Modeling Within-Person Variance in Reaction Time Data of Older Adults

GeroPsych ◽  
2011 ◽  
Vol 24 (4) ◽  
pp. 169-176 ◽  
Author(s):  
Philippe Rast ◽  
Daniel Zimprich
Keyword(s):  
Reaction Time ◽  
Cognitive Aging ◽  
Reaction Times ◽  
Reaction Time Task ◽  
Reaction Time Data ◽  
Scale Model ◽  
Time Data ◽  
Time Task ◽  
The Mean ◽  
Second Wave

In order to model within-person (WP) variance in a reaction time task, we applied a mixed location scale model using 335 participants from the second wave of the Zurich Longitudinal Study on Cognitive Aging. The age of the respondents and the performance in another reaction time task were used to explain individual differences in the WP variance. To account for larger variances due to slower reaction times, we also used the average of the predicted individual reaction time (RT) as a predictor for the WP variability. Here, the WP variability was a function of the mean. At the same time, older participants were more variable and those with better performance in another RT task were more consistent in their responses.

Reaction times and burning rates for wind tunnel headfires

2003 ◽  
Vol 12 (2) ◽  
pp. 195 ◽  
Author(s):  
Ralph M. Nelson, Jr.
Keyword(s):  
Reaction Time ◽  
Wind Tunnel ◽  
Wildland Fire ◽  
Mass Loss Rate ◽  
Fire Behavior ◽  
Reaction Times ◽  
Reaction Time Data ◽  
Combustion Regime ◽  
Fuel Particle ◽  
Time Data

Catchpole et al. (1998) reported rates of spread for 357 heading and no-wind fires burned in the wind tunnel facility of the USDA Forest Service's Fire Sciences Laboratory in Missoula, Montana for the purpose of developing models of wildland fire behavior. The fires were burned in horizontal fuel beds with differing characteristics due to various combinations of fuel type, particle size, packing ratio, bed depth, moisture content, and wind speed. In the present paper, fuel particle and fuel bed data for 260 heading fires from that study (plus as-yet unreported combustion efficiency and reaction time data) are used to develop models for predicting fuel bed reaction time and mass loss rate. Reaction time is computed from the flameout time of a single particle and fuel bed structural properties. It is assumed that the beds burn in a combustion regime controlled by the rate at which air mixes with volatiles produced during pyrolysis, and that not all air entering the fuel bed reaction zone participates in combustion. Comparison of reaction time and burning rate predictions with experimental values is encouraging in view of the simplified modeling approach and uncertainties associated with the experimental measurements.

Reaction Speed as a Function of Stimulus Intensity in Normals and Retardates

1965 ◽  
Vol 20 (2) ◽  
pp. 649-652 ◽  
Author(s):  
Alfred A. Baumeister ◽  
William F. Hawkins ◽  
George Kellas
Keyword(s):  
Reaction Time ◽  
Stimulus Intensity ◽  
Reaction Times ◽  
Reaction Time Task ◽  
Time Task ◽  
Motor Set ◽  
Reaction Speed

The reaction times of retardates and normals were compared as a function of intensity of the reaction signal. Three intensity levels of a 1000-cycle tone were used: 5, 15, and 25 db above threshold. Each S was presented all tones in a completely counterbalanced order. The results revealed that both intelligence groups reacted faster with each increase in intensity of the signal. Since no significant interactions emerged, it cannot be concluded that the groups benefited differentially from increases in intensity of reaction signal. It is suggested that retardates may have a sensory set whereas normals have a motor set in the reaction time task.

Relation between Reaction Time and Loudness

1984 ◽  
Vol 27 (2) ◽  
pp. 306-310 ◽  
Author(s):  
Larry E. Humes ◽  
Jayne B. Ahlstrom
Keyword(s):  
Young Adults ◽  
Reaction Time ◽  
Reaction Times ◽  
Growth Function ◽  
Reaction Time Data ◽  
Intensity Function ◽  
Sound Level ◽  
Time Data ◽  
Sound Levels ◽  
Loudness Growth

The loudness of one-third octave bands of noise centered at either 1, 2, or 4 kHz was measured in 10 normal-hearing young adults for sound levels of 50–90 dB SPL. Reaction times (RT) in response to these same stimuli were also measured in the same subjects. A moderate-to-strong correspondence was observed between the slopes for functions depicting the growth of loudness with sound level and comparable slopes for the reaction-time data. The correlation between slopes for the RT-intensity function and the loudness-growth function was comparable in magnitude to the test,retest correlation for the loudness-growth function except at 1 kHz.

Effects of Uncertainties of Time and Occurrence on Reaction Time of Mentally Handicapped Students

1981 ◽  
Vol 53 (2) ◽  
pp. 355-360 ◽  
Author(s):  
Paul R. Surburg
Keyword(s):  
Reaction Time ◽  
Reaction Times ◽  
Reaction Time Task ◽  
Mentally Handicapped ◽  
Treatment Groups ◽  
Time Task

The purpose of this study was to determine the effects of uncertainties of time and occurrence on reaction time of mildly handicapped students. 33 students were randomly assigned to the following treatment groups: no catch-trials, 10% catch-trials, and 20% catch-trials. Randomly varied foreperiods of 1.5, 3.0, and 4.5 sec. were used in a reaction time task. The role of catch-trials varied over four days of testing. Reaction times following 3.0- and 4.5-sec. were significantly faster than measurements following a 1.5-sec. foreperiod.

Cardiac Cycle Phase and Movement and Reaction Times

1976 ◽  
Vol 42 (3) ◽  
pp. 767-770 ◽  
Author(s):  
Matti J. Saari ◽  
Bruce A. Pappas
Keyword(s):  
Reaction Time ◽  
Cardiac Cycle ◽  
Visual Stimuli ◽  
Reaction Times ◽  
Reaction Time Task ◽  
Stimulus Presentation ◽  
Stimulus Onset ◽  
Cycle Phase ◽  
Second Phase ◽  
Time Task

The EKG was recorded while Ss differentially responded to auditory or visual stimuli in a reaction time task. The EKG record was analyzed by dividing each R-R interval encompassing a stimulus presentation into 9 equal phases. Reaction times were determined as a function of the phase encompassing stimulus onset while movement times were determined for the phase in which the response was initiated. Only reaction time significantly varied with cardiac cycle, with reactions during the second phase being slower than later phases.

Temporal Characteristics of Interstimulus Interval in Serial Choice Reaction Time,

1973 ◽  
Vol 37 (3) ◽  
pp. 723-726
Author(s):  
Robert P. Fishburne ◽  
Wayne L. Waag
Keyword(s):  
Reaction Time ◽  
Choice Reaction Time ◽  
Interstimulus Interval ◽  
Reaction Times ◽  
Reaction Time Task ◽  
Choice Reaction Time Task ◽  
Interval Duration ◽  
Random Interval ◽  
Temporal Characteristics ◽  
The Mean

The present study investigated the effects of presentation schedule and interstimulus interval duration in a serial choice reaction-time task. 45 Ss were randomly assigned to fixed, patterned, and random schedules having durations of interstimulus intervals of 2, 3, and 4 sec. As the regularity of the presentation schedule decreased, reaction time increased. For fixed-interval presentation, reaction time increased as a function of duration while the quickest reaction times occurred at the mean interstimulus interval for random-interval presentation. Reaction times remained the same under the patterned-interval presentation schedule.

Response to Simulated Traffic Signals Using Light-Emitting Diode and Incandescent Sources

2000 ◽  
Vol 1724 (1) ◽  
pp. 39-46 ◽  
Author(s):  
John D. Bullough ◽  
Peter R. Boyce ◽  
Andrew Bierman ◽  
Kathryn M. Conway ◽  
Kun Huang ◽  
...  
Keyword(s):  
Reaction Time ◽  
Light Emitting Diode ◽  
Reaction Times ◽  
Reaction Time Data ◽  
Traffic Signals ◽  
Time Data ◽  
Light Emitting ◽  
Color Identification ◽  
Mean Reaction Time

Simulated light-emitting diode (LED) traffic signals of different luminances were evaluated relative to incandescent signals of the same nominal color and at the luminances required by the specifications of the Institute of Transportation Engineers. Measurements were made of the reaction times to onset and the number of missed signals for red, yellow, and green incandescent and LED signals. Measurements also were made of subjects’ ability to correctly identify signal colors and of their subjective brightness and conspicuity ratings. All measurements were made under simulated daytime conditions. There were no significant differences in mean reaction time, percentage of missed signals, color identification, or subjective brightness and conspicuity ratings between simulated incandescent and LED signals of the same nominal color and luminance. Higher luminances were needed for the yellow and green signal colors to ensure that they produced the same reaction time, the same percentage of missed signals, and the same rated brightness and conspicuity as a red signal at a given luminance. Equations fitted to the reaction time data, the missed signals data, and the brightness and conspicuity ratings for the LED signals can be used to make quantitative predictions of the consequences of proposed changes in signal luminance for reaction time, brightness, and conspicuity.

A CRITICAL REVIEW OF RICHARD LYNN'S REPORTS ON REACTION TIME AND RACE

2010 ◽  
Vol 43 (1) ◽  
pp. 113-123 ◽  
Author(s):  
DREW M. THOMAS
Keyword(s):  
Reaction Time ◽  
Racial Differences ◽  
Critical Review ◽  
Reaction Times ◽  
Reaction Time Data ◽  
Decision Time ◽  
General Intelligence ◽  
Time Data ◽  
The World ◽  
Decision Times

SummaryIn the early 1990s, psychologist Richard Lynn published papers documenting average reaction times and decision times in samples of nine-year-olds taken from across the world. After summarizing these data, Lynn interpreted his results as evidence of national and racial differences in decision time and general intelligence. Others have also interpreted Lynn's data as evidence of racial differences in decision time and intelligence. However, comparing Lynn's summaries with his original reports shows that Lynn misreported and omitted some of his own data. Once these errors are fixed the rankings of nations in Lynn's datasets are unstable across different decision time measures. This instability, as well as within-race heterogeneity and between-race overlap in decision times, implies that Lynn's reaction time data do not permit generalizations about the decision times and intelligence of people of different races.

scholarly journals Human Reaction Times: Linking Individual and Collective Behaviour Through Physics Modeling

Symmetry ◽  
2021 ◽  
Vol 13 (3) ◽  
pp. 451
Author(s):  
Juan Carlos Castro-Palacio ◽  
Pedro Fernández-de-Córdoba ◽  
J. M. Isidro ◽  
Sarira Sahu ◽  
Esperanza Navarro-Pardo
Keyword(s):  
Reaction Time ◽  
Gaussian Function ◽  
Visual Stimuli ◽  
Reaction Times ◽  
Cognitive Disorders ◽  
Reaction Time Data ◽  
Ideal Gas ◽  
Time Data ◽  
Physics Modeling ◽  
The Individual

An individual’s reaction time data to visual stimuli have usually been represented in Experimental Psychology by means of an ex-Gaussian function. In most previous works, researchers have mainly aimed at finding a meaning for the parameters of the ex-Gaussian function which are known to correlate with cognitive disorders. Based on the recent evidence of correlations between the reaction time series to visual stimuli produced by different individuals within a group, we go beyond and propose a Physics-inspired model to represent the reaction time data of a coetaneous group of individuals. In doing so, a Maxwell–Boltzmann-like distribution appeared, the same distribution as for the velocities of the molecules in an Ideal Gas model. We describe step by step the methodology we use to go from the individual reaction times to the distribution of the individuals response within the coetaneous group. In practical terms, by means of this model we also provide a simple entropy-based methodology for the classification of the individuals within the collective they belong to with no need for an external reference which can be applicable in diverse areas of social sciences.

scholarly journals No Myth far and wide:

2018 ◽  
Vol 2 ◽  
Author(s):  
Joachim Hüffmeier ◽  
Stefan Krumm
Keyword(s):  
Reaction Time ◽  
Reaction Times ◽  
Reaction Time Data ◽  
Stopping Rule ◽  
Time Estimate ◽  
Time Data ◽  
Methodological Choices ◽  
Time Correction ◽  
The Individual ◽  
High Chance

Skorski, Extebarria, and Thompson (2016) aim at our article on relay swimmers (Hüffmeier, Krumm, Kanthak, & Hertel, 2012). We have shown that professional freestyle swimmers at relay positions 2 to 4 swam faster in the relay than in the individual competition if they had a high chance to win a relay medal. After applying a reaction-time correction that controls for different starting procedures in relay and individual competitions, Skorski et al. (2016) conclude that swimmers in relays do not swim faster. At first sight, their results appear to show this very pattern. However, we argue that the authors’ findings and conclusion—that our finding is a myth—are not warranted. First, we have also controlled for quicker reaction times in the relay competition. Our correction has been based on the swimmers’ own reaction time data rather than on a constant reaction time estimate and is, thus, more precise than theirs. Second, Skorski et al. treat data from international and national competitions equally although national relay competitions are less attractive for the swimmers than national individual competitions. This difference likely biases their data towards slower relay times. Third, the authors select a small and arbitrary sample without explicit power considerations or a clear stopping rule. Fourth, they unfavorably aggregate their data. We conclude that the reported results are most likely due to the methodological choices by Skorski et al. and do not invalidate our findings.

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