For instance, Solow (1987) demonstrates convincingly that compositional changes in output can lead to incorrect substitution estimates in studies using aggregate data.
The hd-PS automatically defines and selects variables for inclusion in the PS estimating model to adjust treatment effect estimates in studies using automated healthcare data [ 16, 18].
Our prevalence ratio estimates for the cancer of all sites among men and women were comparable to relative risk estimates in studies on cancer incidence (3, 9).
Use of colon cancer controls may provide valid exposure estimates in studies of many occupational risk factors for cancer, but not for studies on exposure related to farming.
The incidence of adhesive small bowel obstruction was comparable to the presented estimates in studies with low and intermediate risk of bias.
The use of inadequate controls or insufficient adjustment for confounders like age and socioeconomic status seemingly diluted the effect estimates in studies with moderate quality.
As noted by Neale et al. (2005), measurement non-invariance on item level between zygosity groups may impact the estimates in studies based on sum scores.
An unresolved issue is the impact of uncontrolled confounding and measurement error on the relative risk estimates in studies of lead and clinical cardiovascular end points.
Intermediate factors were estimated in Study III with 4307, 7214, and 5096 for STP-C-Ag-1, STP-C-Ag-2, and STP-C-Ag-3, respectively.
Parameter values related to pathogen transmission are mostly from laboratory studies, while many demographic parameters are estimated in field studies.
