Finally, there is a negative, significant direct effect of on Risk Factors. Prepopulation (p < 0.001). Accuracy for Decreasing Risk Factors As above, we use the Preacher and Hayes [2008] method to test the significance of the mediators’ effects. The 90% bias-corrected confidence intervals for Stick with Last and are (-1.33, -0.60) and (-0.26, -0.02). Overall, prepopulation reduces Year Work Fast auditors’ accuracy for decreasing risks through the stick-with-last-year and work fast responses. Given that our sticking measure is derived from increasing and no change factors, the direct negative effect of prepopulation on accuracy for decreasing risks may reflect an concern about changing for these risks, consistent with auditor incremental conservatism (e.g., Hoffman and Patton [1997]). [Insert Figure 3 here] 4.1.3 for No Change Risk Factors Figure 4 illustrates the model for no change risk factors. The model fit is relatively poor. While the CFI indicates good fit (CFI = 0.97), the chi-square test is significant (χ2(1) = 5.94; 0.015) and the RMSEA of 0.20 surpasses the threshold of p = 0.10 for mediocre fit (MacCallum et al. [1996]). Despite the poor overall fit, the path coefficients in the model are significant and in the expected directions. There are positive effects of on Prepopulation Stick with Last (Link 1; < 0.001) and (Link 2; = 0.032). Also, there is a positive Year p Work Fast p effect of on (Link 3; < Stick with Last Year Accuracy for No Change Risk Factors p 0.001), and a negative effect of on Work Fast Accuracy for No Change Risk Factors (Link 4; = 0.001). Finally, there is a direct, positive effect of on p Prepopulation ( = 0.008). The Preacher and Hayes [2008] Accuracy for No Change Risk Factors p
Risk Factors. Finally, there is a negative, significant direct effect of Prepopulation on Accuracy for Decreasing Risk Factors (p < 0.001). As above, we use the Preacher and Hayes [2008] method to test the significance of the mediators’ effects. The 90% bias-corrected confidence intervals for Stick with Last Year and Work Fast are (-1.33, -0.60) and (-0.26, -0.02). Overall, prepopulation reduces auditors’ accuracy for decreasing risks through the stick-with-last-year and work fast responses. Given that our sticking measure is derived from increasing and no change factors, the direct negative effect of prepopulation on accuracy for decreasing risks may reflect an incremental concern about changing for these risks, consistent with auditor conservatism (e.g., Hoffman and Patton [1997]). [Insert Figure 3 here] 4.1.3 for No Change Risk Factors Figure 4 illustrates the model for no change risk factors. The model fit is relatively poor. While the CFI indicates good fit (CFI = 0.97), the chi-square test is significant (χ2(1) = 5.94; p = 0.015) and the RMSEA of 0.20 surpasses the threshold of 0.10 for mediocre fit (MacCallum et al. [1996]). Despite the poor overall fit, the path coefficients in the model are significant and in the expected directions. There are positive effects of Prepopulation on Stick with Last Year (Link 1; p < 0.001) and Work Fast (Link 2; p = 0.032). Also, there is a positive effect of Stick with Last Year on Accuracy for No Change Risk Factors (Link 3; p < 0.001), and a negative effect of Work Fast on Accuracy for No Change Risk Factors (Link 4; p = 0.001). Finally, there is a direct, positive effect of Prepopulation on Accuracy for No Change Risk Factors ( p = 0.008). The Preacher and Hayes [2008]