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Indirect Effects and the Test of Mediation

Indirect Effects and the Test of Mediation. Example Objective: Compare Path Models to Multiple Regression and Illustrate Concepts of Indirect Effects and Mediation. Example Data: Community Response to Wildfire in California Shrublands. View of Data in KeeleyDataCov.xls.

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Indirect Effects and the Test of Mediation

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  1. Indirect Effects and the Test of Mediation

  2. Example Objective: Compare Path Models to Multiple Regression and Illustrate Concepts of Indirect Effects and Mediation

  3. Example Data: Community Response to Wildfire in California Shrublands

  4. View of Data in KeeleyDataCov.xls rich = plant species richness in 1000 m2 plots tcov = total cover of all species coastran = distance from the coast (transformed) s_age = age of the stand that burned, in years fidx = fire severity index hetero = index of within-plot heterogeneity optabio = index of optimum abiotic conditions (low N, high sand, high rock)

  5. Bivariate Patterns.

  6. Indirect Effects as Causal Tests: Step 1 How do we interpret the observation that plant cover the year after the fires is a function of the age of the stand that burned? Perhaps older stands burn hotter and produce more severe fires.

  7. Indirect Effects as Causal Tests: Step 2 Evaluating the possibility that effect of stand age on plant cover following fire is because older stands burn hotter.

  8. Setting Amos "Analysis Properties" for this example.

  9. standardized path coefficients R-square Indirect Effects as Causal Tests: Step 3 Testing the hypothesis of mediation - results. Chi-square less than 3.84 indicates we pass the test for concluding that fire severity mediates the effect of stand age on vegetation recovery.

  10. Calculating the Magnitude of the Indirect Effect. Standardized indirect effect of s_age on tcov = 0.45 x -0.44 = -0.198.

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