The five-point scale version had better data quality in terms of missing data, end effects at the item and scale level, as well as higher levels of internal consistency.
However, the requirement for additional surgery for stress urinary incontinence and vaginal vault prolapse adds heterogeneity to the study population, and this together with protocol departures and missing data, undoubtedly effects the power of our study.
We compared missing data, floor effects, means, internal consistency reliability, scale score correlation, and ability to identify residents with conspicuous depression (chart diagnosis or use of antidepressant) across cognitive impairment strata.
However, EST studies consider only a shallow sampling of genomic content and include a large amount of missing data, the effect of which has never been thoroughly investigated.
Subsequently, mixed modeling has become a major area of statistical research, including work on the computation of maximum likelihood estimates, nonlinear mixed effect models, missing data in mixed effects models, and Bayesian estimation of mixed effects models (West et al. 2007).
To address the challenges of the missing data, a random effects Bayesian negative binomial model is developed for the state of Ohio.
This led to missing data, the potential effects of which we have attempted to minimise through the use of multiple imputation methods.
Items were assessed for missing data and ceiling effects, and factor analysis was used to assess the underlying structure of the items.
All noted differences in the frequency of missing data describe large effect sizes (in Cohen's effect size taxonomy [ 13]) and are statistically significant (P <.001).
However, a sensitivity analysis using 20 completed sets of multiply imputed data showed that the missing data had little effect on the overall outcome of the study.
