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Effect sizes were derived from standardized regression coefficients in which treatment group differences, adjusted for outcomes scores at baseline, were divided by the standard deviation of the outcomes.
Again, considering the original data ( n = 130 ), it turns out that Manufacture and distribution of gas (code 402000) is responsible for the largest deviation of the outcomes when comparing methods A-B and A-C for 2001 , 2002 2003 and 2006 (with the largest difference of −2.562% in 2002).
Where clinically useful, we estimated a benefit in units of percentage change since baseline from the standardised mean differences by estimating the pooled standard deviation from the means of the standard deviation of the outcomes in treatment and control groups for each study, and multiplying the standardised mean differences by this.
For each outcome measure in each study, the standardized mean difference (SMD; equal to the difference in the mean outcome between the groups divided by the standard deviation of the outcomes among the participants, which was reported in units of standard deviation) was calculated, which allows data measured on different scales to be merged.
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Using the standard deviation of students' mathematics scores in the sample, the coefficients were transformed into predicted standardized differences by dividing the regression coefficient by the standard deviation of the outcome variable (see Table 1).
Regression weights represented the deviation of the outcome variable for each separate group from the grand mean.
The observed standard deviation of the outcome variable is 6.5, so an effect size of 0.2 would correspond to a change in the outcome measure of 1.3.
SMD is calculated as the difference in mean outcome between groups, divided by the standard deviation of the outcome among participants.
As the standard deviation of the outcome measure was only a rough estimate, a total of 70 patients were included in both groups.
To this end, we will re-assess the standard deviation of the outcome variables and, if necessary, adjust the sample size accordingly (without breaking the randomisation code).
The standard deviation of the outcome variable was used to calculate the sample size needed for a full scale trial using PS: Power and Sample Size Calculation.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com