scholarly journals Analysis of speed-accuracy trade-offs using the Wiener diffusion model for choice reaction times

2021 ◽  
Author(s):  
Annalise Aleta LaPlume
Keyword(s):  
Response Time ◽  
Diffusion Model ◽  
Response Times ◽  
Reaction Times ◽  
Response Time Data ◽  
Choice Response ◽  
Time Data ◽  
Trade Offs ◽  
R Programming ◽  
Speed Accuracy

A methodology review paper on the utility and challenges of modelling speed-accuracy trade-offs in response time data. The paper reviews the importance of accounting for speed-accuracy trade-offs when measuring response times, and provides background on diffusion models for response time data. It then describes a practical software implementation of the EZ-diffusion model to model speed-accuracy trade-offs in choice response time data using the R programming language.

Measures of phonological typicality

2010 ◽  
Vol 5 (3) ◽  
pp. 281-299 ◽  
Author(s):  
Padraic Monaghan ◽  
Morten H. Christiansen ◽  
Thomas A. Farmer ◽  
Stanka A. Fitneva
Keyword(s):  
Lexical Decision ◽  
Response Time ◽  
Word Processing ◽  
Response Times ◽  
Parameter Variation ◽  
Response Time Data ◽  
Speech Sounds ◽  
Time Data ◽  
Monosyllabic Word ◽  
Lexical Categories

Phonological Typicality (PT) is a measure of the extent to which a word’s phonology is typical of other words in the lexical category to which it belongs. There is a general coherence among words from the same category in terms of speech sounds, and we have found that words that are phonologically typical of their category tend to be processed more quickly and accurately than words that are less typical. In this paper we describe in greater detail the operationalisation of measures of a word’s PT, and report validations of different parameterisations of the measure. For each variant of PT, we report the extent to which it reflects the coherence of the lexical categories of words in terms of their sound, as well as the extent to which the measure predicts naming and lexical decision response times from a database of monosyllabic word processing. We show that PT is robust to parameter variation, but that measures based on PT of uninflected words (lemmas) best predict response time data for naming and lexical decision of single words.

scholarly journals Sequential Sampling Models Without Random Between-Trial Variability: The Racing Diffusion Model of Speeded Decision

2017 ◽  
Author(s):  
Gabriel Tillman
Keyword(s):  
Response Time ◽  
Diffusion Model ◽  
Response Times ◽  
Sequential Sampling ◽  
Good Reason ◽  
Accumulation Process ◽  
Time Data ◽  
Evidence Accumulation ◽  
Sequential Sampling Models ◽  
Sequential Sampling Model

Most current sequential sampling models have random between-trial variability in their parameters. These sources of variability make the models more complex in order to fit response time data, do not provide any further explanation to how the data were generated, and have recently been criticised for allowing infinite flexibility in the models. To explore and test the need of between-trial variability parameters we develop a simple sequential sampling model of N-choice speeded decision making: the racing diffusion model. The model makes speeded decisions from a race of evidence accumulators that integrate information in a noisy fashion within a trial. The racing diffusion does not assume that any evidence accumulation process varies between trial, and so, the model provides alternative explanations of key response time phenomena, such as fast and slow error response times relative to correct response times. Overall, our paper gives good reason to rethink including between-trial variability parameters in sequential sampling models

Passenger Response Time Data-Sets for Large Passenger Ferries and Cruise Ships Derived from Sea Trials

2013 ◽  
Vol 155 (A1) ◽  
Keyword(s):  
Response Time ◽  
Response Times ◽  
Response Time Data ◽  
Data Sets ◽  
Time Data ◽  
Data Set ◽  
Analysis Methodology ◽  
Cruise Ships ◽  
Passenger Ships ◽  
Response Time Distributions

This paper describes research that was carried-out under the EU FP7 research project SAFEGUARD and presents passenger response time data generated from five full-scale semi-unannounced assembly trials at sea. The data-sets were generated from three different types of passenger ships, a RO-PAX ferry without cabins (RP1), a cruise ship (CS) and a RO-PAX ferry with cabins (RP2). In total, response times from 2366 people were collected making it the largest response time data-set ever collected – on land or sea. The analysis methodology used to extract the response time data and the resultant response time distributions (RTD) is presented. A number of key findings from the data analysis are presented along with three recommendations to modify the IMO guidelines governing ship evacuation analysis, namely; (a) it is inappropriate to use the same RTD for cruise ships and RO-PAX vessels; (b) a new Day Case RTD is suggested for RO-PAX vessels and (c) new Day and Night RTDs are suggested for cruise ships.

PASSENGER RESPONSE TIME DATA-SETS FOR LARGE PASSENGER FERRIES AND CRUISE SHIPS DERIVED FROM SEA TRIALS

2021 ◽  
Vol 155 (A1) ◽  
Author(s):  
R Brown ◽  
E R Galea ◽  
S Deere ◽  
L Filippidis
Keyword(s):  
Response Time ◽  
Response Times ◽  
Response Time Data ◽  
Data Sets ◽  
Time Data ◽  
Data Set ◽  
Analysis Methodology ◽  
Cruise Ships ◽  
Passenger Ships ◽  
Response Time Distributions

This paper describes research that was carried-out under the EU FP7 research project SAFEGUARD and presents passenger response time data generated from five full-scale semi-unannounced assembly trials at sea. The data-sets were generated from three different types of passenger ships, a RO-PAX ferry without cabins (RP1), a cruise ship (CS) and a RO-PAX ferry with cabins (RP2). In total, response times from 2366 people were collected making it the largest response time data-set ever collected – on land or sea. The analysis methodology used to extract the response time data and the resultant response time distributions (RTD) is presented. A number of key findings from the data analysis are presented along with three recommendations to modify the IMO guidelines governing ship evacuation analysis, namely; (a) it is inappropriate to use the same RTD for cruise ships and RO-PAX vessels; (b) a new Day Case RTD is suggested for RO-PAX vessels and (c) new Day and Night RTDs are suggested for cruise ships.

Using response time data to reduce testing time in cognitive tests.

2018 ◽  
Vol 30 (3) ◽  
pp. 328-338 ◽  
Author(s):  
Maria Bertling ◽  
Jonathan P. Weeks
Keyword(s):  
Response Time ◽  
Response Time Data ◽  
Testing Time ◽  
Cognitive Tests ◽  
Time Data

scholarly journals Qualitative speed-accuracy tradeoff effects can be explained by a diffusion/fast-guess mixture model

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Roger Ratcliff ◽  
Inhan Kang
Keyword(s):  
Mixture Model ◽  
Diffusion Model ◽  
Response Times ◽  
Model Fit ◽  
Orientation Discrimination ◽  
Model Parameters ◽  
Stimulus Contrast ◽  
Accuracy Stress ◽  
Speed Accuracy ◽  
Selective Influence

AbstractRafiei and Rahnev (2021) presented an analysis of an experiment in which they manipulated speed-accuracy stress and stimulus contrast in an orientation discrimination task. They argued that the standard diffusion model could not account for the patterns of data their experiment produced. However, their experiment encouraged and produced fast guesses in the higher speed-stress conditions. These fast guesses are responses with chance accuracy and response times (RTs) less than 300 ms. We developed a simple mixture model in which fast guesses were represented by a simple normal distribution with fixed mean and standard deviation and other responses by the standard diffusion process. The model fit the whole pattern of accuracy and RTs as a function of speed/accuracy stress and stimulus contrast, including the sometimes bimodal shapes of RT distributions. In the model, speed-accuracy stress affected some model parameters while stimulus contrast affected a different one showing selective influence. Rafiei and Rahnev’s failure to fit the diffusion model was the result of driving subjects to fast guess in their experiment.

scholarly journals Dose-Response-Time Data Analysis: An Underexploited Trinity

2018 ◽  
Vol 71 (1) ◽  
pp. 89-122 ◽  
Author(s):  
Johan Gabrielsson ◽  
Robert Andersson ◽  
Mats Jirstrand ◽  
Stephan Hjorth
Keyword(s):  
Data Analysis ◽  
Response Time ◽  
Dose Response ◽  
Response Time Data ◽  
Time Data
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