「Missing data and imputation」の版間の差分
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5行目: | 5行目: | ||
|+Mechanisms (assumptions) of data missing | |+Mechanisms (assumptions) of data missing | ||
|- | |- | ||
− | ! | + | !style="width:7em" rowspan="2"| |
− | ! | + | !style="witdh:4em" rowspan="2"|Abbr. |
− | ![ | + | !colspan="2"|Missing depends on/<br>Missing occurs because of |
+ | !rowspan="2"|[Example]<br>A cohort study in which participants self report their body weight every week via special app installed on their smartphones. Demographic variables are also collected. | ||
|- | |- | ||
− | !Missing not at random< | + | !style="width:7em"|missing (unobserved) value itself |
− | | | + | !style="width:7em"|other observed variable(s) |
− | + | |- | |
+ | !Missing not at random | ||
+ | !MNAR | ||
+ | |style="text-align:center"|<big>YES</big> | ||
+ | |style="text-align:center"|— | ||
| | | | ||
− | *Some participants '''intentionally | + | *Some participants '''intentionally denied to report higher body weights they didn't like''' and only reported lower body weights they accepted |
− | ** | + | *Researchers have no information why they denied to report body weights in several weeks |
+ | **Missing occurred '''because of the missing values themselves''' | ||
+ | **Researchers cannot explain/predict the missing mechanism from other observed (reported) body weights or other variables | ||
|- | |- | ||
− | !Missing at randam< | + | !Missing at randam |
− | | | + | !MAR |
− | + | |style="text-align:center"|<big>NO</big> | |
− | + | |style="text-align:center"|<big>YES</big> | |
| | | | ||
− | *15% of female participants | + | *'''15% of female participants denied to report''' their body weights after participation '''regardless of measured body weights''', but only 1% of male denied to report |
− | * | + | *Researchers can identify that female participants more likely denied to report body weights than male |
− | ** | + | **Missing occurred NOT because of body weights themselves but '''because of another variable ''sex''''' |
+ | **Missing mechanism is at random, i.e., free from missing values only inside each participant, but NOT at random, i.e., NOT free from variable ''sex'' | ||
|- | |- | ||
− | !Missing completely at random< | + | !Missing completely at random |
− | | | + | !MCAR |
− | + | |style="text-align:center"|<big>NO</big> | |
− | + | |style="text-align:center"|<big>NO</big> | |
| | | | ||
− | *A participant | + | *A participant '''moved to outside cohort area''' because of family affair and was lost to follow up |
− | ** | + | *A participant '''failed to report body weights because of malfunction of the app''' |
+ | **Missing occurred NOT because of body weights themselves NOR other variables | ||
+ | **Missing mechanism is completely at random, i.e., completely free from both of missing (unobserved) values and observed values in body weight or in other variables | ||
|} | |} |
2023年12月10日 (日) 17:18時点における最新版
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Three mechanisms (assumptions) of data missing
Abbr. | Missing depends on/ Missing occurs because of |
[Example] A cohort study in which participants self report their body weight every week via special app installed on their smartphones. Demographic variables are also collected. | ||
---|---|---|---|---|
missing (unobserved) value itself | other observed variable(s) | |||
Missing not at random | MNAR | YES | — |
|
Missing at randam | MAR | NO | YES |
|
Missing completely at random | MCAR | NO | NO |
|