Add validation analysis

.gitignore

@@ -182,3 +182,6 @@ firestore.indexes.json
 
 # Typedoc generated docs
 docs
+
+validation/data
+validation/simulation/resp

README.md

@@ -37,12 +37,25 @@ const numItems = cat.nItems;
 
 // find the next available item from an input array of stimuli based on a selection method
 
-const stimuli = [{difficulty: -3,  item: 'item1'}, {difficulty: -2,  item: 'item2'}];
+const stimuli = [{difficulty: -3, item: 'item1'}, {difficulty: -2,  item: 'item2'}];
 
 const nextItem = cat.findNextItem(stimuli, 'MFI');
 ```
 
+## Validations
+### Validation of theta estimate and theta standard error
+Reference software: mirt (Chalmers, 2012)
+![img.png](validation/plots/jsCAT_validation_1.png)
+
+### Validation of MFI algorithm 
+Reference software: catR (Magis et al., 2017)
+![img_1.png](validation/plots/jsCAT_validation_2.png)
+
+
 ## References
+Chalmers, R. P. (2012). mirt: A multidimensional item response theory package for the R environment. Journal of Statistical Software.
+
+Magis, D., & Barrada, J. R. (2017). Computerized adaptive testing with R: Recent updates of the package catR. Journal of Statistical Software, 76, 1-19.
 
 Lucas Duailibe, irt-js, (2019), GitHub repository, https://github.com/geekie/irt-js
 

paper/paper.md

@@ -9,16 +9,18 @@ authors:
       affiliation: 1
     - name: Jason D. Yeatman
       orcid: 0000-0002-2686-1293
-      affiliation: "1, 2"
+      affiliation: "1, 2, 3"
     - name: Adam Richie-Halford
       orcid: 0000-0001-9276-9084
       affiliation: "1, 2"
 affiliations:
-  - name: # TODO (Anya) Add GSE affiliation
-    index: 1
-  - name: # TODO (Anya) Add DBP affiliation
+  - name: Stanford University Graduate School of Education
+    index: 1 
+  - name: Stanford University School of Medicine, Division of Developmental Behavioral Pediatrics
     index: 2
-date: 13 March 2023
+  - name: Stanford University Department of Psychology
+    index: 3
+date: 5 October 2023
 bibliography: paper.bib
 ---
 
@@ -33,13 +35,11 @@ bibliography: paper.bib
 
 # Summary
 
-jsCAT is a JavaScript library to support a fully client-side adaptive testing
-environment. Computerized Adaptive Testing (CAT) is a type of assessment that
-uses computer algorithms to dynamically adjust the difficulty of questions based
-on a test-taker's performance. Although CAT has been widely researched and
-applied in areas such as education and psychology (e.g., GRE and Duolingo),
-designing a CAT solution suitable for large-scale school administration remains
-a challenge. Imagine we are administering 500 children in a school at the same
+jsCAT is a JavaScript library to support fully client-side computerized adaptive testing. Computerized Adaptive Testing 
+is an approach to assessment that uses an algorithm to select the most informative item to present to a test-taker 
+based on their previous responses. Although CAT has been widely researched and applied in areas such as education 
+and psychology (e.g., GRE and Duolingo), designing a CAT solution suitable for large-scale school administration 
+remains a challenge. Imagine we are administering 500 children in a school at the same
 time, where reliable wifi is not guaranteed at all times, which means that we
 should minimize data communications between the client and servers to prevent
 disruptions. Most existing adaptive testing solutions, written in R or Python,
@@ -78,4 +78,4 @@ Funding Acquisition: JY.
 
 # References
 
-<!-- TODO (Anya): Add references in the paper.bib file -->
+<!-- TODO (Anya): Add references in the paper.bib file -->