Sentence examples for between treatment groups assuming from inspiring English sources

The targeted sample size was 150 patients (100 receiving IFX+NPX and 50 receiving PBO+NPX) for 90% power to detect a 30% difference in ASAS partial remission between treatment groups, assuming a 15% withdrawal rate.

A sample size of 91 patients was based on similar studies conducted with other RA treatments 6 17 and 0% difference between treatment groups assuming an 80% response rate.

It also had a similarly low power of 80% to detect a 50% reduction in early neonatal mortality between treatment groups, assuming a two tailed test, with α=0.05 and an early neonatal mortality rate of 15 per 1000 live births.

A sample size of 141 participants per treatment group (564 in total) was estimated to give an 80% power of detecting a 2 mmHg difference in dBP between treatment groups, assuming a standard deviation of 6 mmHg for the change from baseline and a two-sided alpha = 0.05.

This sample size, however, only had 80% power to detect a 40% reduction in low birth weight between treatment groups, assuming a two tailed test, with α=0.05 and a prevalence of low birth weight of 4.6% (prevalence observed across all treatment groups).

A sample size of 120 subjects was planned to have 90% power to detect a difference in this outcome between treatment groups, assuming a population difference of 29 min/day, SD of the 26-week values of 59 min/day, correlation between baseline and 26-week values of 0.66 (based on data from a prior study [ 8)]), an α level of 0.05, and no more than 15% losses to follow-up.

A two-group continuity corrected chi-squared test with a two-sided 5% significance level had 80% power to detect a clinically relevant difference between the treatment groups, assuming 28% in the rofecoxib group and 14% in the lumiracoxib group when the sample size is 146 patients per treatment arm.

The sample size determination in study 1 indicated that a total enrollment of 126 subjects would provide 90%% statistical power for detecting a 30%% difference in the response rate between the treatment groups, assuming a 30%% response in the vehicle control group and a two-sided type 1 error of 0.05.

With 754 patients in two groups, the study has more than 80% power to detect a difference of 1 point in SCORE function at 12 months between the two treatment groups, assuming a SD of 4.5 points.

The minimum effective sample size targeted for this study was 10 patients in each of the three groups, which would allow for 80% power to detect a clinically large size mean differences (i.e. 50% or 250 min per week of physical activity) between the music and no music treatment groups, assuming a two-tailed alpha of 0.05.

With 34 participants per group, we will have 97% power to find a significant difference between at least two of the 6 groups and 80% power to find a significant difference between Group 6 and Group 2, the treatment groups assumed to differ most in proportion of improvement.