![]() The index of moderated mediation and the bootstrap confidence interval produced by PROCESS is an automatic implementation of the formal test of moderated mediation described in sections 12.3 and 12.4.ģ PROCESS Model Index of Moderated Mediation 7 and 8 (a 3i b i )δ 14 (a i b 3i )δ 15 (a i b 2i )δ 58 (dichotomous W only) δ 59 (dichotomous W only) δ 74 a i c 2i Unless the moderator is a dichotomous variable, δ is set to one, yielding an index of moderated mediation that is the slope of the line relating the size of the conditional indirect effect of X on Y through M i to the moderator. PROCESS automatically produces this index of moderated mediation through each mediator in the model as well as bootstrap confidence interval for inference. An inference as to whether this index of moderated mediation is statistically different from zero is a formal test of moderation of the indirect effect by the moderator in the model. The table below formalizes how this index is constructed in terms of the model coefficients from the statistical model as diagrammed in the model templates section of this Appendix. The slope of the line relating the indirect effect to the moderator is the index of moderated mediation described in Hayes (2015). See the conceptual and statistical diagrams in the model templates document available through the web page for Introduction to Mediation, Moderation, and Conditional Process Analysis at Index of Moderated Mediation For some models, the indirect effect of X on Y through mediator M i can be expressed as a linear function of the single moderator in the model. For example, output such as Moderator value(s) defining Johnson-Neyman significance region(s) Value % below % above reflects that in the data, only 1.55% of the cases have a value of moderator less than, whereas 98.45% of the cases have a value of the moderator larger than Similarly, 44.19% of the cases have a value of moderator less than and 55.81% of the cases have a value of the moderator larger than Models 75 and 76 Two new conditional process models are added to PROCESS that specify two moderators of the X M, M Y, and/or X Y paths. Additional Johnson-Neyman Output When the Johnson-Neyman technique is used, the PROCESS output in this release includes a table at the top that provides information about theĢ percent of cases in the data with values of the moderator above ( % above ) or below ( % below ) the points of transition in significance identified using the JN method. For example, to set 12 characters for numbers with six after the decimal, use decimals=12.6. In the SAS version of PROCESS, the F should be left off the dec argument. In the dec argument, a should be larger than b. For example, decimals=f12.6 specifies twelve characters with six to the right of the decimal place. In this argument, Fa.b sets the number of characters allocated to numbers to a and the number of decimal places to display to the right of the decimal point to b. This argument is set to F10.4 by default, meaning numbers in the output will contain up to ten characters, with four of these to the right of the decimal. This can be changed with the dec argument when using the decimals option. This document was produced and uploaded to on February 27, Decimal Place Precision in Output PROCESS generates numerical output to four decimals places of resolution. All features described as additions to earlier releases can be found in later releases as well. This supplementary documentation is cumulative. 1 Supplementary PROCESS Documentation This document is an addendum to Appendix A of Introduction to Mediation, Moderation, and Conditional Process Analysis that describes options and output added to PROCESS since the printing of the book in May Whenever a new feature is added to PROCESS the version number is changed.
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