A Susan M Niessen
Biographic Data
| ID | 6540545 |
|---|---|
| NAME | A Susan M Niessen |
| GIVEN NAMES | A Susan M |
| FAMILY NAME | Niessen |
| SIGNATURE | NIESSEN A S M |
| AFFILIATIONS | University of Groningen |
| ORCID | 0000-0001-8249-9295 |
| VERIFIED | Yes |
| TOTAL WORKS | 3 |
| TOTAL CITATIONS | 0 |
| AUTHOR COUNT | 3 |
| EDITOR COUNT | 0 |
| FIRST PUBLICATION YEAR | 2016 |
| LATEST PUBLICATION YEAR | 2023 |
| H-INDEX | 0 |
Predicting decision-makers’ algorithm use
Decision makers typically integrate multiple pieces of information to make predictions and decisions. They also sometimes receive algorithmic advice, but often discount such advice. This usually results in less consistent and less accurate predictions than consistently using the advice. We hypothesized that individual differences on psychological traits such as dutifulness (a facet of conscientiousness), decision-making styles, and predictor vali…
The autonomy‐validity dilemma in mechanical prediction procedures: The quest for a compromise
A robust finding in psychological research is that combining information with a mechanical rule results in more valid predictions than combining information holistically in the mind. Nevertheless, information is typically combined holistically in practice, resulting in suboptimal predictions and decisions. Earlier research showed that decision makers are more likely to use mechanical prediction procedures when they retain autonomy in the decision…
Detecting careless respondents in web-based questionnaires: Which method to use
High data quality is an important prerequisite for sound empirical research. Meade and Craig (2012) and Huang, Curran, Keeney, Poposki, and DeShon (2012) discussed methods to detect unmotivated or careless respondents in large web-based questionnaires. We first discuss these methods and present multi-test extensions of person-fit statistics as alternatives. Second, we applied these methods to data collected through a web-based questionnaire, in w…
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Detecting careless respondents in web-based questionnaires: Which method to use
High data quality is an important prerequisite for sound empirical research. Meade and Craig (2012) and Huang, Curran, Keeney, Poposki, and DeShon (2012) discussed methods to detect unmotivated or careless respondents in large web-based questionnaires. We first discuss these methods and present multi-test extensions of person-fit statistics as alternatives. Second, we applied these methods to data collected through a web-based questionnaire, in w…
The autonomy‐validity dilemma in mechanical prediction procedures: The quest for a compromise
A robust finding in psychological research is that combining information with a mechanical rule results in more valid predictions than combining information holistically in the mind. Nevertheless, information is typically combined holistically in practice, resulting in suboptimal predictions and decisions. Earlier research showed that decision makers are more likely to use mechanical prediction procedures when they retain autonomy in the decision…
Predicting decision-makers’ algorithm use
Decision makers typically integrate multiple pieces of information to make predictions and decisions. They also sometimes receive algorithmic advice, but often discount such advice. This usually results in less consistent and less accurate predictions than consistently using the advice. We hypothesized that individual differences on psychological traits such as dutifulness (a facet of conscientiousness), decision-making styles, and predictor vali…
Computer Science (3 works) · Psychology (3 works) · Applied Psychology (2 works) · Clinical Psychology (2 works) · Construct validity (2 works) · Decision-Making and Behavioral Economics (2 works) · Incremental validity (2 works) · Mathematics (2 works) · Predictive validity (2 works) · Psychometrics (2 works)