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Assess Multiple Studies with RoB 2

Source: R/bias_rob2.R
assess_rob2_batch.Rd

Performs RoB 2 risk of bias assessment for multiple studies from a data frame.

Usage

assess_rob2_batch(data, .suppress_messages = FALSE)

Arguments

data

Data frame with columns for study_id, domain judgments, and optionally supporting text. Required columns:

  • study_id: Study identifier

  • d1_randomization: Domain 1 judgment

  • d2_deviations: Domain 2 judgment

  • d3_missing_data: Domain 3 judgment

  • d4_measurement: Domain 4 judgment

  • d5_selection: Domain 5 judgment

Optional columns: d1_support, d2_support, d3_support, d4_support, d5_support, outcome, overall, overall_justification

.suppress_messages

Logical. If TRUE, suppresses individual assessment messages. Default: FALSE

Value

A list of RoB2Result objects, named by study_id.

Examples

if (FALSE) { # \dontrun{
# Create data frame with study assessments
rob_data <- data.frame(
  study_id = c("STUDY001", "STUDY002", "STUDY003"),
  d1_randomization = c("Low", "Low", "High"),
  d2_deviations = c("Low", "Some concerns", "Low"),
  d3_missing_data = c("Low", "Low", "Low"),
  d4_measurement = c("Some concerns", "Low", "Low"),
  d5_selection = c("Low", "Low", "Low"),
  d4_support = c("Unblinded assessment", "", ""),
  outcome = c("OS", "PFS", "OS"),
  stringsAsFactors = FALSE
)

results <- assess_rob2_batch(rob_data)
results[["STUDY001"]]@overall

# Get summary of all assessments
summary_df <- do.call(rbind, lapply(results, function(r) r@summary_df))
} # }