Plot all effect estimates against p values
all_plot()
generates a scatter plot with effect estimates of all possible models again p values.
all_plot( data, xlabels = c(0, 0.001, 0.01, 0.05, 0.2, 0.5, 1), xlim = c(0, 1), xlab = "P value", ylim = NULL, ylab = NULL, yscale_log = FALSE, title = NULL )
data
: Object from all_cox
, all_glm
, all_speedglm
, or all_glm
, including all effect estimate values.xlabels
: Numeric vector x-axis tick labels. Default is "c(0, 0.001, 0.01, 0.05, 0.2, 0.5, 1)"
.xlim
: Vector of 2 numeric values for x-axis limits. Default is "c(0, 1)"
.xlab
: Character string for x-axis name. Default is "P value"
.ylim
: Vector of 2 numeric values for y-axis limits.ylab
: Character string for y-axis name. Default depends on original model types.yscale_log
: TRUE or FALSE to re-scale y-axis to "log10". Default is "FALSE"
.title
: Character for plot title. Default is "NULL"
.A ggplot2
object: scatter plot
vlist <- c("Age", "Sex", "Married", "BMI", "Education", "Income") results <- all_cox(crude = "Surv(t0, t1, Endpoint) ~ Diabetes", xlist = vlist, data = diab_df) all_plot(results)
Useful links