Sentence examples for baseline differences were estimated from inspiring English sources

Daytime sleepiness measurements, overnight polysomnography and blood pressure results among groups adjusting for baseline differences were estimated by linear regression models.

Baseline patient demographics and clinical and disease characteristics were compared between the two drug-exposure cohorts, and standardized differences were estimated.

A difference-in-difference was estimated between baseline (3 years before merger approval) and each subsequent year up to 4 years post-merger, controlling for work environment, drivers of job satisfaction, data year, type of hospital and occupation group.

There were some differences in baseline characteristics between the intervention and the control and these were included in an analysis which explored how the estimates of the treatment effect changed when baseline differences were controlled for.

Three baseline differences were found between groups.

If any significant baseline differences are identified, intervention effects will be estimated using multivariable analysis adjusted for baseline variables as well as stratified analysis using propensity scores.

Differences in baseline variables were estimated by use of absolute differences (DIF) with 95% confidence intervals (CI) for categorical variables or Wilcoxon rank-sum test for continuous variables.

Differences in baseline variables were estimated by use of absolute differences and 95% confidence intervals (categorical variables) or the Wilcoxon rank-sum test (continuous variables).

Scenario analysis was conducted to explore the effects of changing the way QALYs were estimated and adjusting for baseline difference in the population.

The expected differences in the person's level of SRH at diagnosis were estimated using baseline information.

Two-year health care use and costs of SS participants and control subjects were estimated in regressions adjusting for baseline differences.