Debian Med Psychology packages

According to its authors, praat is "doing phonetics by computer". Through its graphical interface, several speech analysis functionalities are available: spectrograms, cochleograms, and pitch and formant extraction. Articulatory synthesis, as well as synthesis from pitch, formant, and intensity are also available. Other features are segmentation, labelling using the phonetic alphabet, and computation of statistics. Praat is configurable and extensible through its own scripting language and has provisions for communicating with other programs.

Psignifit дозволяє виконувати встановлення психометричних функцій для наборів даних, здійснюючи повний контроль над великою кількістю параметрів. Дані можуть бути отримані як з текстового файлу, так і за допомогою конвеєрів.

Psignifit виконує обчислення довірчих інтервалів, а також перевірку критерію відношення правдоподібності.

В цьому пакунку міститься версія для командного рядка.

PsychoPy provides an environment for creating psychology stimuli using Python scripting language. It combines the graphical strengths of OpenGL with easy Python syntax to give psychophysics a free and simple stimulus presentation and control package.

The goal is to provide, for the busy scientist, tools to control timing and windowing and a simple set of pre-packaged stimuli and methods. PsychoPy features

• IDE GUI for coding in a powerful scripting language (Python)
• Builder GUI for rapid development of stimulation sequences
• Use of hardware-accelerated graphics (OpenGL)
• Integration with Spectrascan PR650 for easy monitor calibration
• Simple routines for staircase and constant stimuli experimental methods as well as curve-fitting and bootstrapping
• Simple (or complex) GUIs via wxPython
• Easy interfaces to joysticks, mice, sound cards etc. via PyGame
• Video playback (MPG, DivX, AVI, QuickTime, etc.) as stimuli

PyEPL is a stimuli delivery and response registration toolkit to be used for generating psychology (as well as neuroscience, marketing research, and other) experiments.

It provides

• presentation: both visual and auditory stimuli
• responses registration: both manual (keyboard/joystick) and sound (microphone) time-stamped
• sync-pulsing: synchronizing your behavioral task with external acquisition hardware
• flexibility of encoding various experiments due to the use of Python as a description language
• fast execution of critical points due to the calls to linked compiled libraries

This toolbox is here to be an alternative for a widely used commercial product E'(E-Prime)

This package provides PyEPL for supported versions of Python.

Psignifit allows fitting of psychometric functions to datasets while maintaining full control over a large number of parameters. Psignifit performs the calculation of confidence intervals as well as goodness-of-fit tests. In addition it offers:

• full Bayesian treatment of psychometric functions including Bayesian model selection and goodness of fit assessment
• identification of influential observations and outlier detection
• flexible shape definition of the psychometric function

This package provides the Python bindings.

This package provides functions for reading and writing data stored by statistical packages such as Minitab, S, SAS, SPSS, Stata, ...

This package is part of the set of packages that are 'recommended' by R Core and shipped with upstream source releases of R itself.

This package includes several procedures used in psychometrics and scaling, including:

• Cohen's Kappa and weighted Kappa (two-rater agreement tests)
• Cronbach's Alpha (an item-reliability test)
• Focused Principal Components Analysis
• Intraclass correlation coefficients
• Light's Kappa (an N-rater agreement test)
• Screeplots and graphical representations of principal components

The Vision Egg is a programming library that uses standard, inexpensive computer graphics cards to produce visual stimuli for vision research experiments.

This metapackage will install Debian packages which might be useful for carrying out any experiment relating physical stimuli and their psychological effects.

The selection of packages is targeting software for stimuli delivery. For additional software related to the analysis of the acquired data refer to science-neuroscience-cognitive, med-imaging depending on the domain of application. Additionally look into science-bci since those often provide a complete loop frameworks including stimuli delivery.

Miscellaneous functions for psychometric problems

A number of routines for personality, psychometrics and experimental psychology. Functions are primarily for scale construction using factor analysis, cluster analysis and reliability analysis, although others provide basic descriptive statistics. Functions for simulating particular item and test structures are included. Several functions serve as a useful front end for structural equation modeling. Graphical displays of path diagrams, factor analysis and structural equation models are created using basic graphics. Some of the functions are written to support a book on psychometrics as well as publications in personality research. For more information, see the personality-project.org/r webpage.

Contains functions useful for correlation theory, meta-analysis (validity-generalization), reliability, item analysis, inter-rater reliability, and classical utility

Recursive partitioning based on psychometric models, employing the general MOB algorithm (from package party). Currently, only Bradley-Terry trees are implemented.

An assortment of functions that could be useful in analyzing data from pyschophysical experiments. It includes functions for calculating d' from several different experimental designs, links for m-alternative forced-choice (mafc) data to be used with the binomial family in glm (and possibly other contexts) and self-Start functions for estimating gamma values for CRT screen calibrations.