Open Source Mac Psychology Software

IRAMUTEQ : Interface de R pour les Analyses Multidimensionnelles de Textes et de Questionnaires. Logiciel de traitement de données pour des corpus texte ou de type individus/caractères. Permet notamment de réaliser des analyses de type "ALCESTE"

Estimating G-DINA model and a variety of widely-used models subsumed by the G-DINA model, including the DINA model, DINO model, additive-CDM (A-CDM), linear logistic model (LLM), reduced reparametrized unified model (RRUM), multiple-strategy DINA model for dichotomous responses. Estimating models within the G-DINA model framework using user-specified design matrix and link functions. Estimating Bugs-DINA, DINO and G-DINA models for dichotomous responses. Estimating sequential G-DINA model for ordinal and nominal responses. Estimating the generalized multiple-strategy cognitive diagnosis models (experimental). Estimating the diagnostic tree model (experimental). Estimating multiple-choice models. Modelling independent, saturated, higher-order, loglinear smoothed, and structured joint attribute distribution. Accommodating multiple-group model analysis. Imposing monotonic constrained success probabilities. Accommodating binary and polytomous attributes.

This is a package for Structural Equation Modeling in development. It is written for extensibility, that is, you can easily define your own objective functions and other parts of the model. At the same time, it is (very) fast. We provide fast objective functions, gradients, and for some cases hessians as well as approximations thereof. As a user, you can easily define custom loss functions. For those, you can decide to provide analytical gradients or use finite difference approximation / automatic differentiation. You can choose to mix loss functions natively found in this package and those you provide. In such cases, you optimize over a sum of different objectives (e.g. ML + Ridge). This strategy also applies to gradients, where you may supply analytic gradients or opt for automatic differentiation or mixed analytical and automatic differentiation. You may consider using this package if you need extensibility and/or speed, and if you want to extend SEM.

The psychmeta package provides tools for computing bare-bones and psychometric meta-analyses and for generating psychometric data for use in meta-analysis simulations. Currently, the package supports bare-bones, individual-correction, and artifact-distribution methods for meta-analyzing correlations and d values. Please refer to the overview tutorial vignette for an introduction to psychmeta’s functions and workflows. psychmeta is hosted on both CRAN and GitHub. Documentation for psychmeta’s functions is available in the package’s PDF manual. Includes tools for converting effect sizes, computing sporadic artifact corrections, reshaping meta-analytic databases, computing multivariate corrections for range variation, and more.

EyeMap is a visualization and analysis tool for text reading eye movement data. It can process Unicode, proportion/non-proportion and spaced/unspaced reading materials, which supports various languages and experiment methods.

The Success Mindmap is a toolkit that allows you to map out a clear concise snapshot of your life. The toolkit allows you to set milestones in your life path, ones that you can track back to in the future so that you can make better choices in the future.

The project will deliver tools, libraries and recipes (combinations of tools and algorithms) to allow end users the capability to conduct empirical analysis where the results can be used to support claims of validity associated with an assessment.

This project aims to develop open source psychometric data analysis software, including estimation software for Rasch and Item Response Theory (IRT) models for both dichotomous and polytomous test items.

On The Mark is a video and image scoring system that allows one to mark any number of events and durations through a simple, easy-to-use graphical interface.

This Matlab toolbox runs a GLM on graph theoretic network properties in brain networks. The GLM accepts continuous & categorical between-participant predictors and categorical within-participant predictors. Significance is determined via non-parametric permutation tests. The toolbox allows testing of both fully connected and thresholded networks (based on a range of thresholds). The toolbox also provides a data processing path for resting state fMRI data. Several options for partialing nuisance signals are available, including local and total white matter signal (Jo et al., 2013), calculation of Saad et al. (2013)'s GCOR, and the use of Chen et al. (2012) GNI method to determine whether global signal partialing is needed. In addition, Power et al. (2014)'s motion scrubbing method is available.

Used to manually code eye gaze data from digital video files.

# مكتبة أبجد تحتوى على كتب، ومخطوطات نادرة جدا. بلتعاون مع منتدي الملوك السبعة للروحانيات حقوق النشر© هذا المُصنَّف مرخص بموجب رخصة المشاع الإبداعي نَسب المُصنّف - منع الاشتقاق 4.0 دولي. E-Mail : aba.elwaled@gmail.com Phone : +201030070676 https://elmlok-7.yoo7.com ___________ https://www.facebook.com/Abjjaad ___________ https://www.facebook.com/AabjAad ___________ https://elmlok7yoo7com.wordpress.com ___________ https://www.reddit.com/user/ro7ane ___________ https://elml0k.blogspot.com ___________ https://ro7ane.tumblr.com ___________ https://twitter.com/ro7ane1 ___________ https://www.instagram.com/abjad.science ___________ https://www.pinterest.com/Abjad66/_saved ___________ https://www.facebook.com/groups/549252415819771/ ___________ https://www.linkedin.com/in/abjad-science-513159194 ___________ https://www.youtube.com/channel/UCR9T7Fw83ovaf7sgPjgVEMg

Global Consciousness Project uses hardware "random" number generators and finds patterns between that and major world events. This Java applet will run on their webpage and translate that data to music-like audio. Or for general audio synthesizing.

Program to help with the procedure called theWork of ByronKatie. It is not standalone executable on windows or osx. It will require the installation of python, wxPython, and pygame, all free. Links on the website.

ELIA(Eyegaze Language Integration Analysis) supports the analysis of eye-tracking data for studies in language processing. ELIA eases early analysis of data to enable iterative development of experiments in response to spoken language.

The Model Zoo of Cognitive Diagnosis Models, including classic Item Response Ranking (IRT), Multidimensional Item Response Ranking (MIRT), Deterministic Input, Noisy "And" model(DINA), and advanced Fuzzy Cognitive Diagnosis Framework (FuzzyCDF), Neural Cognitive Diagnosis Model (NCDM), Item Response Ranking framework (IRR), Incremental Cognitive Diagnosis (ICD) and Knowledge-association baesd extension of NeuralCD (KaNCD). Cognitive diagnosis model (CDM) for intelligent educational systems is a type of model that infers students' knowledge states from their learning behaviors (especially exercise response logs). Typically, the input of a CDM could be the students' response logs of items (i.e., exercises/questions), the Q-matrix that denotes the correlation between items and knowledge concepts (skills). The output is the diagnosed student knowledge states, such as students' abilities and students' proficiencies on each knowledge concepts.

Datasets in Education and convenient interface for downloading and preprocessing dataset in education. The CLI tools to quickly convert the "raw" data of the dataset into "mature" data for knowledge tracing task. The "mature" data is in json sequence format and can be modeled by XKT and TKT(TBA) The analysis dataset tool only supports the json sequence format. To check the following statical indexes of the dataset. In order to better verify the effectiveness of the model, the dataset is usually divided into train/valid/test or using kfold method. Each item in the sequence represents one interaction. The first element of the item is the exercise id (in some works, the exercise id is not one-to-one mapped to one knowledge unit(ku)/concept, but in junyi, one exercise contains one ku) and the second one indicates whether the learner correctly answers the exercise, 0 for wrongly while 1 for correctly.

FreeBrain will be an application for the analysis of 2D neurophysiological signals, like heart-rate, EEG or eyemovements. It is aimed at those who want intuitive or free software and those who want a customizeble tool that can handle mixed datasets.

GameWeb is a web-based platform for experimental games research. GameWeb allows users to track mouse movements, create, adjust, pause and monitor games from a web interface. Based upon Apache, MySQL, and PHP projects.

HabraCharts is an open source project collecting information from habrahabr.ru

A tool for gathering usability feedback from web users in a low-impact manner.

J-Astro is a utility for astrological calculations. Beeing developed under linux, binaries are available for Linux, Mac OSX and for Win (XP / Win7). The user interface is built using the Qt4 libraries.

The aim of the JQuizAPI project is to define a simple API to construct test that may be used in diferent areas: - Surveys - Psychometric tests - Polls

For the purpose of policy simulation in coupled social-ecological systems (e.g. energy supply), a credible modelling of actors – especially citizens – and their decision processes is needed. This requires a framework capable of handling high numbers of heterogeneous agents (several hundreds of thousands). LARA (Lightweight Architecture for boundedly Rational Agents) meets these requirements and fills the gap between frameworks without built-in psychological foundations and full-fledged cognitive architectures which are both not viable options in this context. LARA provides prefabricated components of an agent’s decision process like perception, memory, and different modes of decision making. These components are psychologically plausible, i.e. based on appropriate psychological results and theories. Moreover, interfaces for basic learning and social influence are available.

NeuroKiwi is the application of the Associative Model (AM, previously dubbed AMDroid), being a model storing relational change-detections. The application tries to emulate ground-up knowledge accumulation with limited or no prior knowledge of shapes or patterns.