Luppo Kuillman

Chapter 4 96 More precisely, EA has a statistically significant effect on reporting (Effect=.9892, p =.0091) only at the higher end of the scale (see Table 3, which displays the Johnson- Neyman significance regions). These results suggest that EA does not increase the likelihood of RRC except when behavioral control is high, and that it has no effect at average or low levels. Given the significant correlation between “Age” and EA (see Table 2), we also tested the overall model by including age as a covariate. This had no impact on the effects. Table 3: Conditional effect of EAS on BP-RRC at values of the moderator BCPH (defined by Johnson-Neyman significance region(s) BCPH (raw scale scores) BCPH (two-step transformation scores) Effect se t p LLCI ULCI -2.4864 -1413.9 866.5 -1.63 .10 -3125.9 298 -2.2378 -1224,4 793.5 -1.54 .12 -2792.2 343.4 -1.9891 -1034.8 722 -1.43 .15 -2461.4 391.7 -1.7405 -845.3 652.5 -1.29 .19 -2134.5 443.9 -1.4919 -655.7 585.7 -1.12 .26 -1812.9 501.5 -1.2432 -466.2 522.6 -.89 .37 -1498.7 566.4 -.9946 -276.6 464.7 -.59 .55 -1194.8 641.6 -.7459 -87.1 414.3 -.21 .83 -905.7 731.6 -.4973 102.5 374.4 .27 .78 -637.2 842.2 -.2486 292 348.5 .83 .40 -396.6 980.6 .0000 481.6 339.9 1.41 .16 -190.1 1153.2 .2486 671.1 349.9 1.91 .06 -20.3 1362.5 ≥ .80 .2824 696.8 352.7 1.97 .05 .0 1393.7 .4973 860.7 377.1 2.28 .02 115.7 1605.7 ≥ .83.3 .7459 1050.2 417.9 2.51 .01 224.4 1876 ≥ 86.67 .9946 1239.8 469 2.64 <.01 313 2166.5 1.232 1429.3 527.4 2.71 <.01 387.2 2471.3 1.4919 1618.8 590.8 2.74 <.01 451.5 2786.2 ≥ 93.33 1.7405 1808.4 657.9 2.75 <.01 508.6 3108.3 ≥ 96.67 1.9891 1997.9 727.5 2.74 <.01 560.5 3435.5 2.2378 2187.5 799.2 2.73 <.01 608.5 3766.6 100 2.4864 2377.1 872.3 2.72 <.01 653.7 4100.5 Bold are statistically significant regions at P < 0.05