#### New project update
**There is a new project where we introduce a Monte Carlo method for conducting power analysis in the context of network models. You can find more information and the manuscript at https://osf.io/qksd7. The accompanying `R` package `powerly` can be installed from CRAN and is avaliable at https://github.com/mihaiconstantin/powerly.**
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#### Current project overview
This study started as a Master's Thesis project for the Research Master in [Individual Differences and Assessment](https://www.tilburguniversity.edu/education/masters-programmes/research-master-psychology) at Tilburg University. It represents a pilot study for providing sample size recommendations for cross-sectional network models. The study was run with `R` package `netpaw` `v1.1.0`. This version of the package is permanently [available on GitHub as a release](https://github.com/mihaiconstantin/netpaw/releases/tag/v1.1.0) with commit SHA-1 [`9ca8392`](https://github.com/mihaiconstantin/netpaw/tree/9ca839210efe107bc8ccff38bc383d1d59e0b351).
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#### Main files of interest:
- [Manuscript - Sample Size Recommendations Cross-Sectional Networks.pdf](https://osf.io/tcfej)
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#### Relevant links:
- [GitHub public repository for the simulation R package as used in the pilot study (i.e., commit `9ca8392`)](https://github.com/mihaiconstantin/netpaw/tree/9ca839210efe107bc8ccff38bc383d1d59e0b351)
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***Note.*** At commit [`9ca8392`](https://github.com/mihaiconstantin/netpaw/tree/9ca839210efe107bc8ccff38bc383d1d59e0b351) the package was named `netPower` instead of `netpaw`.
