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Sample size multiple vs. single-media... |
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I tested two mediation models: one with an observed mediator and one with a latent mediator (3 indicators). X=binary, Y=continuous, 130 obs, bootstrap CI. As both mediators are related (r=0.58), it may be better to test a single model with two mediators instead of separate single-mediator models. But is this also a good idea given my limited sample size? Below the results of the different models: Model A: observed mediator M1 path a: beta=-0.24 path b: beta=-0.11 path c': beta=0.30 indirect effect: estimate=0.23 (95% CI -0.11, 1.01) direct effect: estimate=2.51 (95% CI 1.22, 4.14) Model B: latent mediator M2 path a: beta=-0.50 path b: beta=-0.53 path c': beta=0.07 indirect effect: estimate=2.21 (95% CI 0.70, 5.25) direct effect: estimate=0.55 (95% CI -2.25, 2.31) Model C: two mediators M1, M2 path a1: beta=-0.50 path b1: beta=-0.68 path a2: beta=-0.25 path b2: beta=0.25 indirect effect M1: estimate=2.85 (95% CI 0.87, 9.73) indirect effect M2: estimate=-0.52 (95% CI -3.37, 0.08) total indirect effect: 2.33 (95% CI 0.73, 7.30) direct effect: 0.43 (95% CI -3.93, 2.37) How can I decide whether model C suffers from the limited sample size? I see that the CIs for the indirect effects are wider, so the estimates are less precise. What else should I look at? |
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Sorry, I think I got the answer. I conducted a Monte Carlo simulation study to determine the power of model C. I hope I did it the correct way, but the output shows a % sig coeff of 0.88 for the indirect effect of M1 and 0.07 for M2, which shows that my analysis is not underpowered, right? - probability to reject null-hypothesis when it is (indeed) false (ind M1) is 0.88 - probability to reject null-hypothesis when it is actually true (ind M2) is 0.07, which I interpret to be low or is that not low? |
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The M1 power of .88 is fine. The M2 power of .07 is too low - I don't know why you say the hypothesis for M2 is true; the true indirect effect is not zero. |
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