plot_phr.RdCreate a dataset that can be used to produce a PHR cumulative incidence curves and effect plots.
plot_phr(
...,
effect_measure_type = NULL,
smooth = FALSE,
alpha = 0.05,
ref = 1
)cumrisk objects supplied as a list or as seperate arguments
The type of effect to plot (default NULL = plots cumulative risk funtions), valid options include: RD,CD,RR, CR,AR, logRR.
A flag to indicate the use of LOESS smoothing for risk difference
The desired nominal significance level of the confidence intervals.
Identifies the treatmet group in the supplied object(s) to be used as a referent category for risk differecence curves. Defaults to one.
A tibble in the format for upload to a PHR using nswpr
models = specify_models(identify_treatment(Statin, formula = ~DxRisk ),
identify_censoring(EndofEnrollment, formula = ~DxRisk),
identify_outcome(Death))
fit = estimate_ipwrisk(example1, models,
times = seq(0,24,0.1),
labels = c("IPTCW main analysis"))
plot_phr(fit)
#> # A tibble: 482 × 7
#> time estimate lcl ucl group_label grp1 grp2
#> <dbl> <dbl> <dbl> <dbl> <fct> <fct> <fct>
#> 1 0 0 0 0 Control IPTCW main analysis NA
#> 2 0.1 0 0 0 Control IPTCW main analysis NA
#> 3 0.2 0 0 0 Control IPTCW main analysis NA
#> 4 0.3 0.00127 0 0.00255 Control IPTCW main analysis NA
#> 5 0.4 0.00127 0 0.00255 Control IPTCW main analysis NA
#> 6 0.5 0.00164 0.000261 0.00302 Control IPTCW main analysis NA
#> 7 0.6 0.00349 0.000325 0.00665 Control IPTCW main analysis NA
#> 8 0.7 0.00426 0.000920 0.00759 Control IPTCW main analysis NA
#> 9 0.8 0.00583 0.00214 0.00951 Control IPTCW main analysis NA
#> 10 0.9 0.00599 0.00230 0.00969 Control IPTCW main analysis NA
#> # … with 472 more rows