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PL
Celem niniejszej pracy było przetestowanie modelu teoretycznego zakładającego, że agresja rodzica powstaje w wyniku doświadczania stresu w stosunku do dziecka. Następnie sprawdzono, czy agresja rodziców jest negatywnie związana z rozwojem ich dzieci. W pierwszym badaniu wzięło udział 154 rodziców dzieci w wieku od 3 do 6 lat. Drugie badanie przeprowadzono na 80 dzieciach w wieku od 6 do 10 lat uczęszczających do szkoły oraz na ich rodzicach. Model został przetestowany przy użyciu systemów równań strukturalnych, algorytmy eksploracji danych przeprowadziły analizę skupień, która pogrupowała podmioty na podstawie podobieństwa zmiennych opisanych w modelu. Wyniki pokazały, że zależności w modelu wahały się od umiarkowanych do wysokich. Rodzice, którzy w największym stopniu stosowali presję, agresję i wycofywanie się, mieli najwyższy poziom stresu rodzicielskiego.
EN
The aim of this study was to test a theoretical model assuming that a parent’s aggression arises as a result of experiencing stress in relation to their child. Subsequently, it was checked whether the parents’ aggression is negatively related to the development of their children. Hundred fifty-four parents of children aged 3 to 6 took part in the first study. The second study was conducted on 80 children between 6- and 10-years old attending school and on their parents. The model was tested using structural equation systems, data mining algorithms performed a cluster analysis that grouped the subjects based on similarity in the variables described in the model. The results revealed that the relationships in the model ranged from moderate to high. Parents who used pressure, aggression, and withdrawal to the greatest extent had the highest levels of parental stress.
EN
Personal characteristics that parents want to shape in their children are called parental goals and can be divided into desired and undesired traits. Which of them are most and the least desirable by parents in context of developing child’s personality? Do parental goals change with the age of the child? The study was conducted on a sample of 319 parents of children aged 3, 4, 5 and 6 years old. Analyses were carried out using two data mining algorithms: (a) text mining algorithms, (b) support vector machine and (c) social network analysis, and (d) Aranowska's λ judge agreement coefficient. The results revealed that parents of preschool children care mainly about the development of competency traits, especially self-reliance. When it comes to undesirable traits, parents make sure that their children do not develop traits from the field of temperament - personality (especially aggressiveness) and traits from the area of lack of virtues (selfishness, laziness, lies). It is noticeable that when the child reaches the age of 4 the parental goals change. Based on the characteristics selected by parents, it can be correctly predicted how old the child is.
EN
Aggression can be evaluated in a variety of ways. Among the self-reported measures, the Buss-Durkee Hostility Inventory (Buss, Durkee, 1957) has been one of the most popular questionnaire. On the basis of this previous work, Buss and Perry proposed a psychometrically improved and updated measure of aggression: The Aggression Questionnaire (Buss, Perry, 1992). The Buss-Perry Aggression Ques-tionnaire (BPQA) has quickly become the gold-standard for the measurement of aggression. The original version of the BPAQ contains 29 items and is designed to assess four dispositional components of aggression: Physical Aggression, Verbal Aggression, Anger, and Hostility. However, the BPAQ scale has been extensively validated, the validation focused, mainly, on samples of college students. In this study, exploratory and confirmatory models were evaluated among a sample of 3990 Polish participants (aged from 10 to 79 years). A 5-factor structure resulted in the exploratory analysis and 5-factor structure showed acceptable fits in confirmatory analyses. Implications and limitations of these solutions are discussed.
EN
The paper describes a model of the multivariate analysis of variance (MANOVA). First, we outline differences between this method and the univariate analysis of variance (ANOVA). We present basic repeated measures designs and point to the research designs that provide data which can be analyzed only with the MANOYA models. We describe formal structure of the MANOVA model and provide its basic definitions. We show how these definitions are related to terms of ANOVA. Development of the ANOVA logic into the MANOYA model is shown in relation to a discussion on independence between expected values of variables and their bivariate correlations (more precisely - means of variables and Pearson product-moment correlation coefficients). We explain how the assumptions, null hypotheses and test statistics of MANOVA have been developed from the ANOVA model. We point to the inconclusiveness of the formal MANOYA solution (lack of the one, established, test statistic) and show these test statistics which appeared most often in the statistical software in the last twenty years. We illustrate formalities of the model with one fictional example of a simple one-way MANOVA. Ali test statistics introduced in this paper were calculated by hand and compared with SPSS output. Moreover, an example of application of multivariate analysis of variance in psychological research was portrayed, using a study on evaluation of managers' performance. In this example, we emphasize reasons why it is necessary to complement MANOVA with another method: discriminant analysis.
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