50 research outputs found

    Age and Employee Green Behaviors: A Meta-Analysis

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    Recent economic and societal developments have led to an increasing emphasis on organizational environmental performance. At the same time, demographic trends are resulting in increasingly aging labor forces in many industrialized nations. Commonly held stereotypes suggest that older workers are less likely to be environmentally responsible than younger workers. To evaluate the degree to which such age differences are present, we meta-analyzed 132 independent correlations and 336 d-values based on 4676 professional workers from 22 samples in 11 countries. Contrary to popular stereotypes, age showed small positive relationships with pro-environmental behaviors, suggesting that older adults engaged in these workplace behaviors slightly more frequently. Relationships with age appeared to be linear for overall, Conserving, Avoiding Harm, and Taking Initiative pro-environmental behaviors, but non-linear trends were observed for Transforming and Influencing Others behaviors

    Age and Employee Green Behaviors: A Meta-Analysis

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    Recent economic and societal developments have led to an increasing emphasis on organizational environmental performance. At the same time, demographic trends are resulting in increasingly aging labor forces in many industrialized nations. Commonly held stereotypes suggest that older workers are less likely to be environmentally responsible than younger workers. To evaluate the degree to which such age differences are present, we meta-analyzed 132 independent correlations and 336 d-values based on 4676 professional workers from 22 samples in 11 countries. Contrary to popular stereotypes, age showed small positive relationships with pro-environmental behaviors, suggesting that older adults engaged in these workplace behaviors slightly more frequently. Relationships with age appeared to be linear for overall, Conserving, Avoiding Harm, and Taking Initiative pro-environmental behaviors, but non-linear trends were observed for Transforming and Influencing Others behaviors

    datawizard: an R package for easy data preparation and statistical transformations

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    The {datawizard} package for the R programming language (R Core Team, 2021) provides a lightweight toolbox to assist in key steps involved in any data analysis workflow: (1) wrangling the raw data to get it in the needed form, (2) applying preprocessing steps and statistical transformations, and (3) compute statistical summaries of data properties and distributions. Therefore, it can be a valuable tool for R users and developers looking for a lightweight option for data preparation

    Not all effects are indispensable: Psychological science requires verifiable lines of reasoning for whether an effect matters

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    Psychological researchers currently lack guidance for how to make claims about and evaluate the practical relevance and significance of observed effect sizes, i.e. whether a finding will have impact when translated to a different context of application. Although psychologists have recently highlighted theoretical justifications for why small effect sizes might be practically relevant, such justifications fail to provide the information necessary for evaluation and falsification. Claims about whether an observed effect size is practically relevant need to consider both the mechanisms amplifying and counteracting practical relevance, as well as the assumptions underlying each mechanism at play. To provide guidance for making claims about whether an observed effect size is practically relevant in such a way that the claims can be systematically evaluated, we present examples of widely applicable mechanisms and the key assumptions needed for justifying whether an observed effect size can be expected to generalize to different contexts. Routine use of these mechanisms to justify claims about practical relevance has the potential to make researchers’ claims about generalizability substantially more transparent. This transparency can help move psychological science towards a more rigorous assessment of when psychological findings can be applied in the world

    The Crowdsourced Replication Initiative: Investigating Immigration and Social Policy Preferences. Executive Report.

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    In an era of mass migration, social scientists, populist parties and social movements raise concerns over the future of immigration-destination societies. What impacts does this have on policy and social solidarity? Comparative cross-national research, relying mostly on secondary data, has findings in different directions. There is a threat of selective model reporting and lack of replicability. The heterogeneity of countries obscures attempts to clearly define data-generating models. P-hacking and HARKing lurk among standard research practices in this area.This project employs crowdsourcing to address these issues. It draws on replication, deliberation, meta-analysis and harnessing the power of many minds at once. The Crowdsourced Replication Initiative carries two main goals, (a) to better investigate the linkage between immigration and social policy preferences across countries, and (b) to develop crowdsourcing as a social science method. The Executive Report provides short reviews of the area of social policy preferences and immigration, and the methods and impetus behind crowdsourcing plus a description of the entire project. Three main areas of findings will appear in three papers, that are registered as PAPs or in process

    configural: Multivariate profile analysis

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    Supplemental materials for Predictors of hurricane evacuation decisions: A meta-analysis

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    \u3cem\u3epsychmeta\u3c/em\u3e: An R Package for Psychometric Meta-Analysis

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    Over the past four decades, psychometric meta-analysis (PMA) has emerged a key way that psychological disciplines build cumulative scientific knowledge. Despite the importance and popularity of PMA, software implementing the method has tended to be closed-source, inflexible, limited in terms of the psychometric corrections available, cumbersome to use for complex analyses, and/or costly. To overcome these limitations, we created the psychmeta R package: a free, open-source, comprehensive program for PMA
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