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| Table 10.1 (Part 1), pp. 441-442: Sample statistics estimated by multiple imputation followed by ML |
10.1 (Part 1) |
10.1 (Part 1) .inp |
Data are unavailable |
| Table 10.1 (Part 2), pp. 441-442: Sample statistics estimated by Bayes using an unrestricted model |
10.1 (Part 2) |
10.1 (Part 2) .inp |
Data are unavailable |
| Table 10.4, p. 451: Step 1 Monte Carlo simulation assuming MAR: Generating the data |
10.4 |
10.4 .inp |
N/A |
| Table 10.5, pp. 452-453: Step 2 external Monte Carlo simulation assuming MAR: Analyzing the data including the missing data indicator |
10.5 |
10.5 .inp |
Generated by 10.4 |
| Table 10.7, p. 454: Step 2 external Monte Carlo simulation assuming MAR: Analyzing the data excluding the missing data indicator |
10.7 |
10.7 .inp |
Generated by 10.4 |
| Table 10.9, p. 455: Step 2 external Monte Carlo simulation assuming MAR: Analyzing the data excluding the missing data indicator and using listwise |
10.9 |
10.9 .inp |
Generated by 10.4 |
| Table 10.11, p.459: Monte Carlo simulation with missingness due to a missing data correlate z |
10.11 |
10.11 .inp |
N/A |
| Table 10.12, p.461: Step 2 external Monte Carlo simulation including the missing data correlate z as a covariate |
10.12 |
10.12 .inp |
Generated by 10.11 |
| Table 10.13, p. 461: Step 2 external Monte Carlo simulation excluding the missing data correlate z |
10.13 |
10.13 .inp |
Generated by 10.11 |
| Table 10.14, pp. 462-463: Step 2 external Monte Carlo simulation excluding the missing data correlate z and using listwise |
10.14 |
10.14 .inp |
Generated by 10.11 |
| Table 10.15, pp. 462-463: Step 2 external Monte Carlo simulation using AUXILIARY = z(M) |
10.15 |
10.15 .inp |
Generated by 10.4 |
| Table 10.17, p. 467: Monte Carlo simulation under NMAR with missingness predicted by a variable with missing data: Generating the data |
10.17 |
10.17 .inp |
N/A |
| Table 10.18, p. 468: Step 2 external Monte Carlo simulation under NMAR: Analyzing the data including the missing data indicator using selection modeling |
10.18 |
10.18 .inp |
Generated by 10.17 |
| Table 10.19, p. 468: Step 2 external Monte Carlo simulation under NMAR: ML assuming MAR |
10.19 |
10.19 .inp |
Generated by 10.17 |
| Table 10.20, p. 469: Step 2 external Monte Carlo simulation under NMAR: Listwise |
10.20 |
10.20 .inp |
Generated by 10.17 |
| Table 10.22, p. 471: Step 2 external Monte Carlo simulation under MAR: Selection modeling |
10.22 |
10.22 .inp |
Generated by 10.4 |
| Table 10.24, p. 473: Aggression mediation modeling with multiple imputation of agg1 (approach 9 in Table 10.25) |
10.24 |
10.24 .inp |
Data are unavailable |
| Table 10.25 (Approach 1), p. 474: Listwise (n=250) |
10.25 (Approach 1) |
10.25 (Approach 1) .inp |
Data are unavailable |
| Table 10.25 (Approach 2), p. 474: ML assuming MAR (n=392) |
10.25 (Approach 2) |
10.25 (Approach 2) .inp |
Data are unavailable |
| Table 10.25 (Approach 3), p. 474: ML assuming MAR with black as missing data correlate (n=392) |
10.25 (Approach 3) |
10.25 (Approach 3) .inp |
Data are unavailable |
| Table 10.25 (Approach 4), p. 474: ML on multiple imputation of agg5 (n=392) |
10.25 (Approach 4) |
10.25 (Approach 4) .inp |
Data are unavailable |
| Table 10.25 (Approach 5), p. 474: Bayes (n=392) |
10.25 (Approach 5) |
10.25 (Approach 5) .inp |
Data are unavailable |
| Table 10.25 (Approach 6), p. 474: Selection modeling, missing regressed on agg5 (n=392) |
10.25 (Approach 6) |
10.25 (Approach 6) .inp |
Data are unavailable |
| Table 10.25 (Approach 7), p. 474: ML assuming MAR (n=441) |
10.25 (Approach 7) |
10.25 (Approach 7) .inp |
Data are unavailable |
| Table 10.25 (Approach 8), p. 474: ML assuming MAR with black as missing data correlate (n=441) |
10.25 (Approach 8) |
10.25 (Approach 8) .inp |
Data are unavailable |
| Table 10.25 (Approach 9), p. 474: ML on multiple imputation of agg1 (n=441) |
10.25 (Approach 9) |
10.25 (Approach 9) .inp |
Data are unavailable |
| Table 10.25 (Approach 10), p. 474: Bayes (n=441) |
10.25 (Approach 10) |
10.25 (Approach 10) .inp |
Data are unavailable |
| Table 10.25 (Approach 11), p. 474: Selection modeling, missing regressed on agg5 (n=441) |
10.25 (Approach 11) |
10.25 (Approach 11) .inp |
Data are unavailable |
| Table 10.25 (Approach 12), p. 474: ML assuming MAR (n=441) |
10.25 (Approach 12) |
10.25 (Approach 12) .inp |
Data are unavailable |
| Table 10.25 (Approach 13), p. 474: ML on multiple imputation of agg1 (n=441) |
10.25 (Approach 13) |
10.25 (Approach 13) .inp |
Data are unavailable |
| Table 10.25 (Approach 14), p. 474: Bayes (n=441) |
10.25 (Approach 14) |
10.25 (Approach 14_ .inp |
Data are unavailable |
| Table 10.25 (Approach 15), p. 474: Selection modeling, missing regressed on agg5 (n=441) |
10.25 (Approach 15) |
10.25 (Approach 15) .inp |
Data are unavailable |
| Table 10.25 (Approach 16), p. 474: Selection modeling, missing regressed on agg5 and black (n=441) |
10.25 (Approach 16) |
10.25 (Approach 16) .inp |
Data are unavailable |
| Table 10.26, p. 477: Step 1 Monte Carlo simulation generating MAR missing data, n=200, 40% missing |
10.26 |
10.26 .inp |
N/A |
| Table 10.27, p. 478: Step 2 external Monte Carlo simulation: MLR assuming normality |
10.27 |
10.27 .inp |
Generated by 10.26 |
| Table 10.28, p. 479: Step 2 external Monte Carlo simulation: Bayes assuming normality |
10.28 |
10.28 .inp |
Generated by 10.26 |
| Table 10.29, p. 479: Step 2 external Monte Carlo simulation: Bayes treating binary x’s as binary |
10.29 |
10.29 .inp |
Generated by 10.26 |
| Table 10.30, p. 481: Step 1 Monte Carlo simulation generating NMAR missing data, n=200, 40% missing |
10.30 |
10.30 .inp |
N/A |
| Table 10.31, p. 481: Step 2 external Monte Carlo simulation under NMAR: MLR assuming normality |
10.31 |
10.31 .inp |
Generated by 10.30 |
| Table 10.32, p. 482: Step 2 external Monte Carlo simulation under NMAR: Bayes assuming normality |
10.32 |
10.32 .inp |
Generated by 10.30 |
| Table 10.33, p. 482: Step 2 external Monte Carlo simulation under NMAR: Bayes treating binary x’s as binary |
10.33 |
10.33 .inp |
Generated by 10.30 |
General Description