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Stability of Individual Differences in Multiwave Panel Studies: Comparison of Simplex Models and One‐Factor Models
Author(s) -
Marsh Herbert W.
Publication year - 1993
Publication title -
journal of educational measurement
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.917
H-Index - 47
eISSN - 1745-3984
pISSN - 0022-0655
DOI - 10.1111/j.1745-3984.1993.tb01072.x
Subject(s) - simplex , construct (python library) , structural equation modeling , measure (data warehouse) , scale (ratio) , factor analysis , psychology , statistics , set (abstract data type) , variable (mathematics) , econometrics , mathematics , computer science , data mining , physics , combinatorics , mathematical analysis , quantum mechanics , programming language
The purpose of this investigation is to evaluate structural equation models (SEMs) for measures of the same construct collected on multiple occasions (one‐variable, multiwave panel studies). Simplex models hypothesize that a measure at any one wave is substantially influenced by the measure at the 0immediately preceding wave; correlations between the same construct measured on different occasions are predicted to decline systematically as the number of intervening occasions increases. Alternatively, a one‐factor model posits that a person's score at any one time is a function of some underlying “true” score and a random disturbance that is idiosyncratic to the time; no temporal ordering of correlations is assumed. Both the simplex and one‐factor models can befit when there is only a single indicator of each construct at each wave (e.g., scale scores), but there are serious limitations to such models. Stronger models are possible when the same set of multiple indicators (e.g., the items that make up the scale) is measured at each wave. In Study 1, based on students' evaluations of teaching effectiveness collected over an 8‐year period, one‐factor models fit the data well, whereas simplex models did not. In Study 2, based on personality variables collected over a 4‐year period during adolescence, one‐factor models again provided an excellent fit to the data, whereas the simplex model did marginally poorer. The results challenge an overreliance on simplex models and demonstrate that a one‐factor model is a potentially useful alternative that should be considered in multiwave studies.

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