Merge branch 'main' of https://github.com/KyuriP/Discovering_CCM

Author: KyuriP

README.md

@@ -70,9 +70,9 @@ We examine three different cyclic causal discovery methods and investigate their
 
 | Folder                                     | Contents                                                         |
 | :----------------------------------------- | :--------------------------------------------------------------- |
-| [`manuscript`](./%20%20%20%20%20manuscript)               | It contains all relevant files associated with the main manuscript. <br> • `manuscript_KP.pdf`: the deliverable manuscript. <br> • `manuscript_KP.tex`:  a plaintext file that contains the source code to generate `manuscript_KP.pdf`.  <br> • `references.bib`: a bibliography file that contains all the references used in the manuscript. <br> • `kyuriapa.bst`: a BibTeX style file used to render [APA](https://apastyle.apa.org/style-grammar-guidelines/paper-format) formatting and style of references.|
-| [`simulation`](./%20%20%20%20simulation)       | It contains all `R` scripts required to run the simulation study.  <br> • `01_simulation.R`: simulate models, generate data, and run the algorithms. <br> • `02_simulation_results.R`: evaluate performance of algorithms and create figures. <br> • `03_sensitivity_analysis1.R`: run the secondary simulation with randomly sampled coefficients for the regression matrix $\mathbf{B}$. <br> • `04_sensitivity_analysis2.R`: conduct the secondary simulation by randomly sampling coefficients with *positive* values for the regression matrix $\mathbf{B}$. <br> • `05_sensitivity_analysis3.R`: run secondary analysis  with varying $\alpha$ levels. <br> • `06_extra_analysis.R`: investigate the unexpected patterns in the *5-variable dense* conditions from the main simulation study.<br> • `data`: output objects from all simulations are stored as `Rdata` files due to considerable processing time involved.      |
-| [`empirical_example`](./%20%20%20empirical_example) | It contains all R scripts required to run the empirical analysis. <br> • `01_empirical_analysis.R`: run empirical analysis (apply the CCD, FCI and CCI algorithms to an empirical data from [McNally et al. (2017)](https://www.cambridge.org/core/journals/psychological-medicine/article/abs/comorbid-obsessivecompulsive-disorder-and-depression-a-bayesian-network-approach/DAA4E2352A9E26809A4EAE35C366E900#supplementary-materials). <br> • `02_stability_analysis.R`: perform the stability analysis on the empirical data (*Appendix I* in the paper). <br> • `data`: raw data that is publicly available [here](https://www.cambridge.org/core/journals/psychological-medicine/article/abs/comorbid-obsessivecompulsive-disorder-and-depression-a-bayesian-network-approach/DAA4E2352A9E26809A4EAE35C366E900#supplementary-materials) and output objects from the sensitivity analysis saved as `Rdata` files.               |
+| [`manuscript`](./%20%20%20%20%20manuscript)               | It contains all relevant files associated with the main manuscript. <br> • `manuscript_KP.pdf`: the finalized manuscript. <br> • `manuscript_KP.tex`:  a plaintext file that contains the source code to generate the manuscript.  <br> • `references.bib`: a bibliography file that contains all the references used in the manuscript. <br> • `kyuriapa.bst`: a BibTeX style file used to render [APA](https://apastyle.apa.org/style-grammar-guidelines/paper-format) formatting and style of references.|
+| [`simulation`](./%20%20%20%20simulation)       | It contains all `R` scripts required to run the simulation study.  <br> • `01_simulation.R`: simulate models, generate data, and run the algorithms. <br> • `02_simulation_results.R`: evaluate performance of algorithms and create figures. <br> • `03_sensitivity_analysis1.R`: run the secondary simulation with randomly sampled coefficients for the regression matrix $\mathbf{B}$. <br> • `04_sensitivity_analysis2.R`: conduct the secondary simulation by randomly sampling coefficients with *positive* values for the regression matrix $\mathbf{B}$. <br> • `05_sensitivity_analysis3.R`: run secondary analysis  with varying $\alpha$ levels. <br> • `06_extra_analysis.R`: investigate the unexpected patterns in the *5-variable dense* conditions from the main simulation study.<br> • `data`: results from all simulations are stored as `Rdata` files because of the considerable processing time required to run them.   |
+| [`empirical_example`](./%20%20%20empirical_example) | It contains all R scripts required to run the empirical analysis. <br> • `01_empirical_analysis.R`: run the empirical analysis by applying the CCD, FCI and CCI algorithms to empirical data from [McNally et al. (2017)](https://www.cambridge.org/core/journals/psychological-medicine/article/abs/comorbid-obsessivecompulsive-disorder-and-depression-a-bayesian-network-approach/DAA4E2352A9E26809A4EAE35C366E900#supplementary-materials). <br> • `02_stability_analysis.R`: perform the stability analysis on the empirical data (*Appendix I* in the paper). <br> • `data`: raw data that is publicly available [here](https://www.cambridge.org/core/journals/psychological-medicine/article/abs/comorbid-obsessivecompulsive-disorder-and-depression-a-bayesian-network-approach/DAA4E2352A9E26809A4EAE35C366E900#supplementary-materials) and output objects from the sensitivity analysis saved as `Rdata` files.               |
 | [`utils`](./%20%20utils)               | It includes all the supporting functions required to run the other `R` scripts for conducting analyses. |
 | [`supplementary_material`](./%20supplementary_material)           |It contains all files related to the supplementary material of the paper. <br> The supplementary material can be accessed via this [link](https://kyurip.quarto.pub/discovering-cyclic-causal-models/).|
 | [`figures`](./figures)               | It contains all the figures that are presented in the paper.                    |