Matching Items (8)

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Examining the Factor Structure of the Hare Self-Report Psychopathy Scale

Description

The 64-item Hare Self-Report Psychopathy Scale (Hare SRP; Paulhus, Neumann, & Hare, in press) is the most recent revision of the SRP, which has undergone numerous iterations. Little research has

The 64-item Hare Self-Report Psychopathy Scale (Hare SRP; Paulhus, Neumann, & Hare, in press) is the most recent revision of the SRP, which has undergone numerous iterations. Little research has been conducted with this new edition; therefore, the goal of the current study was to elucidate the factor structure as well as the criterion-related, convergent, and discriminant validity of the measure in a large sample of college students (N=602). Confirmatory factor analyses revealed that the best-fitting model was the original four-factor model proposed by the authors of the Hare SRP (compared to a one-factor, two-factor, and four-factor random model). The four-factor model revealed superior fit for the data relative to the other alternative models. In addition, we elaborated on the psychometric properties of this four-factor model in this sample. The Hare SRP total and factor scores evidenced good internal reliability as well as promising criterion-related, convergent, and discriminant validity in terms of predicting scores on conceptually relevant external criteria. Implications for theory and future research are discussed.

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Created

Date Created
  • 2012

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The factor structure of curriculum-based writing indices at Grades 3, 7, and 10

Description

National assessment data indicate that the large majority of students in America perform below expected proficiency levels in the area of writing. Given the importance of writing skills, this is

National assessment data indicate that the large majority of students in America perform below expected proficiency levels in the area of writing. Given the importance of writing skills, this is a significant problem. Curriculum-based measurement, when used for progress monitoring and intervention planning, has been shown to lead to improved academic achievement. However, researchers have not yet been able to establish the validity of curriculum-based measures of writing (CBM-W). This study examined the structural validity of CBM-W using exploratory factor analysis. The participants for this study were 253 third, 154 seventh, and 154 tenth grade students. Each participant completed a 3-minute writing sample in response to a narrative prompt. The writing samples were scored for fifteen different CBM-W indices. Separate analyses were conducted for each grade level to examine differences in the CBM-W construct across grade levels. Due to extreme multicollinearity, principal components analysis rather than common factor analysis was used to examine the structure of writing as measured by CBM-W indices. The overall structure of CBM-W indices was found to remain stable across grade levels. In all cases a three-component solution was supported, with the components being labeled production, accuracy, and sentence complexity. Limitations of the study and implications for progress monitoring with CBM-W are discussed, including the recommendation for a combination of variables that may provide more reliable and valid measurement of the writing construct.

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Created

Date Created
  • 2012

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The sensitivity of confirmatory factor analytic fit indices to violations of factorial invariance across latent classes: a simulation study

Description

Although the issue of factorial invariance has received increasing attention in the literature, the focus is typically on differences in factor structure across groups that are directly observed, such as

Although the issue of factorial invariance has received increasing attention in the literature, the focus is typically on differences in factor structure across groups that are directly observed, such as those denoted by sex or ethnicity. While establishing factorial invariance across observed groups is a requisite step in making meaningful cross-group comparisons, failure to attend to possible sources of latent class heterogeneity in the form of class-based differences in factor structure has the potential to compromise conclusions with respect to observed groups and may result in misguided attempts at instrument development and theory refinement. The present studies examined the sensitivity of two widely used confirmatory factor analytic model fit indices, the chi-square test of model fit and RMSEA, to latent class differences in factor structure. Two primary questions were addressed. The first of these concerned the impact of latent class differences in factor loadings with respect to model fit in a single sample reflecting a mixture of classes. The second question concerned the impact of latent class differences in configural structure on tests of factorial invariance across observed groups. The results suggest that both indices are highly insensitive to class-based differences in factor loadings. Across sample size conditions, models with medium (0.2) sized loading differences were rejected by the chi-square test of model fit at rates just slightly higher than the nominal .05 rate of rejection that would be expected under a true null hypothesis. While rates of rejection increased somewhat when the magnitude of loading difference increased, even the largest sample size with equal class representation and the most extreme violations of loading invariance only had rejection rates of approximately 60%. RMSEA was also insensitive to class-based differences in factor loadings, with mean values across conditions suggesting a degree of fit that would generally be regarded as exceptionally good in practice. In contrast, both indices were sensitive to class-based differences in configural structure in the context of a multiple group analysis in which each observed group was a mixture of classes. However, preliminary evidence suggests that this sensitivity may contingent on the form of the cross-group model misspecification.

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Created

Date Created
  • 2011

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A study of statistical power and type I errors in testing a factor analytic model for group differences in regression intercepts

Description

In the past, it has been assumed that measurement and predictive invariance are consistent so that if one form of invariance holds the other form should also hold. However, some

In the past, it has been assumed that measurement and predictive invariance are consistent so that if one form of invariance holds the other form should also hold. However, some studies have proven that both forms of invariance only hold under certain conditions such as factorial invariance and invariance in the common factor variances. The present research examined Type I errors and the statistical power of a method that detects violations to the factorial invariant model in the presence of group differences in regression intercepts, under different sample sizes and different number of predictors (one or two). Data were simulated under two models: in model A only differences in the factor means were allowed, while model B violated invariance. A factorial invariant model was fitted to the data. Type I errors were defined as the proportion of samples in which the hypothesis of invariance was incorrectly rejected, and statistical power was defined as the proportion of samples in which the hypothesis of factorial invariance was correctly rejected. In the case of one predictor, the results show that the chi-square statistic has low power to detect violations to the model. Unexpected and systematic results were obtained regarding the negative unique variance in the predictor. It is proposed that negative unique variance in the predictor can be used as indication of measurement bias instead of the chi-square fit statistic with sample sizes of 500 or more. The results of the two predictor case show larger power. In both cases Type I errors were as expected. The implications of the results and some suggestions for increasing the power of the method are provided.

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Created

Date Created
  • 2010

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Quantifying the matrix of domination

Description

This paper is seeking to use exploratory factor analysis to construct a numeric representation of Hill Collin's matrix of domination. According to Hill Collins, the Current American matrix of domination,

This paper is seeking to use exploratory factor analysis to construct a numeric representation of Hill Collin's matrix of domination. According to Hill Collins, the Current American matrix of domination, or the interlocking systems of oppression, includes race, gender, class, sexual orientation, religion, immigration status, disability, and age. The study uses exploratory factor analysis to construct a matrix of domination scale. The study launched an on-line survey (n=448) that was circulated through the social network Facebook to collect data. Factor analysis revealed that the constructed matrix of domination represents an accurate description of the current social hierarchy in the United States. Also, the constructed matrix of domination was an accurate predictor of the probability of experiencing domestic abuse according to the current available statistics.

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Created

Date Created
  • 2011

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The structure of cyber and traditional aggression: an integrated conceptualization

Description

ABSTRACT The phenomenon of cyberbullying has captured the attention of educators and researchers alike as it has been associated with multiple aversive outcomes including suicide. Young people today have easy

ABSTRACT The phenomenon of cyberbullying has captured the attention of educators and researchers alike as it has been associated with multiple aversive outcomes including suicide. Young people today have easy access to computer mediated communication (CMC) and frequently use it to harass one another -- a practice that many researchers have equated to cyberbullying. However, there is great disagreement among researchers whether intentional harmful actions carried out by way of CMC constitute cyberbullying, and some authors have argued that "cyber-aggression" is a more accurate term to describe this phenomenon. Disagreement in terms of cyberbullying's definition and methodological inconsistencies including choice of questionnaire items has resulted in highly variable results across cyberbullying studies. Researchers are in agreement however, that cyber and traditional forms of aggression are closely related phenomena, and have suggested that they may be extensions of one another. This research developed a comprehensive set of items to span cyber-aggression's content domain in order to 1) fully address all types of cyber-aggression, and 2) assess the interrelated nature of cyber and traditional aggression. These items were administered to 553 middle school students located in a central Illinois school district. Results from confirmatory factor analyses suggested that cyber-aggression is best conceptualized as integrated with traditional aggression, and that cyber and traditional aggression share two dimensions: direct-verbal and relational aggression. Additionally, results indicated that all forms of aggression are a function of general aggressive tendencies. This research identified two synthesized models combining cyber and traditional aggression into a shared framework that demonstrated excellent fit to the item data.

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Created

Date Created
  • 2013

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Factor Structure of the Wechsler Intelligence Scales for Children-Fourth Edition Among Referred Native American Students

Description

The Native American population is severely underrepresented in empirical test validity research despite being overrepresented in special education programs and at an increased risk for special educational evaluation. This study

The Native American population is severely underrepresented in empirical test validity research despite being overrepresented in special education programs and at an increased risk for special educational evaluation. This study is the first to investigate the structural validity of the Wechsler Intelligence Scale for Children - Fourth Edition (WISC-IV) with a Native American sample. The structural validity of the WISC-IV was investigated using the core subtest scores of 176, six-to-sixteen-year-old Native American children referred for a psychoeducational evaluation. The exploratory factor analysis procedures reported in the WISC-IV technical manual were replicated with the current sample. Congruence coefficients were used to measure the similarity between the derived factor structure and the normative factor structure. The Schmid-Leiman orthogonalization procedure was used to study the role of the higher-order general ability factor. Results support the structural validity of the first-order and higher-order factors of the WISC-IV within this sample. The normative first-order factor structure was replicated in this sample, and the Schmid-Leiman procedure identified a higher-order general ability factor that accounted for the greatest amount of common variance (70%) and total variance (37%). The results support the structural validity of the WISC-IV within a referred Native American sample. The outcome also suggests that interpretation of the WISC-IV scores should focus on the global ability factor.

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Created

Date Created
  • 2011

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Cyberbullying among children in Japanese and American middle schools: an exploration of prevalence and predictors

Description

ABSTRACT Cyberbullying has emerged as one of educators' and researchers' chief concerns as the use of computer mediated communication (CMC) has become ubiquitous among young people. Many undesirable outcomes have

ABSTRACT Cyberbullying has emerged as one of educators' and researchers' chief concerns as the use of computer mediated communication (CMC) has become ubiquitous among young people. Many undesirable outcomes have been identified as being linked to both traditional and cyberbullying, including depression,truancy, and suicide. America and Japan have both been identified as nations whose youth engage frequently in the use of CMC, and may be at a potentially higher risk to be involved in cyberbullying. Time spent using CMC has been linked to involvement in cyberbullying, and gender and age have, in turn, been linked to CMC use - these may play significant roles in determining who is at risk. In order to assess the effects of nationality, gender, and age on cyberbullying involvement among Japanese and American middle school students, a survey exploring these factors was developed and carried out with 590 American and Japanese middles school students (Japan: n = 433 and America: n = 157). MANOVA results indicated that that Americans tend to both use CMC more and be more involved in cyberbullying. In addition, Japanese involvement increased with age, while American involvement did not. There were minimal differences between Americans and Japanese with regards to traditional bullying.

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Agent

Created

Date Created
  • 2011