Publications by authors named "Matthijs J Warrens"

Since people's attitude toward lesbians, gay men and bisexual people (LGB) affects young LGB people's mental health and subsequently their quality of life, it is important to establish people's attitudes toward LGB people. The current study examined attitudes toward lesbian, gay and bisexual people among Dutch students and the psychometrical characteristics of adapted instruments measuring attitudes toward sexual diversity. The students in the sample (N = 1.

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There is ample evidence showing that childhood maltreatment increases two to three fold the risk of victimization in adulthood. Various risk factors, including posttraumatic stress disorder (PTSD) symptoms, dissociation, self-blame, and alcohol abuse are related to revictimization. Although previous research examined associations between risk factors for revictimization, the evidence is limited and the proposed models mostly include a handful of risk factors.

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Regression analysis makes up a large part of supervised machine learning, and consists of the prediction of a continuous independent target from a set of other predictor variables. The difference between binary classification and regression is in the target range: in binary classification, the target can have only two values (usually encoded as 0 and 1), while in regression the target can have multiple values. Even if regression analysis has been employed in a huge number of machine learning studies, no consensus has been reached on a single, unified, standard metric to assess the results of the regression itself.

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Cohen's kappa coefficient is commonly used for assessing agreement between classifications of two raters on a nominal scale. Three variants of Cohen's kappa that can handle missing data are presented. Data are considered missing if one or both ratings of a unit are missing.

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Objectives: De Vet, Mokkink, Mosmuller, and Terwee (2017) discovered that the Spearman-Brown formula (SB formula) can be used to transform certain intraclass correlation coefficients (ICCs) for single measurements into the corresponding ICCs for average measurements, without knowledge of the variance components.

Results: A formal proof of the discovery by De Vet et al. is presented.

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Cohen's kappa is presently a standard tool for the analysis of agreement in a 2 × 2 reliability study, and weighted kappa is a standard statistic for summarizing a 2 × 2 validity study. The special cases of weighted kappa, for example Cohen's kappa, are chance-corrected measures of association. For various measures of 2 × 2 association it has been observed in the literature that, after correction for chance, they coincide with a special case of weighted kappa.

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We discuss properties that association coefficients may have in general, e.g., zero value under statistical independence, and we examine coefficients for 2x2 tables with respect to these properties.

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This paper studies correction for chance in coefficients that are linear functions of the observed proportion of agreement. The paper unifies and extends various results on correction for chance in the literature. A specific class of coefficients is used to illustrate the results derived in this paper.

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Individual performance was compared across three different tasks that tap into the binding of stimulus features in perception, the binding of action features in action planning, and the emergence of stimulus-response bindings ("event files"). Within a task correlations between the size of binding effects were found within visual perception (e.g.

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