General package update (#10)

* testing new type hierarchy

* intermediate commit

* update reliability for PsychometricTest

* implement ten berge mu

* rename functions

* remove unused dependencies

* remove unused files

* add compat entries

* new reliability interface

* refactor reliability

* refactor lambda4

* add some docs

* postpone PsychometricTests integration

* increase precision in mu

* update glb

* import kwdef

* remove unused deps

* add basic precompilation

.JuliaFormatter.toml

@@ -0,0 +1,3 @@
+always_for_in = true
+short_to_long_function_def = true
+always_use_return = true

.github/workflows/CI.yml

@@ -18,7 +18,6 @@ jobs:
       fail-fast: false
       matrix:
         version:
-          - '1.6'
           - '1.8'
           - 'nightly'
         os:

.gitignore

@@ -1,2 +1,4 @@
 /Manifest.toml
-.vscode
+.vscode
+
+.DS_Store

Project.toml

@@ -4,19 +4,34 @@ authors = ["Philipp Gewessler <p.gewessler@gmx.at> and constributors"]
 version = "0.1.0"
 
 [deps]
+Bootstrap = "e28b5b4c-05e8-5b66-bc03-6f0c0a0a06e0"
 Combinatorics = "861a8166-3701-5b0c-9a16-15d98fcdc6aa"
 Distributions = "31c24e10-a181-5473-b8eb-7969acd0382f"
-InvertedIndices = "41ab1584-1d38-5bbf-9106-f11c6c58b48f"
 JuMP = "4076af6c-e467-56ae-b986-b466b2749572"
 LinearAlgebra = "37e2e46d-f89d-539d-b4ee-838fcccc9c8e"
+OrderedCollections = "bac558e1-5e72-5ebc-8fee-abe8a469f55d"
+PrecompileTools = "aea7be01-6a6a-4083-8856-8a6e6704d82a"
+Printf = "de0858da-6303-5e67-8744-51eddeeeb8d7"
 ProgressMeter = "92933f4c-e287-5a05-a399-4b506db050ca"
 Random = "9a3f8284-a2c9-5f02-9a11-845980a1fd5c"
+Reexport = "189a3867-3050-52da-a836-e630ba90ab69"
 SCS = "c946c3f1-0d1f-5ce8-9dea-7daa1f7e2d13"
-Statistics = "10745b16-79ce-11e8-11f9-7d13ad32a3b2"
+StatsAPI = "82ae8749-77ed-4fe6-ae5f-f523153014b0"
 StatsBase = "2913bbd2-ae8a-5f71-8c99-4fb6c76f3a91"
+Tables = "bd369af6-aec1-5ad0-b16a-f7cc5008161c"
+Term = "22787eb5-b846-44ae-b979-8e399b8463ab"
 
 [compat]
-julia = "1.6"
+Combinatorics = "1"
+Distributions = "0.25"
+JuMP = "1"
+PrecompileTools = "1"
+ProgressMeter = "1"
+SCS = "2"
+StatsBase = "0.34"
+Tables = "1"
+Term = "2"
+julia = "1.8"
 
 [extras]
 Test = "8dfed614-e22c-5e08-85e1-65c5234f0b40"

README.md

@@ -1,7 +1,50 @@
-# ClassicalTestTheory
+# ClassicalTestTheory.jl
 
 [![Stable](https://img.shields.io/badge/docs-stable-blue.svg)](https://p-gw.github.io/ClassicalTestTheory.jl/stable)
 [![Dev](https://img.shields.io/badge/docs-dev-blue.svg)](https://p-gw.github.io/ClassicalTestTheory.jl/dev)
 [![Build Status](https://github.com/p-gw/ClassicalTestTheory.jl/actions/workflows/CI.yml/badge.svg?branch=main)](https://github.com/p-gw/ClassicalTestTheory.jl/actions/workflows/CI.yml?query=branch%3Amain)
 [![Coverage](https://codecov.io/gh/p-gw/ClassicalTestTheory.jl/branch/main/graph/badge.svg)](https://codecov.io/gh/p-gw/ClassicalTestTheory.jl)
 
+ClassicalTestTheory.jl is a Julia package for data analysis using [Classical Test Theory](https://en.wikipedia.org/wiki/Classical_test_theory#:~:text=It%20is%20a%20theory%20of,the%20reliability%20of%20psychological%20tests.).
+
+## Installation
+```julia
+] add https://github.com/p-gw/ClassicalTestTheory.jl.git
+```
+
+## Getting started
+ClassicalTestTheory.jl provides two entry points to doing data analsis. 
+The input data can either be a numeric `Matrix` or a [`PsychometricTest`](https://github.com/JuliaPsychometrics/PsychometricTests.jl). 
+While `Matrix` methods provide full functionality, `PsychometricTest` methods provide some 
+additional convenience such as scale analysis. 
+For details on how to use ClassicalTestTheory.jl with `PsychometricTest` see [XXX](#).
+
+Consider some input data `x`,
+
+```julia-repl
+julia> n_persons = 100;
+julia> n_items = 8;
+
+julia> x = rand(0:100, n_persons, n_items);
+```
+
+we can get some descriptive analysis of the items,
+
+```julia
+itemanalysis(x)
+```
+
+or estimate the internal consistency (e.g. using Cronbach's alpha)
+
+```julia
+reliability(x, Alpha())
+```
+
+The package will automatically calculate the coefficient from the data and construct appropriate confidence intervals.
+
+To get multiple estimates of reliability just pass a vector of methods:
+
+```julia
+coefficients = [Alpha(), GLB(), Mu(2)]
+reliability(x, coefficients)
+```