Fig. 3 – MCAR |
1) Complete-case analysis |
Increased in volatility
with percentage of missing data. |
Increased non-linearly with the
percentage of missing data. |
|
2) Unweighted analysis |
Unbiased. |
Unbiased, except smaller CI for
Fisher’s z. |
|
3) SS-weighted analysis |
Unbiased. |
Unbiased. |
|
4 -14) Imputations in general
Random sample imputation
Bayes predictive mean matching
|
Unbiased for log response ratio, unbiased and slightly volatile for
Hedges’ d and Fisher’s z.
-
-
|
Unbiased, except for high percentages of missing data.
Unbiased, except smaller for Hedges’ d.
Increases non-linearly with the percentage of missing data.
|
Fig 4 – MAR |
1) Complete-case analysis |
Deviation increased
non-linearly with the percentage of missing data. |
Increased
non-linearly with the percentage of missing data. |
|
2) Unweighted analysis |
Unbiased |
Unbiased, except smaller CI for
Fisher’s z. |
|
3) SS-weighted analysis |
Unbiased. |
Unbiased. |
|
4 -14) Imputations in general
Random sample imputation
Bayes predictive mean matching
|
Unbiased for log response ratio, unbiased and slightly volatile for
Hedges’ d and Fisher’s z.
-
-
|
Unbiased, except for high percentages of missing data.
Unbiased, except smaller for Hedges’ d.
Increases non-linearly with the percentage of missing data.
|