9 research outputs found
Integrating Financial Therapy within Family-Owned Businesses: A Theoretical Case Vignette with Recommended Strategies for Consulting with Copreneurs
Get PDFBroadly speaking, finances are often one of the most strenuous aspects of a relationship. One potential contributing factor to financial conflict experienced by couples are having different beliefs or attitudes towards money, coined previously as money scripts (Klontz, Kahler, & Klontz, 2008). Differing money scripts between partners can cause a breach in understanding of their partner\u27s internal experience around money that may lead to misunderstanding and conflict. This may be magnified for copreneurs, or romantic partners, who integrate a personal and working relationship within a business’s ownership structure. In this unique arrangement of personal and professional relationships, the traditional lines separating work and home life are either nonexistent or blurred. This paper serves to explore the conflict through a hypothetical case study and provides detailed financial therapy interventions that may be used to help copreneurs who are experiencing money conflict. The outline of interventions serves to aid financial therapists in their work with clients who are part of a family-owned business by helping these clients better communicate through the unique dynamics of a copreneur relationship
Conceptual Framework for Using Computers to Enhance Employee Engagement in Large Offices
No full textModeling Linkage Disequilibrium Increases Accuracy of Polygenic Risk Scores
Get PDFPolygenic risk scores have shown great promise in predicting complex disease risk and will become more accurate as training sample sizes increase. The standard approach for calculating risk scores involves linkage disequilibrium (LD)-based marker pruning and applying a p value threshold to association statistics, but this discards information and can reduce predictive accuracy. We introduce LDpred, a method that infers the posterior mean effect size of each marker by using a prior on effect sizes and LD information from an external reference panel. Theory and simulations show that LDpred outperforms the approach of pruning followed by thresholding, particularly at large sample sizes. Accordingly, predicted R2 increased from 20.1% to 25.3% in a large schizophrenia dataset and from 9.8% to 12.0% in a large multiple sclerosis dataset. A similar relative improvement in accuracy was observed for three additional large disease datasets and for non-European schizophrenia samples. The advantage of LDpred over existing methods will grow as sample sizes increase
Modeling Linkage Disequilibrium Increases Accuracy of Polygenic Risk Scores
No full textPolygenic risk scores have shown great promise in predicting complex disease risk and will become more accurate as training sample sizes increase. The standard approach for calculating risk scores involves linkage disequilibrium (LD)-based marker pruning and applying a p value threshold to association statistics, but this discards information and can reduce predictive accuracy. We introduce LDpred, a method that infers the posterior mean effect size of each marker by using a prior on effect sizes and LD information from an external reference panel. Theory and simulations show that LDpred outperforms the approach of pruning followed by thresholding, particularly at large sample sizes. Accordingly, predicted R2 increased from 20.1% to 25.3% in a large schizophrenia dataset and from 9.8% to 12.0% in a large multiple sclerosis dataset. A similar relative improvement in accuracy was observed for three additional large disease datasets and for non-European schizophrenia samples. The advantage of LDpred over existing methods will grow as sample sizes increase
