2013
DOI: 10.3758/s13423-013-0404-5
|View full text |Cite
|
Sign up to set email alerts
|

Mental chronometry and individual differences: Modeling reliabilities and correlations of reaction time means and effect sizes

Abstract: We used a general stage-based model of reaction time (RT) to investigate the psychometric properties of mean RTs and experimental effect sizes (i.e., differences in mean RTs). Using the model, formulas were derived for the reliabilities of mean RTs and RT difference scores, and these formulas provide guidance about the number of trials per participant needed to obtain reliable estimates of these measures. In addition, formulas were derived for various different types of correlations computed in RT research (e.… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
3
1
1

Citation Types

5
163
1

Year Published

2015
2015
2022
2022

Publication Types

Select...
6
2
1

Relationship

0
9

Authors

Journals

citations
Cited by 127 publications
(169 citation statements)
references
References 136 publications
5
163
1
Order By: Relevance
“…This is consistent with other research; For example, a study found that the performance variability measures in the d2 attention test should be interpreted with caution as they lack reliability [16]. Another study demonstrated (by means of simulation analysis on grounds of classical test theory) that measures of performance variability can never achieve the same degree of reliability as compared to measures of central tendency (i.e., mean scores) [42]. …”
Section: Discussionsupporting
confidence: 88%
“…This is consistent with other research; For example, a study found that the performance variability measures in the d2 attention test should be interpreted with caution as they lack reliability [16]. Another study demonstrated (by means of simulation analysis on grounds of classical test theory) that measures of performance variability can never achieve the same degree of reliability as compared to measures of central tendency (i.e., mean scores) [42]. …”
Section: Discussionsupporting
confidence: 88%
“…Importantly, however, whereas some recommendations and intuition imply that high correlations should emerge between two tasks that are mediated by the same mechanism (i.e., Carlson & Herdman, 2012), there exist considerable pitfalls in interpreting correlations between RT difference effects. For instance, many other and task-unspecific factors can influence participants' performance, thus difference time parameters are additionally constrained (Miller & Ulrich, 2013).…”
Section: Discussionmentioning
confidence: 99%
“…For example, correlations between difference scores may diminish due to task-unspecific variation and for relatively smaller effect sizes (Miller & Ulrich, 2013), which we cannot exclude for the current data sets. At its essence, these constraints indicate that a lack of correlation can also be observed if two processes have a common construct.…”
Section: Limitations Of the Individual-differences Approach For The Smentioning
confidence: 99%
“…This limitation was the result of the broad range of measures we employed, which led to time constraints in testing to avoid participant fatigue. Moreover, there are inherent difficulties involved in measuring individual difficulties within a factorial design, particularly one that involve measures of speed (Hedge, Powell, & Sumner, 2017;Miller & Ulrich, 2013). Further research using a stronger battery of measures is therefore required to test our prediction of a relationship between inhibitory control and lexical planning in healthy aging.…”
Section: Discussionmentioning
confidence: 99%