref_value_size = 1,
  ref_value_linetype = "dashed",
  ref_value_by_panel = FALSE,
  ref_value_by_panel_data = NULL,
  interval_col = "blue",
  interval_size = 1,
  interval_fatten = 4,
  interval_linewidth = 1,
  interval_shape = "circle small",
  bsv_col = "red",
  bsv_shape = "circle small",
  bsv_text_id = c("BSV", "bsv", "IIV", "Bsv"),
  interval_bsv_text = "",
  strip_col = "#E5E5E5",
  paramname_shape = FALSE,
  paramname_color = FALSE,
  legend_shape_reverse = FALSE,
  legend_color_reverse = FALSE,
  facet_switch = c("both", "y", "x", "none"),
  facet_scales = c("fixed", "free_y", "free_x", "free"),
  facet_space = c("fixed", "free_x", "free_y", "free"),
  facet_labeller = "label_value",
  label_wrap_width = 55,
  facet_labeller_multiline = FALSE,
  strip_placement = c("inside", "outside"),
  strip_outline = TRUE,
  facet_spacing = 5.5,
  major_x_ticks = NULL,
  major_x_labels = NULL,
  minor_x_ticks = NULL,
  x_range = NULL,
  logxscale = FALSE,
  show_yaxis_gridlines = TRUE,
  show_xaxis_gridlines = TRUE,
  show_table_facet_strip = "none",
  table_facet_switch = c("both", "y", "x", "none"),
  show_table_yaxis_tick_label = FALSE,
  reserve_table_xaxis_label_space = TRUE,
  table_panel_border = TRUE,
  table_position = c("right", "below", "none"),
  plot_table_ratio = 4,
  vertical_dodge_height = 0.8,
  legend_space_x_mult = 1,
  legend_ncol_interval = 1,
  legend_ncol_shape = 1,
  plot_margin = c(5.5, 5.5, 5.5, 5.5),
  table_margin = c(5.5, 5.5, 5.5, 5.5),
  legend_margin = c(0, 0.1, -0.1, 0),
  parse_xlabel = FALSE,
  parse_ylabel = FALSE,
  plot_title = "\n",
  return_list = FALSE
)

Arguments

Examples

library(dplyr)
library(ggplot2)

# Example 1

plotdata <- get_sample_data("forest-plot-table.csv")
plotdata <- plotdata %>%
  mutate(midlabel = format(round(mid,2), nsmall = 2),
         lowerlabel = format(round(lower,2), nsmall = 2),
         upperlabel = format(round(upper,2), nsmall = 2),
         LABEL = paste0(midlabel, " [", lowerlabel, "-", upperlabel, "]"))
param <- "BZD AUC"
plotdata <-  filter(plotdata,paramname==param)
plotdata$covname <- reorder(plotdata$covname,plotdata$upper,FUN =max)
plotdata$label <- reorder(plotdata$label,plotdata$scen)
covs <- c("WEIGHT","AGE")
plotdata <-  filter(plotdata,covname%in%covs)
forest_plot(plotdata,
            ref_legend_text = "Reference (vertical line)",
            area_legend_text = "Reference (vertical line)",
            xlabel = paste("Fold Change in", param, "Relative to Reference"),
            logxscale = TRUE, major_x_ticks =c(0.1,1,1.5),
            show_ref_area = FALSE,
            paramname_color =TRUE,
            interval_col =c("steelblue","red","steelblue","red"),
            facet_formula = "covname~.",
            facet_scales = "free_y",
            facet_space = "free_y",
            show_table_facet_strip = "none",
            table_position = "right",
            plot_title = "",
            plot_table_ratio = 4)

# Example 2

plotdata <- get_sample_data("forest-plot-table.csv")
plotdata <- plotdata %>%
  mutate(midlabel = format(round(mid,2), nsmall = 2),
         lowerlabel = format(round(lower,2), nsmall = 2),
         upperlabel = format(round(upper,2), nsmall = 2),
         LABEL = paste0(midlabel, " [", lowerlabel, "-", upperlabel, "]"))
param <- c("BZD AUC","BZD Cmax")
plotdata <-  filter(plotdata,paramname%in%param)
plotdata <-  filter(plotdata,covname%in%"WEIGHT")
plotdata$covname <- reorder(plotdata$covname,plotdata$upper,FUN =max)
plotdata$label <- reorder(plotdata$label,plotdata$scen)
forest_plot(plotdata,
            ref_legend_text = "Reference (vertical line)",
            area_legend_text = "Reference (vertical line)",
            xlabel = paste("Fold Change of Parameter", "Relative to Reference"),
            show_ref_area = FALSE,
            facet_formula = "covname~paramname",
            facet_scales = "free_y",
            facet_space = "free_y",
            x_facet_text_size = 10,
            y_facet_text_size = 10,
            y_label_text_size = 10,
            y_label_text_width = 15,
            x_label_text_size = 10,
            facet_switch = "both",
            show_table_facet_strip = "both",
            show_table_yaxis_tick_label = TRUE,
            table_position = "below",
            plot_title = "",
            plot_table_ratio = 1)
## Not run: 

# Example 3a

plotdata <- get_sample_data("forest-plot-table.csv")
plotdata <- plotdata %>%
  mutate(midlabel = format(round(mid,2), nsmall = 2),
         lowerlabel = format(round(lower,2), nsmall = 2),
         upperlabel = format(round(upper,2), nsmall = 2),
         LABEL = paste0(midlabel, " [", lowerlabel, "-", upperlabel, "]"))
plotdata$covname <- reorder(plotdata$covname,plotdata$upper,FUN =max)
plotdata$label <- reorder(plotdata$label,plotdata$scen)

plotdata$compound <- c(rep("1-OH",30),rep("BZD",30))
plotdata$paramname <- c(rep("AUC",15),rep("CMAX",15),rep("AUC",15),rep("CMAX",15))

forest_plot(plotdata,
            ref_area = c(0.8, 1.2),
           x_facet_text_size = 13,
           y_facet_text_size = 13,
            ref_legend_text = "Reference (vertical line)\n+/- 20% limits (colored area)",
            area_legend_text = "Reference (vertical line)\n+/- 20% limits (colored area)",
            xlabel = "Fold Change Relative to Parameter",
            facet_formula = covname~compound,
            facet_switch = "both",
            facet_scales = "free",
            facet_space = "fixed",
            paramname_shape = TRUE,
            legend_shape_reverse = TRUE,
            interval_shape = c("square","triangle"),
            paramname_color =  FALSE,
            combine_interval_shape_legend = FALSE,
            table_position = "right", plot_title = "",
            ref_area_col = rgb( col2rgb("gray50")[1], col2rgb("gray50")[2],col2rgb("gray50")[3],
                                max = 255, alpha = 0.1*255 ) ,
            interval_col = c("steelblue"),
            strip_col = "lightblue",
            plot_table_ratio = 1.5)
            
# Example 3b
        
plotdata$paramname <- c(rep("1-OH",30),rep("BZD",30))
plotdata$paramname2 <- c(rep("AUC",15),rep("CMAX",15),rep("AUC",15),rep("CMAX",15))
forest_plot(plotdata,
           show_ref_area = TRUE,
           x_facet_text_size = 13,
           y_facet_text_size = 13,
           ref_legend_text = "Reference (vertical line)",
           area_legend_text = "Reference (vertical line)",
           xlabel = "Fold Change Relative to Parameter",
           facet_formula = covname~paramname2,
           facet_switch = "both",
           facet_scales = "free",
           facet_space = "free",
           legend_order = c("shape","pointinterval","ref"),
           paramname_shape = TRUE,
           interval_shape = c("diamond","diamond filled",
                              "diamond","diamond filled"),
           paramname_color =  TRUE,
           combine_interval_shape_legend = TRUE,
           legend_shape_reverse = TRUE,
           legend_color_reverse = TRUE,
           interval_legend_title="Median (points)\n95% CI (horizontal lines)",
           table_position = "right", plot_title = "",
           ref_area_col = "gray85" ,
           interval_col = c("#ee3124", "#fdbb2f"),
           strip_col = "#475c6b",
           y_facet_text_col = "white",x_facet_text_col = "white",
           major_x_labels         = c("1/2", "0.8","1", "1.25", "2"),
           logxscale = TRUE, major_x_ticks =c(0.5,0.8,1,1.25,2),
           table_text_size = 5,
           plot_table_ratio = 1.5,
           ref_value_by_panel = TRUE,
           ref_value_by_panel_data = as.data.frame(
           plotdata %>% 
           distinct(paramname2,covname) %>% 
           dplyr::mutate(xintercept=ifelse(paramname2=="CMAX",1,1.2))))

# Example 3

plotdata <- get_sample_data("forestplotdatacpidata.csv")
forest_plot(plotdata,
            ref_area = c(0.8, 1.2),
            x_facet_text_size = 12,
            y_facet_text_size = 12,
            y_label_text_size = 10,
            x_label_text_size = 10,
            table_text_size = 6,
            plot_table_ratio = 1.5,
            ref_legend_text = "Reference (vertical line)\n+/- 20% limits (colored area)",
            area_legend_text = "Reference (vertical line)\n+/- 20% limits (colored area)",
            xlabel = "Fold Change Relative to RHZE",
            facet_formula = "covname~paramname",
            table_position = "below",
            show_table_facet_strip = "both",
            show_table_yaxis_tick_label = TRUE)

# Example 4
plotdata <- get_sample_data("dataforest.csv")
plotdata <- plotdata %>%
  dplyr::mutate(midlabel = format(round(mid,2), nsmall = 2),
         lowerlabel = format(round(lower,2), nsmall = 2),
         upperlabel = format(round(upper,2), nsmall = 2),
         LABEL = paste0(midlabel, " [", lowerlabel, "-", upperlabel, "]"))
plotdata <- plotdata %>%
  filter(covname%in%c("Weight"))
plotdata$label <- as.factor(as.character(plotdata$label))
plotdata$label <- factor(plotdata$label, c("36.2 kg","66 kg","110 kg"))
forest_plot(plotdata,
            ref_area = c(0.8, 1.2),
            x_facet_text_size = 13,
            y_facet_text_size = 13,
            ref_legend_text = "Reference (vertical line)\n+/- 20% limits (colored area)",
            area_legend_text = "Reference (vertical line)\n+/- 20% limits (colored area)",
            xlabel = "Fold Change Relative to Parameter",
            facet_formula = "covname~paramname",
            facet_switch = "both",
            facet_scales = "free",
            facet_space = "fixed",
            table_position = "below",
            plot_table_ratio = 1,
            show_table_facet_strip = "both",
            show_table_yaxis_tick_label = TRUE)

# Example 5

forest_plot(plotdata,
            ref_area = c(0.8, 1.2),
            x_facet_text_size = 13,
            y_facet_text_size = 13,
            ref_legend_text = "Reference (vertical line)\n+/- 20% limits (colored area)",
            area_legend_text = "Reference (vertical line)\n+/- 20% limits (colored area)",
            xlabel = "Fold Change Relative to Parameter",
            facet_formula = "covname~.",
            facet_switch = "both",
            facet_scales = "free",
            facet_space = "fixed",
            paramname_shape = TRUE,
            table_position = "none",
            ref_area_col = rgb( col2rgb("gray50")[1], col2rgb("gray50")[2],col2rgb("gray50")[3],
            max = 255, alpha = 0.1*255 ) ,
            interval_col = "steelblue",
            strip_col = "lightblue",
            plot_table_ratio = 1)

## End(Not run)

Get sample dataset

Description

Get a sample dataset that is included with the package to plot a forest plot.

Usage

get_sample_data(dataset = "dfall.csv")

Arguments

Prezista Drug Label Data

Description

A dataset containing an excerpt from the official Prezista FDA Drug Label to help in the app exploration.

Usage

prezista

Format

A dataset with 33 rows and 6 variables

covname

Covariate Name, a character variable with two values Protease Inihibitors and Other Antiretrovirals

label

Covariate value label, a character variable with several possible values

paramname

Parameter on which the effects are shown, a character variable with three possible values Cmax, AUC and Cmin

mid

Middle value for the effects, the median from the uncertainty distribution

lower

Lower value for the effects usually the 5% from the uncertainty distribution

upper

Upper value for the effects usually the 95% from the uncertainty distribution

Source

Table 16 from https://www.accessdata.fda.gov/drugsatfda_docs/label/2017/021976s045_202895s020lbl.pdf

Run the interactiveforestplot application

Description

Run the interactiveforestplot application.

Usage

run_interactiveforestplot(data = NULL)

Arguments

Examples

if (interactive()) {
  run_interactiveforestplot()
}

Weight Age CDC growth charts data

Description

Weight-for-age, 2 to 20 years, LMS parameters and selected smoothed weight percentiles in kilograms, by sex and age.

Usage

wtage

Format

A dataset with 436 rows and 14 variables

Sex

1=male; 2=female

Agemos

Age in months

L

skewness distribution parameter

M

location distribution parameter

S

scale distribution parameter

P3

Smoothed third percentile

P5

Smoothed fifth percentile

P10

Smoothed tenth percentile

P25

Smoothed twenty fifth percentile

P50

Smoothed fiftieth percentile

P75

Smoothed seventy fifth percentile

P90

Smoothed ninetieth percentile

P95

Smoothed ninety fifth percentile

P97

Smoothed ninety seventh percentile

Source

CDC website https://www.cdc.gov/growthcharts/data/zscore/wtage.csv