(2) To evaluate the predictive role of expectations, gender, baseline muscle pain sensitivity, and intervention order on placebo response.
Univariate general linear model (GLM) analysis of posttreatment LAR detected significant by-group differences even after adjustment for age, gender, baseline values of LAR, and blood pressure.
In specification 4, sample characteristics enter the equation: participant gender (baseline: pooled estimation for men and women) and treatment in the 2000s (omitted: 1980s or 1990s).
With 20 subjects per group, there were nonsignificant differences between groups in the distribution of age, gender, baseline pain (avg. 6.1/10), radicular pain, and morphine dose (5.0 mg).
Controlling for gender, baseline levels of parent-reported oppositional and aggressive behaviors, and level of disruptiveness in the classroom, children who had received the intervention had significantly lower levels of oppositional and aggressive behaviors in the classroom.
Baseline characteristics did not differ significantly regarding age, gender, baseline creatinine, source of admission, presence of hypertension, diabetes and medication pre-ICU admission except for use of colloid starch.
The possible confounders included in the model were age, ethnicity, gender, baseline CD4 cell count, and log transformed VL.
Centralised telephone randomization by independent statisticians was used with full allocation concealment and minimization for age, gender, baseline TICS-M score and consent for MRI.
We used a linear repeated measure mixed model and adjusted for study, age, gender, baseline MMSE, baseline CDR and APOE e4 status.
Gender, baseline GCS, cranial nerve palsy and hemiparesis on presentation went forward into multivariate analysis where only hemiparesis remained significant in the final model (OR = 0.05, p = 0.04 [95% CI 0.003, 0.92]).
Interactions of ED with age, gender, baseline BMI, smoking, EI BMR, follow-up duration, and baseline waist circumference (for waist circumference change analyses only) were investigated by introducing product terms into the models.
