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| Table 8.2, pp. 319-320: Mediation analysis with a binary outcome using probit for smoking data |
8.2 |
8.2 .inp |
smoking.txt |
| Table 8.5, pp. 322-323: Mediation analysis with a binary outcome using logit for smoking data |
8.5 |
8.5 .inp |
smoking.txt |
| Table 8.8, pp. 326-330: Mediation analysis with a binary outcome without an intervention-mediator interaction for vaccination data |
8.8 |
8.8 .inp |
Source_8.10.09.dat |
| Table 8.9, pp. 326-330: Mediation analysis with a binary outcome with an intervention-mediator interaction for vaccination data |
8.9 |
8.9 .inp |
Source_8.10.09.dat |
| Table 8.12, pp. 334-335: Mediation analysis with a count outcome using a negative binomial model for school removal data |
8.12 |
8.12 .inp |
Data are unavailable |
| Table 8.14, p. 336: Mediation analysis with a count outcome using a negative binomial model for school removal data and computing the probability of a zero count |
8.14 |
8.14 .inp |
Data are unavailable |
| Table 8.15, p. 341: Two-part mediation model of economic stress data (Table 8.17, (1) and (2)) |
8.15 |
8.15 .inp |
estress.txt* |
| Table 8.18, p. 345: Two-part mediation model of economic stress data for continuous part of the outcome (Table 8.17, (3)) |
8.18 |
8.18 .inp |
estress.txt* |
| Table 8.17 (4), pp. 343-344: Two-part mediation model of economic stress data using log of the outcome (Table 8.17, (4)) |
8.17 (4) |
8.17 (4) .inp |
estress.txt* |
| Table 8.19, p. 346: Two-part mediation model of economic stress data using the original outcome (Table 8.17, (5)) |
8.19 |
8.19 .inp |
estress.txt* |
| Table 8.22, pp. 351-352: Hypothetical potential outcome example (binary X and M, continuous Y) |
8.22 |
8.22 .inp |
potential.txt |
| Table 8.26, pp. 355-356: Mediation analysis using probit with ordinal mediator for smoking data |
8.26 |
8.26 .inp |
smoking.txt |
| Table 8.29 (Approach 2), p. 357: Ordinal mediator using WLSMV with latent mediator |
8.29 (Approach 2) |
8.29 (Approach 2) .inp |
4cat m.txt |
| Table 8.29 (Approach 3), p. 357: Ordinal mediator using Bayes with observed mediator |
8.29 (Approach 3) |
8.29 (Approach 3) .inp |
smoking.txt |
| Table 8.29 (Approach 4), p. 357: Ordinal mediator using Bayes with latent mediator |
8.29 (Approach 4) |
8.29 (Approach 4) .inp |
4cat m.txt |
| Table 8.31, pp. 359-360: Pearl’s artificial 2 x 2 x 2 mediation example |
8.31 |
8.31 .inp |
n200expanded.txt |
| Table 8.35, pp. 364-365: Nominal mediator and binary outcome for hypothetical data |
8.35 |
8.35 .inp |
nombin9expanded.txt |
| Table 8.40, pp. 371**: Step 1 Monte Carlo simulation with a latent mediator measured by three indicators |
8.40 |
8.40 .inp |
N/A |
| Table 8.41, p. 372**: Step 2 external Monte Carlo simulation using a sum of indicators as the mediator |
8.41 |
8.41 .inp |
Generated by 8.40 |
| Table 8.43, p. 376: Aggressive behavior mediation model with a moderator and an observed mediator formed as a sum of four items |
8.43 |
8.43 .inp |
Data are unavailable |
| Table 8.44, p. 377: Aggressive behavior mediation model with a moderator and a latent mediator measured by four items |
8.44 |
8.44 .inp |
Data are unavailable |
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