Supplemental Material for Belief Bias Is Response Bias: Evidence From a Two-Step Signal Detection Model

2018 ◽  
Keyword(s):  
Signal Detection ◽  
Response Bias ◽  
Belief Bias ◽  
Detection Model

Assessing Children's Racial Attitudes via a Signal Detection Model

1973 ◽  
Vol 36 (2) ◽  
pp. 587-598 ◽  
Author(s):  
Kathryn H. Williams ◽  
John E. Williams ◽  
Robert C. Beck
Keyword(s):  
Preschool Children ◽  
Signal Detection ◽  
Response Bias ◽  
Skin Color ◽  
Absolute Judgment ◽  
Positive Signal ◽  
Detection Model ◽  
Negative Adjective ◽  
Response Biases ◽  
Negative Signal

Previous research indicated that, in relative choice situations, both Caucasian and Negro preschool children tend to associate positive evaluative adjectives with light-skinned human figures and negative evaluative adjectives with dark-skinned ones. The present study utilized a signal-detection model with figures presented singly so that response bias, as well as sensitivity to the color-signal, could be evaluated. 30 Caucasian and 30 Negro preschool children were given 48 trials on which either a dark-skinned or light-skinned figure was accompanied by a story containing a positive or a negative adjective and were asked if the story described the figure. Dark-skinned figures carried a negative “signal” for Ss of both races. While the light-skinned figure carried a positive signal for the Caucasian Ss, the evidence for Negro Ss was unclear. The data also showed strong acquiescent (“yea-saying”) response biases, i.e., the children tended to respond “yes” much more frequently than “no,” regardless of the type of adjective employed or the skin-color of the presented figure. It was concluded that the basic phenomena previously shown with the relative choice methodology can also be shown with the absolute judgment methodology of the signal-detection model.

Recognition Memory for Self-Relevant Personality-Trait Words

2009 ◽  
Vol 68 (3) ◽  
pp. 133-142 ◽  
Author(s):  
Marek Nieznański
Keyword(s):  
Recognition Memory ◽  
Signal Detection ◽  
Response Bias ◽  
Personality Trait ◽  
Recognition Task ◽  
The Self ◽  
Rating Task ◽  
Detection Model ◽  
Self Study ◽  
Trait Words

Two studies based on a signal detection model of recognition memory are presented. Both studies investigated detection and response bias in the recognition of personality-trait words with respect to their relation to the self. Study 1 employed a yes-no task in which participants were to recognize trait adjectives. Study 2 employed a rating task in which participants declared their confidence with respect to whether a noun or an adjective had been presented. After the recognition task, participants selected personality-trait words that described them and ones that described other people. The results indicated a stronger tendency to say “old” for self-descriptive than for non-self-descriptive adjectives and nouns. Study 2 suggested that self-descriptive nouns are better detected than non-self-descriptive nouns.

Associations between collectivism and perception of social threat: a signal detection approach

2019 ◽  
Author(s):  
Tuong-Van Vu ◽  
Catrin Finkenauer ◽  
Lydia Krabbendam
Keyword(s):  
Signal Detection ◽  
Response Bias ◽  
Social Adjustment ◽  
Emotional Expressions ◽  
Social Threat ◽  
Threat Detection ◽  
Perceptual Sensitivity ◽  
Detection Approach ◽  
Self Construal ◽  
The Individual

Collectivistic orientation, which entails interdependent self-construal and concern for interpersonal harmony and social adjustment, has been suggested to be associated with detecting emotional expressions that signal social threat than individualistic orientation, which entails independent self-construal. The present research tested if this detection is a result of enhanced perceptual sensitivity or of response bias. We used country as proxy of individualism and collectivism (Country IC), measured IC of individuals with a questionnaire (Individual IC) and manipulated IC with culture priming (Situational IC). Dutch participants in the Netherlands (n = 143) and Chinese participants in China (n = 151) performed a social threat detection task where they had to categorize ambiguous facial expressions as “angry” or “not angry”. As the stimuli varied in degrees of scowling and frequency of presentation, we were able to measure the participants' perceptual sensitivity and response bias following the principles of the Signal Detection Theory. On the Country IC level, the results indicated that individualism-representative Dutch participants had higher perceptual sensitivity than collectivism-representative Chinese participants; whereas, Chinese participants were more biased towards categorizing a scowling face as “angry” than the Dutch (i.e. stronger liberal bias). In both groups, collectivism on the Individual IC was associated with a bias towards recognizing a scowling face as “not angry” (i.e. stronger conservative bias). Culture priming (Situational IC) affected neither perceptual sensitivity nor response bias. Our data suggested that cultural differences were in the form of behavioral tendency and IC entails multiple constructs linked to different outcomes in social threat detection.

scholarly journals Hazard Perception in City and Highway Environments

2019 ◽  
Vol 63 (1) ◽  
pp. 1404-1408
Author(s):  
John Paul Plummer ◽  
Anastasia Diamond ◽  
Alex Chaparro ◽  
Rui Ni
Keyword(s):  
Signal Detection ◽  
Response Bias ◽  
Signal Detection Theory ◽  
Response Criterion ◽  
Crash Risk ◽  
Hazard Perception ◽  
Driving Experience ◽  
City Environment ◽  
Video Clips ◽  
The City

Hazard perception (HP) is an important aspect of driving performance and is associated with crash risk. In the current study, we investigate the effect of roadway environment (city vs. highway) and expertise on HP. HP was measured using HP clips that evaluated response lag (defined as the time from the participant’s response to the end of the clip) and fuzzy signal detection theory metrics of response criterion and sensitivity. Forty videos were used: 20 from highway environments and 20 from city environments. Forty-eight participants with a range of driving experience as assessed by the years since obtaining a license (less than 1 year to 24 years) completed the study. There were differences between city and highway environments in response lag and response bias; participants responded earlier to the hazards in the highway environment and exhibited a more liberal response bias. Driving experience was significantly correlated to response lag. When the video clips were categorized by environment, driving experience was only significantly correlated with performance for the city environment.

Phantom ROC: Recollection rejection in a hybrid conjoint recognition signal detection model

Memory ◽  
2006 ◽  
Vol 14 (6) ◽  
pp. 655-671 ◽  
Author(s):  
James Michael Lampinen ◽  
Kristina N. Watkins ◽  
Timothy N. Odegard
Keyword(s):  
Signal Detection ◽  
Detection Model ◽  
Recollection Rejection

The Four-States Model of Memory Retrieval Experiences

2007 ◽  
Vol 215 (1) ◽  
pp. 61-71 ◽  
Author(s):  
Edgar Erdfelder ◽  
Lutz Cüpper ◽  
Tina-Sarah Auer ◽  
Monika Undorf
Keyword(s):  
Signal Detection ◽  
Memory Retrieval ◽  
Measurement Model ◽  
Standard Errors ◽  
Parameter Estimates ◽  
Unequal Variances ◽  
One Dimensional ◽  
Detection Model ◽  
Memory States ◽  
The One

Abstract. A memory measurement model is presented that accounts for judgments of remembering, knowing, and guessing in old-new recognition tasks by assuming four disjoint latent memory states: recollection, familiarity, uncertainty, and rejection. This four-states model can be applied to both Tulving's (1985) remember-know procedure (RK version) and Gardiner and coworker's ( Gardiner, Java, & Richardson-Klavehn, 1996 ; Gardiner, Richardson-Klavehn, & Ramponi, 1997 ) remember-know-guess procedure (RKG version). It is shown that the RK version of the model fits remember-know data approximately as well as the one-dimensional signal detection model does. In contrast, the RKG version of the four-states model outperforms the corresponding detection model even if unequal variances for old and new items are allowed for.We show empirically that the two versions of the four-statesmodelmeasure the same state probabilities. However, the RKG version, requiring remember-know-guess judgments, provides parameter estimates with smaller standard errors and is therefore recommended for routine use.

Effects of Social Influence in a Recognition Task of Auditory Intensity: A Temporary Shift in Criterion

1976 ◽  
Vol 42 (1) ◽  
pp. 75-85 ◽  
Author(s):  
Michael D. Biderman ◽  
William D. McBrayer ◽  
Mary La Montagne
Keyword(s):  
Social Influence ◽  
Signal Detection ◽  
Principal Components ◽  
Recognition Task ◽  
Discriminative Ability ◽  
Auditory Intensity ◽  
Detection Model ◽  
Social Sensitivity ◽  
The Social ◽  
Orthogonal Components

The effects of responses of another person or a computer occurring prior to the subjects' responses in tasks of recognition of auditory intensity were interpreted in terms of a signal-detection model which assumed that subjects shifted their decision criteria temporarily on each trial. A parameter representing the amount of criterion shift reliably estimated sensitivity to social influence. When the social sensitivity parameter was estimated from the data, discriminative ability, defined as d', was unaffected by the presence of social influence. Principal components analyses suggested that social sensitivity and discriminative ability represented essentially orthogonal components of subjects' decision behavior.

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