Invalid responding in questionnaire-based research: Implications for the study of schizotypy.
Bibliographic record
Abstract
Data collected through self-report questionnaires are particularly susceptible to inappropriate or random responding, and such invalid data increase noise and attenuate true statistical relationships. While many researchers studying schizotypy have employed infrequency measures to exclude participants, such measures are not universally employed. Moreover, some researchers have even outright questioned whether validity scales are warranted. Here, we show the effect of invalid responses on the relationship between schizotypy and hedonic reaction. For valid responders, negative schizotypal traits were inversely related to both anticipatory and consummatory pleasure (p < .01). Invalid responses were found for 23% of respondents, and within these subjects, no relationship was found between any of the measures. When the valid and invalid respondents were pooled, the relationship was dampened. Furthermore, linear multiple regression modeling showed that validity trended toward moderating the relationship between the variables of interest. These data highlight the importance of screening for, and excluding, invalid responses in schizotypy research. Our results also affirm that screening for random responding is effective and warranted. Implications for future studies employing questionnaire-based methods are discussed.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".