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The practical guide behind this tool: when it applies, how to read the output, and the traps that make it say the wrong thing.
Standard-library analysis: does a predictor relate to an outcome through a third variable, or does its relationship with the outcome depend on one? Map a predictor, an outcome, and either a mediator or a moderator (plus optional covariates). Mediation splits the total association into the direct path and the indirect path that runs through the mediator: the a, b, c and c-prime paths with standard errors, the indirect effect a×b with a percentile bootstrap confidence interval, the proportion mediated where it is interpretable, the Sobel test reported alongside with its weakness stated, and the whole path diagram as a table. Moderation fits the interaction model and reports the conditional slope of the predictor at low, mean and high values of the moderator (or within each moderator level). Every narrative states, in your own column names, the assumption set a causal reading would rest on.
Interactive table visualization
Interactive bar visualization
Interactive histogram visualization
Interactive table visualization
Interactive table visualization
Plain-English reading of the results and what to do next.
Test whether a predictor relates to an outcome through an intermediate step, with a bootstrap interval on the indirect path
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MCP Analytics. Mediation & Moderation Analysis. Free tool. https://mcpanalytics.ai/free/standard_mediation. Accessed [date you used it].
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