auto_detect_columns

Provides comprehensive analytics, reporting, and testing capabilities
for systematic review search strategies. The package focuses on validating search
performance, generating standardized 'PRISMA'-compliant reports, and ensuring
reproducibility in evidence synthesis. Features include precision-recall analysis,
cross-database performance comparison, benchmark validation against gold standards,
sensitivity analysis, temporal coverage assessment, automated report generation,
and statistical comparison of search strategies. Supports multiple export formats
including 'CSV', 'Excel', 'RIS', 'BibTeX', and 'EndNote'. Includes tools for duplicate
detection, search strategy optimization, cross-validation frameworks, meta-analysis
of benchmark results, power analysis for study design, and reproducibility package
creation. Optionally connects to 'PubMed' for direct database searching and real-time
strategy comparison using the 'E-utilities' 'API'. Enhanced with bootstrap comparison
methods, 'McNemar' test for strategy evaluation, and comprehensive visualization tools
for performance assessment. Methods based on Manning et al. (2008)
for information retrieval metrics, Moher et al. (2009)
for 'PRISMA' guidelines, and Sampson et al. (2006) for
systematic review search methodology.

Chao Liu Liu

searchAnalyzeR

Advanced Analytics and Testing Framework for Systematic Review
Search Strategies

auto_detect_columns function

<dl><dt>results</dt>
<dd>Data frame to analyze</dd></dl>

Arguments

Auto-detect Column Mappings — auto_detect_columns

<dl>

<dt>results</dt>
<dd>Data frame to analyze</dd>

</dl>

auto_detect_columns: Auto-detect Column Mappings

Description

Usage

Value

Arguments