Abstract
In any research study, there is an underlying research process that should begin with a clear articulation of the study’s goal. The study’s goal drives this process; it determines many study features including the estimand of interest, the analytic approaches that can be used to estimate it, and which coefficients, if any, should be interpreted. “Misalignment” can occur in this process when analytic approaches and/or interpretations do not match the study’s goal; misalignment is potentially more likely to arise when study goals are ambiguously framed. This study documented misalignment in the observational epidemiologic literature and explored how the framing of study goals contributes to its occurrence. The following misalignments were examined: 1) use of an inappropriate variable selection approach for the goal (a “goal-methods” misalignment) and 2) interpretation of coefficients of variables for which causal considerations were not made (e.g., Table 2 Fallacy, a “goal-interpretation” misalignment). A random sample of 100 articles published 2014-2018 in the top 5 general epidemiology journals were reviewed. Most reviewed studies were causal, with either explicitly stated (13/103, 13%) or associationally-framed (71/103, 69%) aims. Full alignment of goal-methods-interpretations was infrequent (9/103, 9%), although clearly causal studies (5/13, 38%) were more often fully aligned than seemingly causal ones (3/71, 4%). Goal-methods misalignments were common (34/103, 33%), but most frequently, methods were insufficiently reported to draw conclusions (47/103, 46%). Goal-interpretations misalignments occurred in 31% (32/103) of studies and occurred less often when the methods were aligned (2/103, 2%) compared with when the methods were misaligned (13/103, 13%).
Variable selection with missing data in both covariates and outcomes: Imputation and machine learning
