scholarly journals Genetic and environmental components of the individual differences in response time distribution

2019 ◽  
Author(s):  
Liya Merzon ◽  
Ivan Voronin
Keyword(s):  
Individual Differences ◽  
Response Time ◽  
Time Distribution ◽  
Response Time Distribution ◽  
The Individual

Type-based associations in grapheme-color synaesthesia revealed by response time distribution analyses

2011 ◽  
Vol 20 (4) ◽  
pp. 1548-1557 ◽  
Author(s):  
Jun Saiki ◽  
Ayako Yoshioka ◽  
Hiroki Yamamoto
Keyword(s):  
Response Time ◽  
Time Distribution ◽  
Response Time Distribution

scholarly journals Response Time Distribution Analysis of Semantic and Response Interference in a Manual Response Stroop Task

2019 ◽  
Vol 66 (3) ◽  
pp. 231-238 ◽  
Author(s):  
Nabil Hasshim ◽  
Michelle Downes ◽  
Sarah Bate ◽  
Benjamin A. Parris
Keyword(s):  
Response Time ◽  
Stroop Task ◽  
Time Distribution ◽  
Response Times ◽  
Response Time Distribution ◽  
Stroop Interference ◽  
Response Conflict ◽  
Distribution Analysis ◽  
Manual Response ◽  
Response Interference

Abstract. Previous analyses of response time distributions have shown that the Stroop effect is observed in the mode (μ) and standard deviation (σ) of the normal part of the distribution, as well as its tail (τ). Specifically, interference related to semantic and response processes has been suggested to specifically affect the mode and tail, respectively. However, only one study in the literature has directly manipulated semantic interference, and none manipulating response interference. The present research aims to address this gap by manipulating both semantic and response interference in a manual response Stroop task, and examining how these components of Stroop interference affect the response time distribution. Ex-Gaussian analysis showed both semantic and response conflict to only affect τ. Analyzing the distribution by rank-ordered response times (Vincentizing) showed converging results as the magnitude of both semantic and response conflict increased with slower response times. Additionally, response conflict appeared earlier on the distribution compared to semantic conflict. These findings further highlight the difficulty in attributing specific psychological processes to different parameters (i.e., μ, σ, and τ). The effect of different response modalities on the makeup of Stroop interference is also discussed.

Grice-representability of response time distribution families

Psychometrika ◽  
1993 ◽  
Vol 58 (2) ◽  
pp. 281-314 ◽  
Author(s):  
Ehtibar N. Dzhafarov
Keyword(s):  
Response Time ◽  
Time Distribution ◽  
Response Time Distribution

scholarly journals Integrated response and transit time distributions of watersheds by combining hydrograph separation and long-term transit time modeling

2010 ◽  
Vol 14 (8) ◽  
pp. 1537-1549 ◽  
Author(s):  
M. C. Roa-García ◽  
M. Weiler
Keyword(s):  
Response Time ◽  
Transit Time ◽  
Time Distribution ◽  
Response Time Distribution ◽  
Hydrograph Separation ◽  
Response Distribution ◽  
Time Modeling ◽  
Realistic Description ◽  
Integrated Response

Abstract. We present a new modeling approach analyzing and predicting the Transit Time Distribution (TTD) and the Response Time Distribution (RTD) from hourly to annual time scales as two distinct hydrological processes. The model integrates Isotope Hydrograph Separation (IHS) and the Instantaneous Unit Hydrograph (IUH) approach as a tool to provide a more realistic description of transit and response time of water in catchments. Individual event simulations and parameterizations were combined with long-term baseflow simulation and parameterizations; this provides a comprehensive picture of the catchment response for a long time span for the hydraulic and isotopic processes. The proposed method was tested in three Andean headwater catchments to compare the effects of land use on hydrological response and solute transport. Results show that the characteristics of events and antecedent conditions have a significant influence on TTD and RTD, but in general the RTD of the grassland dominated catchment is concentrated in the shorter time spans and has a higher cumulative TTD, while the forest dominated catchment has a relatively higher response distribution and lower cumulative TTD. The catchment where wetlands concentrate shows a flashier response, but wetlands also appear to prolong transit time.

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