Please can you assist with devising a power calculation, also if we statistical support for a research project, how much do you charge?
The study is RCT looking at vaginal laser vs sham for post-menopausal women with recurrent UTI.
This is what I have currently written – is this nonsense?
This is a proof-of-concept trail but has been modelled against previous published studies which has used the same intervention. Dryness and dyspareunia have previously been used as the primary outcomes with previously published data on lasers. The sample size estimation was conducted using mean improvement of 10-cm VAS for dryness and dyspareunia derived from two previously published studies (16, 19). The clinically acceptable margin was determined at 10% (1 cm). Hence, a sample size of 40 patients per group will establish a non-inferiority trial at a power of 80% and level of significance 0.05. Considering an expected average drop-out rate 10%, 44 participants will be required per group and 88 participants in total.
As this is proof-of concept trial half of this participants will be recruited, 22 participants per group, 44 participants in total.
Interim analysis will be made following the 6-month follow-up using the primary outcome “To determine and compare the incidence of symptomatic antibiotic treated UTI during at 6-month follow-up”, the sample size will then be recalculated and adjusted accordingly. Should it exceed total 100 participants further ethical approval will be obtained.
The sample size was calculated by an independent statistician using the formula for non-inferiority trials for continuous variables provided in the article of Zhong B (26).
This is a relative new area with no completed studies yet looking at change of UTI incidence as the primary outcome – Here is an abstract reporting interim analysis can we use this?
Our null-hypothesis is that UTI incidence will increase with laser treatment
Target improvement <1 UTI in 6 months.
14 freelances font une offre moyenne de 135 £ pour ce travail
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Hi, I would suggest you to read about OC Curves and Data Distributions before calculating the sample size because Sample is a picture of Population you cannot risk that, I would suggest to use 2 to 3 methods and take m Plus
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