Package index • respondeR

Responder analysis

Pooled responder proportions and between-arm effect measures.

responder_analysis(): Responder analysis of continuous trial outcomes
print(<responder_result>) `[`(<responder_result>) summary(<responder_result>) print(<summary.responder_result>) as.data.frame(<responder_result>) plot(<responder_result>): Methods for responder analysis results
responder_rd_individual(): Per-study responder risk differences
responder_proportions(): Responder proportions from continuous arm summaries

Fitted meta-analyses and pooled effects

responder_from_effect(): Responder measures from a pooled relative effect
as_responder_data(): Extract a responder-analysis data frame from a meta-analysis object

Reporting

Threshold sensitivity and summary-of-findings tables.

responder_curve(): Responder measures across a range of MID thresholds
plot(<responder_curve>): Plot a responder curve
responder_sof(): GRADE summary-of-findings rows from a responder analysis
format_responder_results(): Format responder-analysis results for display

Threshold-free

Effect size that needs no MID.

responder_cles(): Common-language effect size (probabilistic index)

Data preparation

impute_change_sd(): Impute the standard deviation of a change score
estimate_change_cor(): Estimate the baseline-to-final correlation from fully reported studies

App

launch_responder_analysis(): Launch the Responder Analysis Shiny application

Data

sample_responder_data: Example responder-analysis dataset
vas_pain: VAS pain change scores from a spinal-health exercise meta-analysis