## ----include = FALSE----------------------------------------------------------
knitr::opts_chunk$set(collapse = TRUE, comment = "#>")

## ----setup--------------------------------------------------------------------
library(respondeR)

## -----------------------------------------------------------------------------
sample_responder_data

## -----------------------------------------------------------------------------
impute_change_sd("prepost", sd_baseline = 2.1, sd_final = 2.4, r = 0.5)

## -----------------------------------------------------------------------------
res <- responder_analysis(sample_responder_data, mid = 1)
res

## -----------------------------------------------------------------------------
res$rd
head(as.data.frame(res), 2)

## -----------------------------------------------------------------------------
responder_rd_individual(sample_responder_data, mid = 1)

## ----fig.width = 6.5, fig.height = 3.4, fig.alt = "Forest plot of per-study responder risk differences with pooled estimates"----
plot(res)

## -----------------------------------------------------------------------------
responder_analysis(sample_responder_data, mid = 1, method = "individual",
                   pooling = "random", ci_method = "hksj_adhoc")

## ----fig.width = 6, fig.height = 3.6, fig.alt = "Pooled risk difference against the MID threshold with pointwise confidence bands"----
curve <- responder_curve(sample_responder_data, mids = seq(0, 2, by = 0.25))
plot(curve, at = 1)

## -----------------------------------------------------------------------------
ind <- responder_analysis(sample_responder_data, mid = 1, method = "individual")
responder_sof(ind)
responder_sof(ind, control_risk = c(0.1, 0.4))

## -----------------------------------------------------------------------------
cles <- responder_cles(sample_responder_data)
sprintf("CLES = %.1f%% (%.1f%% to %.1f%%)",
        100 * cles$cles, 100 * cles$cles_lb, 100 * cles$cles_ub)

## -----------------------------------------------------------------------------
vas <- responder_analysis(vas_pain, mid = -1.5, direction = "lower",
                          pooling = "random", ci_method = "hksj_adhoc")
vas

## ----include = FALSE----------------------------------------------------------
v <- as.data.frame(vas)
ind_rd <- round(100 * v$rd[v$method == "individual"])

## -----------------------------------------------------------------------------
responder_sof(vas[vas$method == "individual", ])

## -----------------------------------------------------------------------------
cles <- responder_cles(vas_pain, direction = "lower", pooling = "random")
sprintf("A treated patient has less pain than a control %.0f%% of the time (%.0f%% to %.0f%%)",
        100 * cles$cles, 100 * cles$cles_lb, 100 * cles$cles_ub)

## ----eval = FALSE-------------------------------------------------------------
# launch_responder_analysis()