scholarly journals Motor selection bias in a no-target, response choice version of the attentional cueing paradigm

2010 ◽  
Vol 7 (9) ◽  
pp. 653-653
Author(s):  
D. Wilson ◽  
J. Pratt
Keyword(s):  
Selection Bias ◽  
Target Response ◽  
Response Choice ◽  
Attentional Cueing

Prime Proportion Affects Masked Priming of Fixed and Free-Choice Responses

2010 ◽  
Vol 57 (5) ◽  
pp. 360-366 ◽  
Author(s):  
Glen E. Bodner ◽  
Rehman Mulji
Keyword(s):  
Decision Process ◽  
Free Choice ◽  
Masked Priming ◽  
Local Context ◽  
Previous Trial ◽  
Target Response ◽  
Global Context ◽  
Sequential Trial

Left/right “fixed” responses to arrow targets are influenced by whether a masked arrow prime is congruent or incongruent with the required target response. Left/right “free-choice” responses on trials with ambiguous targets that are mixed among fixed trials are also influenced by masked arrow primes. We show that the magnitude of masked priming of both fixed and free-choice responses is greater when the proportion of fixed trials with congruent primes is .8 rather than .2. Unconscious manipulation of context can thus influence both fixed and free choices. Sequential trial analyses revealed that these effects of the overall prime context on fixed and free-choice priming can be modulated by the local context (i.e., the nature of the previous trial). Our results support accounts of masked priming that posit a memory-recruitment, activation, or decision process that is sensitive to aspects of both the local and global context.

Perceptual Learning Via Attentional Cueing

2011 ◽  
Author(s):  
Michael C. Mozer ◽  
Harold Pashler ◽  
Jason Jones ◽  
Robert Lindsey
Keyword(s):  
Perceptual Learning ◽  
Attentional Cueing

In Reply to ‘No Obvious Impact of NSAIDs on Risk of Kidney Failure: Causal or Another Selection Bias’

2020 ◽  
Vol 76 (5) ◽  
pp. 742-743 ◽  
Author(s):  
Min Zhan ◽  
Rebecca M. Doerfler ◽  
Jeffrey C. Fink
Keyword(s):  
Selection Bias ◽  
Kidney Failure

Correction: “Influence of Selection Bias on the Test Decision – A Simulation Study”

2014 ◽  
Vol 53 (05) ◽  
pp. 343-343
Keyword(s):  
Selection Bias ◽  
Simulation Study ◽  
Error Rate ◽  
Type I Error ◽  
Block Size ◽  
Error Rates ◽  
Type I ◽  
Type I Error Rate ◽  
Representation Error ◽  
Numeric Representation

We have to report marginal changes in the empirical type I error rates for the cut-offs 2/3 and 4/7 of Table 4, Table 5 and Table 6 of the paper “Influence of Selection Bias on the Test Decision – A Simulation Study” by M. Tamm, E. Cramer, L. N. Kennes, N. Heussen (Methods Inf Med 2012; 51: 138 –143). In a small number of cases the kind of representation of numeric values in SAS has resulted in wrong categorization due to a numeric representation error of differences. We corrected the simulation by using the round function of SAS in the calculation process with the same seeds as before. For Table 4 the value for the cut-off 2/3 changes from 0.180323 to 0.153494. For Table 5 the value for the cut-off 4/7 changes from 0.144729 to 0.139626 and the value for the cut-off 2/3 changes from 0.114885 to 0.101773. For Table 6 the value for the cut-off 4/7 changes from 0.125528 to 0.122144 and the value for the cut-off 2/3 changes from 0.099488 to 0.090828. The sentence on p. 141 “E.g. for block size 4 and q = 2/3 the type I error rate is 18% (Table 4).” has to be replaced by “E.g. for block size 4 and q = 2/3 the type I error rate is 15.3% (Table 4).”. There were only minor changes smaller than 0.03. These changes do not affect the interpretation of the results or our recommendations.

Controlling for Variable Liquidity and Selection Bias in Indices of Private Asset Market Values

2002 ◽  
Author(s):  
Jeffrey D. Fisher ◽  
Dean H. Gatzlaff ◽  
David M. Geltner ◽  
Donald R. Haurin
Keyword(s):  
Selection Bias ◽  
Asset Market ◽  
Market Values
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