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Interaction terms for test variable × stunning group only contributed significantly (P < 0.05) when testing for the effect of TB on serum cortisol and stomach HSP, and were not included in any of the other final models.
We estimated a range of z-scores for individual performance on UDS neuropsychological tests by utilizing coefficients (βs) for demographic variables (predictors) for multivariate (MV) and univariate (UV) linear regression models provided by Weintraub and colleagues [ 2], as well as corresponding model RMSE terms for test scores of over 3,000 clinically cognitively normal subjects.
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The final regression model was used for exploratory analysis of effect modification, by inclusion of cross-product terms for testing of specific effect modification hypotheses, one at a time.
To evaluate whether the effect of falls on nursing home placement was modified by age, sex, dementia, delirium, and frailty (effect modification), we dichotomized these variables and created interaction terms for testing in the multivariate models.
The primary focus will be on the group × time interaction, for which the cluster × time interaction will be used as an error term for testing significance.
The interaction between 'soil origin' and 'replicate', where 'replicate' is nested within blocks, was used as error term for testing the soil origin effect.
One may argue that if heterogeneity is detected, then the effect for heterogeneity may be used as an error term for testing inconsistency because heterogeneity effects are nested within the effects for inconsistency.
But we favor a mixed model analysis with random trial × treatment interaction (G.S.T), because we consider it the major error term for testing the design × treatment interaction (G.T), which assesses inconsistency.
In particular, this aggravates the problem how one should choose the error term for testing the effect of individuals (i.e. the completely symmetric component of variation) when the interaction effects are localized in different (asymmetric) subspaces [ 31].
Although the interaction term for testing the dependence of the BMI CHD association on age was statistically significant, the association between BMI and CHD in the older age group could not be accurately estimated as reflected by the wide 95% CIs.
To avoid exclusion of relevant studies, we did not use keywords or indexing terms for diagnostic test accuracy.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com