Obtaining measurement-invariant latent classes across hierarchical units

2010 ◽  
Author(s):  
Louis Tay ◽  
Ed Diener ◽  
Fritz Drasgow
Keyword(s):  
Methodology ◽  
2014 ◽  
Vol 10 (3) ◽  
pp. 100-107 ◽  
Author(s):  
Jürgen Groß ◽  
Ann Cathrice George

When a psychometric test has been completed by a number of examinees, an afterward analysis of required skills or attributes may improve the extraction of diagnostic information. Relying upon the retrospectively specified item-by-attribute matrix, such an investigation may be carried out by classifying examinees into latent classes, consisting of subsets of required attributes. Specifically, various cognitive diagnosis models may be applied to serve this purpose. In this article it is shown that the permission of all possible attribute combinations as latent classes can have an undesired effect in the classification process, and it is demonstrated how an appropriate elimination of specific classes may improve the classification results. As an easy example, the popular deterministic input, noisy “and” gate (DINA) model is applied to Tatsuoka’s famous fraction subtraction data, and results are compared to current discussions in the literature.


2021 ◽  
pp. 088626052199912
Author(s):  
Valdemir Ferreira-Junior ◽  
Juliana Y. Valente ◽  
Zila M. Sanchez

Although many studies addressed bullying occurrence and its associations, they often use individual variables constructed from few items that probably are inadequate to evaluate bullying severity and type. We aimed to identify involvement patterns in bullying victimization and perpetration, and its association with alcohol use, school performance, and sociodemographic variables. Baseline assessment of a randomized controlled trial were used and a latent class analysis was conducted to identify bullying patterns among 1,742 fifth-grade and 2,316 seventh-grade students from 30 public schools in São Paulo, Brazil. Data were collected using an anonymous self-reported, audio-guided questionnaire completed by the participants on smartphones. Multinomial logistic regressions were performed to verify how covariant variables affected bullying latent classes. Both grades presented the same four latent classes: low bullying, moderate bullying victimization, high bullying victimization, and high bullying victimization and perpetration. Alcohol use was associated with all bullying classes in both grades, with odds ratio up to 5.36 (95% CI 3.05; 10.38) among fifth graders from the high bullying victimization and perpetration class. Poor school performance was also strongly associated with this class (aOR = 10.12, 95%CI = 4.19; 24.41). Black/brown 5th graders were 3.35 times more likely to fit into the high bullying victimization class (95% CI 1.34; 8.37). Lack of evidence for association of sociodemographic variables and bullying latent class among seventh-grade students was found. Bullying and alcohol use are highly harmful behaviors that must be prevented. However, prevention programs should consider how racial and gender issues are influencing the way students experience violence.


2021 ◽  
pp. 100305
Author(s):  
Jan Ostermann ◽  
Brian P. Flaherty ◽  
Derek S. Brown ◽  
Bernard Njau ◽  
Amy M. Hobbie ◽  
...  

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