Code replication outcomes — code_replication

Different frameworks have been proposed to code replication outcomes. Here we code:

signal vs no-signal (i.e., significant vs all others)
consistent vs inconsistent (i.e., replication confidence interval overlaps original point estimate) Based on https://etiennelebel.com/documents/lebeletal%282018,ampss%29a-unified-framework-to-quantify-the-credibility-of-scientific-findings.pdf
and success vs failure (significant in right direction vs all others)

Usage

code_replication_outcomes(
  fred_data,
  es_original = "es_original",
  p_original = "p_value_original",
  p_replication = "p_value_replication",
  ci_lower_replication = "ci.lower_replication",
  ci_upper_replication = "ci.upper_replication",
  es_replication = "es_replication"
)

Arguments

fred_data: FReD dataset
es_original: Character. Name of original effect size column.
p_original: Character. Significance of original effect size.
p_replication: Character. Significance of replication effect size.
ci_lower_replication: Character. Lower bound of replication confidence interval.
ci_upper_replication: Character. Upper bound of replication confidence interval.
es_replication: Character. Name of replication effect size column.

Value

Augmented FReD dataset with replication outcome columns, including signal