Title: Model selection for index of asymmetry distribution
Description: Calculate AIC's and AICc's of unimodal model (one normal distribution) and bimodal model(a mixture of two normal distributions) which fit the distribution of indices of asymmetry (IAS), and plot their density, to help determine IAS distribution is unimodel or bimodal.

Title: Model Selection for Index of Asymmetry Distribution
Description: Calculate AIC's and AICc's of unimodal model (one normal distribution) and bimodal model(a mixture of two normal distributions) which fit the distribution of indices of asymmetry (IAS), and plot their density, to help determine IAS distribution is unimodal or bimodal.

Title: Functions to use with data from the Implicit Association Test
Description: Contains a function to implement the standard D-Scoring algorithm
(Greenwald, Banaji, & Nosek, 2003) for Implicit Association Test (IAT)
data, as well as various other functions to produce plots of IAT data.
Collate: 'cleanIAT.R' 'plotIIV.R' 'plotIndVar.R' 'plotItemErr.R'
Packaged: 2013-09-24 02:50:46 UTC; danmartin

Packaged: 2014-07-11 22:23:48 UTC; danmartin

Title: Cleaning and Visualizing Implicit Association Test (IAT) Data
Description: Implements the standard D-Scoring algorithm
data and includes plotting capabilities for exploring raw IAT data.
Packaged: 2016-04-29 13:28:21 UTC; danmartin

Title: Scoring Algorithm for the Implicit Association Test (IAT)
Description: This minimalist package is designed to quickly score raw data outputted from an Implicit Association Test (IAT; Greenwald, McGhee, & Schwartz, 1998) <doi:10.1037/0022-3514.74.6.1464>. IAT scores are calculated as specified by Greenwald, Nosek, and Banaji (2003) <doi:10.1037/0022-3514.85.2.197>. Outputted values can be interpreted as effect sizes. The input function consists of three arguments. First, indicate the name of the dataset to be analyzed. This is the only required input. Second, indicate the number of trials in your entire IAT (the default is set to 220, which is typical for most IATs). Last, indicate whether congruent trials (e.g., flowers and pleasant) or incongruent trials (e.g., guns and pleasant) were presented first for this participant (the default is set to congruent). The script will tell you how long it took to run the code, the effect size for the participant, and whether that participant should be excluded based on the criteria outlined by Greenwald et al. (2003). Data files should consist of six columns organized in order as follows: Block (0-6), trial (0-19 for training blocks, 0-39 for test blocks), category (dependent on your IAT), the type of item within that category (dependent on your IAT), a dummy variable indicating whether the participant was correct or incorrect on that trial (0=correct, 1=incorrect), and the participant’s reaction time (in milliseconds). Three sample datasets are included in this package (labeled 'IAT', 'TooFastIAT', and 'BriefIAT') to practice with.