Contrasts and Correlations in Effect-size Estimation

This article describes procedures for presenting standardized measures of effect size when contrasts are used to ask focused questions of data. The simplest contrasts consist of comparisons of two samples (e.g., based on the independent t statistic). Useful effect-size indices in this situation are members of the g family (e.g., Hedges's g and Cohen's d) and the Pearson r. We review expressions for calculating these measures and for transforming them back and forth, and describe how to adjust formulas for obtaining g or d from t, or r from g, when the sample sizes are unequal. The real-life implications of d or g calculated from t become problematic when there are more than two groups, but the correlational approach is adaptable and interpretable, although more complex than in the case of two groups. We describe a family of four conceptually related correlation indices: the alerting correlation, the contrast correlation, the effect-size con-elation, and the BESD (binomial effect-size display) correlation. These last three correlations are identical in the simple setting of only two groups, but differ when there are move than two groups.Psycholog

Physiological Correlates of Volunteering

We review research on physiological correlates of volunteering, a neglected but promising research field. Some of these correlates seem to be causal factors influencing volunteering. Volunteers tend to have better physical health, both self-reported and expert-assessed, better mental health, and perform better on cognitive tasks. Research thus far has rarely examined neurological, neurochemical, hormonal, and genetic correlates of volunteering to any significant extent, especially controlling for other factors as potential confounds. Evolutionary theory and behavioral genetic research suggest the importance of such physiological factors in humans. Basically, many aspects of social relationships and social activities have effects on health (e.g., Newman and Roberts 2013; Uchino 2004), as the widely used biopsychosocial (BPS) model suggests (Institute of Medicine 2001). Studies of formal volunteering (FV), charitable giving, and altruistic behavior suggest that physiological characteristics are related to volunteering, including specific genes (such as oxytocin receptor [OXTR] genes, Arginine vasopressin receptor [AVPR] genes, dopamine D4 receptor [DRD4] genes, and 5-HTTLPR). We recommend that future research on physiological factors be extended to non-Western populations, focusing specifically on volunteering, and differentiating between different forms and types of volunteering and civic participation

Beginning behavioral research : a conceptual primer, 6th ed./ Rosnow

xviii, 461 hal.: tab.; 23 cm

Beginning behavioral research : a conceptual primer, 6th ed./ Rosnow

xviii, 461 hal.: tab.; 23 cm

Quantitative Methods and Ethics

The purpose of this chapter is to provide a context for thinking about the role of ethics in quantitative methodology.We begin by reviewing the sweep of events that led to the creation and expansion of legal and professional rules for the protection of research subjects and society against unethical research. The risk–benefit approach has served as an instrument of prior control by institutional review boards. After discussing the nature of that approach,we sketch a model of the costs and utilities of the “doing” and “not doing” of research.We illustrate some implications of the expanded model for particular data analytic and reporting practices.We then outline a 5 × 5 matrix of general ethical standards crossed with general data analytic and reporting standards to encourage thinking about opportunities to address quantitative methodological problems in ways that may have mutual ethical and substantive rewards. Finally,we discuss such an opportunity in the context of problems associated with risk statistics that tend to exaggerate the absolute effects of therapeutic interventions in randomized trials