Ĭlick on the link below to download the program. Two cross-platform programs for inferences and interval estimation about indirect effects in mediational models. Users of the p-value calculator calculator may cite:įalk, C.F., & Biesanz, J.C. The use of normal approximations in adapting the partial posterior method to structural equation models also performed well at sample sizes above 100 in a recent simulation study (Falk & Biesanz, 2015). Furthermore, the partial posterior provides a single p-value interpretable in the same way as one would interpret the p-value from Sobel’s test. The calculator may be used for making inferences about indirect effects with multiple regression models (t-distribution computational method), or structural equation or certain multilevel models (see also FAQ about multilevel models) when degree of freedom approximations are not available (normal approximation). In Biesanz et al (2010), the partial posterior approach had high power relative to traditional approaches, power on par with the modern approaches just described, and adequately controlled Type I error rates.
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P-values are computed by the partial posterior method - a high-power alternative to Sobel’s test. Within the program, there are two computational methods - one method where sampling distributions are based in-part on posterior (and t) distributions (appropriate for regression models), and a second method where normal approximations are used in place of posterior distributions (appropriate for larger samples or methods where such normal approximations are used, such as structural equation models).
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The program is intended to be easy-to-use, does not require commercial statistical software, does not require editing of SPSS or SAS syntax, and does not require the raw data.The user only needs to input information that one would normally need to obtain anyway if performing mediational analysis using traditional methods (e.g., regression coefficients, standard errors, degrees of freedom, and t-statistics). This page provides a brief tutorial for the p-value calculator described in Falk & Biesanz (2016).