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UID:pretalx-sips2025-budapest-RBLHPR@pretalx.com
DTSTART;TZID=CET:20250625T101400
DTEND;TZID=CET:20250625T102200
DESCRIPTION:Factor analysis is a powerful tool for examining the dimensiona
 lity of psychological scales and other measurement instruments. While seve
 ral R packages\, such as lavaan\, facilitate the estimation of latent vari
 able models\, they often lack essential diagnostic tools for assessing key
  assumptions of the measurement model. Ignoring these assumptions can lead
  to misleading conclusions. For instance\, poor global model fit may resul
 t from nonlinear relationships between a factor and its indicators\, even 
 when the items are fundamentally unidimensional. To address this gap\, we 
 developed the lavaanDiag package\, which streamlines the diagnostic proces
 s for factor models estimated in lavaan. This package provides functions t
 o visualize residual correlations\, examine relationships between latent v
 ariable estimates\, and compare model-implied and empirical factor-indicat
 or relationships. By offering these tools\, lavaanDiag enhances model eval
 uation and improves the validity of factor analytic research.
DTSTAMP:20260512T122102Z
LOCATION:Underground\, p10
SUMMARY:LT3: Improving Factor Analysis Diagnostics in R: The lavaanDiag Pac
 kage - Karel Rečka
URL:https://pretalx.com/sips2025-budapest/talk/RBLHPR/
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