Table 3.
Assumptions about the missing data mechanism
| Characteristic | Summary |
|---|---|
| Missing data assumptionsa | |
| No statement of missing data assumptions was provided | 86 (66%) |
| Data were assumed to be MAR | 35 (27%) |
| Data were assumed to be not MCAR | 6 (5%) |
| Data were assumed to be MCAR | 2 (2%) |
|
A comprehensive description of missing data assumptions was provided, e.g., using an m-DAG |
0 (0%) |
| Otherb | 1 (1%) |
| Justification provided for missing data assumptions (as % of papers that made a statement about missing data assumptions, n = 44) | |
| Yesc | 11 (25%) |
| No | 33 (75%) |
| Justified the primary analysis using missing data assumptions | |
| Yes | 31 (24%) |
| No | 98 (75%) |
| Otherd | 1 (1%) |
Abbreviations: MAR missing at random, MCAR missing completely at random, MNAR missing not at random, m-DAG missingness directed acyclic graph
aThe assumption may have been stated explicitly or made indirectly. For example, explicit statements of the MAR assumption include: “We assumed the missing at random assumption held and is reasonable”, [112] and “We imputed data using multiple imputation by chained equations under the assumption that data were missing at random” [140]. Indirect statements of the MAR assumption include “This multiple imputation approach assumes missing at random”, [93] and “We first imputed missing values using multiple imputation by chained equations, which assumes the data are missing at random conditional on the variables in the imputation model” [120]
bData assumed to be “MCAR, conditional on age and ethnicity” (n = 1)
cTwo studies justified assuming that data were MCAR; justifications included adding the questionnaire to the study after the study began (n = 1) and a lack in data registration (n = 1). Three studies justified assuming that data were not MCAR; justifications included clinicians ordering tests according to glucose level (n = 1), and describing characteristics associated with missingness (n = 2). Six studies justified assuming that data were MAR; justifications included describing characteristics associated with missingness and/or conducting formal hypothesis tests (n = 4), examining the missingness pattern (n = 1) and because children moved homes and/or were impossible to locate (n = 1)
dJustified MI to improve efficiency in the estimators