Insufficient data pdf4/5/2023 It is therefore recommended that more sophisticated techniques such as MI should be considered in clinical research. Comparing the parameter estimates obtained by each technique to the known parameters of the complete data set revealed that MI outperformed deletion and single imputation approaches. To illustrate the relative efficacy of deletion, single imputation and multiple imputation techniques in the clinical setting, 20 cases were selected randomly from a population study investigating the cognitive sequelae of traumatic brain injury (TBI), and 8 out of 20 cases had scores on one variable deleted to simulate a missing data set. The aim of the current article is to offer a conceptual explanation of the rationale for using newer missing data techniques, with a focus on multiple imputation (MI). Despite this, researchers have been slow to utilise newer statistical approaches known to be more effective. We provide modeling and experimental data describing the dominant ion-loss mechanisms for differential mobility spectrometry (DMS). There is compelling evidence that traditional methods used to address the detrimental impacts of missing data are inadequate.
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