03_omegaReading.Rmd

---
title: | 
  | Categorical Omega calculations for NRC reading scales
output:
  html_document:
    toc: true
    toc_depth: 5
    code_folding: show
---

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__Code written:__ 2019-12-02  
__Last run:__ `r Sys.Date()`   
__Authors:__ Navona Calarco & Colin Decker  
__Website:__ https://rpubs.com/navona/Mar_categoricalOmegaReading
__Git repo:__ https://github.com/navonacalarco/NRC_Mar  
__R version desktop:__ platform: x86_64-apple-darwin15.6.0, arch: x86_64, os: darwin15.6.0, system: x86_64, darwin15.6.0, major: 3, minor: 5.1, year: 2018, month: 07, day: 02, svn rev: 74947, language: R, version.string: R version 3.5.1 (2018-07-02), nickname: Feather Spray  

-----

__Description.__  
This notebook details the code used to run categorical omega on the NRC reading scales. We use categorical as the scales only have 2 levels (right/wrong).

__Relevant documentation__.  
https://www.rdocumentation.org/packages/MBESS/versions/4.6.0/topics/ci.reliability #MBESS  
https://github.com/cran/MBESS/blob/master/R/ci.reliability.R #code underlying ci.reliability()  


__Set up__

```{r setup}

#conditional install and load libraries
if (!require("pacman")) install.packages("pacman")
pacman::p_load(MBESS, tictoc, lavaan)

#read in test df
df_analogies <- read.csv(dir('../data/out/reading', full.names=T, pattern="^df_analogies_"))
df_sentences <- read.csv(dir('../data/out/reading', full.names=T, pattern="^df_sentences_"))
df_synonyms <- read.csv(dir('../data/out/reading', full.names=T, pattern="^df_synonyms_"))

```

```{r}

#check to see if no variance in any items -- none, great
sum(apply(df_analogies, 2, var) == 0) 
sum(apply(df_sentences, 2, var) == 0) 
sum(apply(df_synonyms, 2, var) == 0) 

#run models
ci.reliability(data=df_analogies, type="categorical", conf.level = 0.95, interval.type="bca", B=1000)
ci.reliability(data=df_sentences, type="categorical", conf.level = 0.95, interval.type="bca", B=1000)
ci.reliability(data=df_synonyms, type="categorical", conf.level = 0.95, interval.type="bca", B=1000)

```