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We believe that methods that can accommodate mixed study designs will become more and more important due to the increasing practice of combining data from different groups in consortia collaborations.
RCTs dominated the GM articles, while 40% of WS articles used qualitative or mixed study designs.
Another situation where power calculations for mixed study designs could be useful is pooling of individual datasets for a meta-analysis.
An example where statistical power calculations for mixed study designs are commonly required is a pharmacokinetic study nested within a clinical efficacy study.
The impact of sampling design and number of individuals in mixed study designs should therefore be evaluated prospectively during the design phase of the study to avoid enrolling too few or too many patients.
Power calculations for mixed study designs can confirm if the sample size available for the meta-analysis is sufficient to detect a clinically important effect of the covariate of interest.
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A mixed study design including primary research and secondary research was incorporated to conclude the results.
While the large sample size as well as the mixed study design approach constitutes a major strength for this study, it also has some limitations.
The reviews included here showed a variety of approaches to mixed study design; this is an area where guidelines would assist in combining all available data whilst addressing issues of different study design.
The study took place in Ethiopia using a mixed study design employing a cross sectional household survey among 15 49 year old women combined with in-depth interviews and focus group discussions.
The study used a mixed study design employing a cross sectional household survey among 15 49 year old women combined with qualitative approaches (in-depth interviews and focus group discussions (FGDs)).
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