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UID:pretalx-sips2025-budapest-BPX3XQ@pretalx.com
DTSTART;TZID=CET:20250626T102200
DTEND;TZID=CET:20250626T103000
DESCRIPTION:We investigated the Picture-Word Interference Effect by paramet
 rically manipulating semantic similarity while controlling for lexical ass
 ociation and orthographic/phonological similarity. We also aimed to contro
 l for lexical-semantic variables at both the picture and word levels\, pic
 ture-specific visual properties\, and stimulus-independent confounders. Ho
 wever\, collinearity is a major challenge in psycholinguistics as linguist
 ic variables are highly interrelated. Additionally\, with predictors for b
 oth pictures and words (e.g.\, word frequency for the picture name versus 
 the distractor word)\, it becomes unclear which are more critical for perf
 ormance modulation\, complicating predictor selection. This affects model 
 building\, interpretability\, and robustness. We seek guidance on detectin
 g and mitigating collinearity while ensuring theoretically relevant contro
 ls. Should we use dimensionality reduction\, residualization\, or penalize
 d regression? Furthermore\, we welcome insights on structuring mixed-effec
 ts models to balance complexity and convergence. Feedback from experts in 
 statistical modeling and psycholinguistics would be invaluable in refining
  our approach.
DTSTAMP:20260514T160310Z
LOCATION:Second floor 213
SUMMARY:LT29: Handling collinearity in Picture-Word Interference studies: B
 alancing theoretical relevance and model robustness - Irene Di Pietro
URL:https://pretalx.com/sips2025-budapest/talk/BPX3XQ/
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