inference function

Inference calculations for sequential meta-analysis

Calculates point-estimates, p-values and confidence intervals. Computes naive inference and TSA-adjusted confidence intervals. If the meta-analysis crosses a alpha-spending boundary, a binding beta-spending boundary or reached the sequential RIS, stage-wise ordered inference is also calculated. This function is not supposed to be used individually for Trial Sequential Analysis (TSA). RTSA() is recommended for TSA.

inference(
  bounds,
  timing,
  ana_times,
  ma,
  fixed,
  org_timing,
  inf_type = "sw",
  conf_level = 0.95,
  final_analysis = FALSE,
  tol = 1e-15
)

Arguments

• bounds: The boundaries for the analysis as calculated by the boundaries() function in RTSA.
• timing: The timing of the studies relative to the sequential RIS. A vector consisting of values equal to the proportion of study participants out of the sequential RIS.
• ana_times: The analysis times presented as a vector. Describes at which studies the meta-analyses were performed. If one expects that the meta-analysis was updated per study a vector from 1 to the number of studies included can be used.
• ma: A metaanalysis object from the metaanalysis function.
• fixed: Whether the analysis is for fixed-effect or random-effects meta-analysis. Options are TRUE (meta-analysis is fixed-effect) or FALSE (meta-analysis is random-effects).
• org_timing: The timing of all included studies as a proportion of RIS and not sequential RIS.
• inf_type: For now only option is "sw" (stage-wise). Type of inference used for point estimates, confidence intervals and p-values.
• conf_level: The confidence interval level. Defaults to 0.95 which is 95%.
• final_analysis: Whether or not the this analysis is considered the final analysis.
• tol: The tolerance level. Set to 1e+09.

Returns

A data.frame of cumulative meta-analysis results including stopping boundaries and a list of conditional sequential inference to be parsed to RTSA - results_df: A data.frame containing information about: Cumulative test values, cumulative outcomes, timing of trials, stopping boundaries (alpha_upper, alpha_lower, beta_upper, beta_lower), naive confidence intervals, TSA-adjusted confidence intervals, cumulative p-values and standard deviations.

• seq_inf: If the meta-analysis crosses an alpha-spending boundary, a binding beta-spending boundary or reaches the required information size inference conditional on stopping is provided. A median unbiased estimate, lower and upper confidence interval, and p-value is calculated based on stage-wise ordering.

Examples

ma <- metaanalysis(data = perioOxy, outcome = "RR", mc = 0.8)
sts <- ma$ris$NR_D2$NR_D2_full
timing <- cumsum(perioOxy$nI + perioOxy$nC)/sts
bound_oxy <- boundaries(timing = timing, alpha = 0.05, beta = 0.2, side = 2,
                       futility = "none", es_alpha = "esOF")
inference(timing = bound_oxy$inf_frac, bounds = bound_oxy, ma = ma,fixed = FALSE,
ana_times = 1:length(timing), org_timing = timing)