Since statistically omitting a variable that belongs in population models provides biased and inconsistent estimates, any comparative effectiveness studies in RA treatment should include severity scores.
Our findings indicate that the plate model provides biased results, especially when populations with different volume fractions are compared.
When working with spatially autocorrelated variables, OLS regression models may provide biased parameter estimates, which can lead to incorrect inferences [33].
However, some researchers argue that the random-effects model could provide biased results due to unverifiable assumptions about the data distribution [ 52].
Imputations carried out using a misspecified distribution in the imputation model can provide biased estimates of hazard ratios, especially, if the specified distribution of the phase-2 variable differs from the true one in terms of symmetry (log-normal versus normal distribution).
For example, if Model 4 is used as the generative or true model, then misspecified models (Models 1 3) are expected to provide biased estimates.
Secondly, non-linear fixed effects models has been shown to provide biased results [37], [Greene W, Han C, Schmidt P. The bias of the fixed effects estimator in nonlinear models. Unpublished Manuscript, Stern School of Business, NYU. 2002 29].
When the imputation model was misspecified, MI could provide biased estimates of hazard ratios and predictive abilities.
The OLS would, therefore, provide biased and inconsistent estimates of the model parameters due to simultaneity bias.
Climate impact models that ignore the effects of snow cover change may provide biased biodiversity projections, with potentially erratic implications for Arctic nature conservation planning.
