2017
DOI: 10.1080/10705511.2017.1408015
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Assessing Measurement Invariance in Multiple-Group Latent Profile Analysis

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Cited by 37 publications
(33 citation statements)
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“…As the majority of PSTs assessed with the TOPS are primarily cognitive and arousal-based in nature, it is also important to consider additional measures that capture emotionally-salient PSTs. Second, our focus on Malaysian elite athletes means it is important that future research examines the extent to which these findings generalize to other cohorts of athletes (e.g., culture), and test the invariance of latent profiles across different subgroups (e.g., sex, sport type; Olivera-Aguilar & Rikoon, 2018 ). Third, we relied on one outcome variable to assess external validity evidence of the latent profiles.…”
Section: Discussionmentioning
confidence: 99%
“…As the majority of PSTs assessed with the TOPS are primarily cognitive and arousal-based in nature, it is also important to consider additional measures that capture emotionally-salient PSTs. Second, our focus on Malaysian elite athletes means it is important that future research examines the extent to which these findings generalize to other cohorts of athletes (e.g., culture), and test the invariance of latent profiles across different subgroups (e.g., sex, sport type; Olivera-Aguilar & Rikoon, 2018 ). Third, we relied on one outcome variable to assess external validity evidence of the latent profiles.…”
Section: Discussionmentioning
confidence: 99%
“…The study of measurement invariance in LPA (MI-LPA) is necessary to evaluate whether the latent profiles’ number and nature are the same across certain groups (here, across the three countries’ samples: Germany, Greece, and Switzerland) observed using a series of nested models [ 112 ]. The MI-LPA was tested by comparing an unconstrained model with the same number of profiles and freely estimated means to a means-constrained model across the three countries’ samples.…”
Section: Methodsmentioning
confidence: 99%
“…Therefore, two models were compared: a configural similarity model with freely estimated pattern indicator means between measurement points, and a structural similarity model with equal indicator means. To review the two models, a χ 2 difference testusing the maximum likelihood estimator (MLR) with Satorra-Bentler scaling correction was performed, and both BIC and aBIC were compared (Morin, Meyer, Creusier, & Biétry, 2016b;Olivera-Aguilar & Rikoon, 2018). Secondly, on a more specific level, an indicator of structural stability (SSi) was calculated by averaging squared Euclidian distance between two patterns.…”
Section: Data Analysesmentioning
confidence: 99%