Hoffman, West, & Sheets, 2002; Preacher & Hayes, 2004, 2008; Shrout & Bolger, 2002). In the current study, the Baron and Kenny (1986) criteria were not applied as these are considered to be overly conservative and require a very large sample size to achieve sufficient power (Preacher & Hayes, 2008). Furthermore, mediation results were not described as or as per recent guidance (Rucker, Preacher, Tormala & Petty, ‘full’ ‘partial’ 2011). Bootstrapping techniques were performed in line with recommendations by Preacher and Hayes (2008), with 5000 resamples and 95% bias-corrected and accelerated (BCa) confidence intervals (CI) used to evaluate indirect effects. BCa confidence intervals include corrections for median bias and skew (Efron & Tibshirani, 1993). The use of 95% confidence intervals is equivalent to testing for significance at the .05 level. Indirect effects were considered as significant when the BCa confidence interval did not include zero. Assumptions of the data were checked prior to completing the mediation analysis. Mediation effect sizes were calculated using Preacher and Kelley’s (2011) method as this method is κ² able to describe how large the indirect effect is compared to how large it could be. They argue it can be interpreted using Cohen’s effect size criterion whereby small, medium, and large effect sizes stand at .01, .09, and .25 respectively (Cohen, 1988). Figure 1: The mediation 3. Results 3.1. Sample Characteristics 3.1.1. Response Rate
Hoffman, West, & Sheets, 2002; Preacher & Hayes, 2004, 2008; Shrout & Bolger, 2002). In the current study, the Baron and Kenny (1986) criteria were not applied as these are considered to be overly conservative and require a very large sample size to achieve sufficient power (Preacher & Hayes, 2008). Furthermore, mediation results were not described as ‘full’ or ‘partial’ as per recent guidance (Rucker, Preacher, Tormala & Petty, 2011). Bootstrapping techniques were performed in line with recommendations by Preacher and Hayes (2008), with 5000 resamples and 95% bias-corrected and accelerated (BCa) confidence intervals (CI) used to evaluate indirect effects. BCa confidence intervals include corrections for median bias and skew (Efron & Tibshirani, 1993). The use of 95% confidence intervals is equivalent to testing for significance at the .05 level. Indirect effects were considered as significant when the BCa confidence interval did not include zero. Assumptions of the data were checked prior to completing the mediation analysis. Mediation effect sizes were calculated using Preacher and Kelley’s (2011) κ² method as this method is able to describe how large the indirect effect is compared to how large it could be. They argue it can be interpreted using Cohen’s effect size criterion whereby small, medium, and large effect sizes stand at .01, .09, and .25 respectively (Cohen, 1988). Figure 1: The mediation 3. Results 3.1. Sample Characteristics 3.1.1. Response Rate
Jenni%20Shaw%20Ethesis.docx