cIPMA: An R package for combined importance-performance map analysis

Combined importance–performance map analysis (cIPMA) extends partial least squares structural equation modeling (PLS-SEM) by integrating importance as sufficiency estimates with bottleneck diagnostics necessity thresholds from Necessary Condition Analysis (NCA). While conceptually powerful, the current workflow for cIPMA is fragmented, typically requiring commercial software, manual data rescaling, and external spreadsheet transformation and visualization, which increase the risk of human error and reduce reproducibility. This article introduces cIPMA, an open-source R package that automates the complete cIPMA workflow on top of seminr for PLS-SEM and NCA for necessary condition analysis. The package implements the rescaling and weighting procedures required for importance–performance maps, calls NCA’s CE-FDH ceiling technique to obtain necessity effect sizes and bottleneck tables, and provides publication-ready visualization. Using the cIPMA package, researchers can perform a full cIPMA analysis in a single reproducible script and reduce the likelihood of specification and transcription errors. The package provides a transparent, open-source implementation that enables researchers to explore the interplay between probabilistic sufficiency and necessity logics in behavioral research while adhering to the established methodological requirements of cIPMA.