Analysis of Latent Classes and Influencing Factors According to the Love Types of Korean Adults

2021 ◽  
Vol 27 (4) ◽  
pp. 561-584
Author(s):  
Moon-Sun Ha ◽  
Yeon-Joo Song
Author(s):  
Hanna Lee ◽  
Jeong-Won Han

This study aimed to classify the latent class of parenting attitude for parents with preschool children and school-age children, identify the pattern of transition in the type of parenting attitude over time, and determine the influencing factors associated with the transition. A total of 1462 households were the subjects of this longitudinal study that used latent profile analysis, latent transition analysis, and logistic regression analysis. The parenting attitude in the preschool year was classified into a model of three latent classes of ‘parent uninvolved’, ‘maternal authoritative and paternal authoritarian’, and ‘maternal authoritarian and paternal authoritative’, and the parenting attitude in the school year was classified into a model of four latent classes of ‘parent weak uninvolved’, ‘parent strong uninvolved’, parent authoritative’, and ‘maternal authoritarian and paternal authoritative.’ All latent class subjects with preschool children showed an attitude transition to maternal authoritarian and paternal authoritative when their children were in school years. It was confirmed that a mother’s depression and father’s parenting stress were the most influential factors in the parenting attitude transition. This study lay in identifying the patterns of parenting attitude and the transition in attitude according to the developmental stage of children.


2012 ◽  
Vol 5 ◽  
pp. S95-S96
Author(s):  
Min-Suk Yang ◽  
Yoon-Jung Kim ◽  
Woo-Jung Song ◽  
Min-Hye Kim ◽  
Gyu-Young Hur ◽  
...  

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.


2010 ◽  
Author(s):  
Louis Tay ◽  
Ed Diener ◽  
Fritz Drasgow
Keyword(s):  

2018 ◽  
Author(s):  
I Iozsef ◽  
O Ilyés ◽  
P Miheller ◽  
AV Patai
Keyword(s):  

CICTP 2017 ◽  
2018 ◽  
Author(s):  
Bowen Dong ◽  
Wenjun Du ◽  
Feng Chen ◽  
Qi Deng ◽  
Xiaodong Pan
Keyword(s):  

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