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DTSTART:20231102T020000
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DESCRIPTION:When fitting models to data\, general assumptions are frequentl
y made automatically without much consideration for their implication on s
ubsequent interpretations. For instance\, fitting a standard factor model
often presupposes an underlying set of continuous\, latent factors. Likewi
se\, when searching for group structure\, mixture models (e.g.\, latent pr
ofile analysis\, latent class analysis) or cluster analysis are implemente
d and assume a set of discrete latent classes". Usually\, the type of mode
l that is fit to the data is governed by the theoretical notions underpinn
ing the substantive question of interest. In this talk\, it is shown that
both types of structures can be present and correspond to different subset
s of the data. A general strategy is discussed for extracting both class s
tructure and factor structure. Demonstrations are given on a data set of i
nternet habits of collegiate students.
DTEND:20150427T180000Z
DTSTAMP:20240917T044449Z
DTSTART:20150427T170000Z
LOCATION:USA
SEQUENCE:0
SUMMARY:Steinley Talk
UID:RFCALITEM638621270893315353
X-ALT-DESC;FMTTYPE=text/html:When fitting models to data\, general assum
ptions are frequently made automatically without much consideration for th
eir implication on subsequent interpretations. For instance\, fitting a st
andard factor model often presupposes an underlying set of continuous\, la
tent factors. Likewise\, when searching for group structure\, mixture mode
ls (e.g.\, latent profile analysis\, latent class analysis) or cluster ana
lysis are implemented and assume a set of discrete latent classes". Usuall
y\, the type of model that is fit to the data is governed by the theoretic
al notions underpinning the substantive question of interest. In this talk
\, it is shown that both types of structures can be present and correspond
to different subsets of the data. A general strategy is discussed for ext
racting both class structure and factor structure. Demonstrations are give
n on a data set of internet habits of collegiate students.

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