Statistical methods used to compare groups on primary outcomes.

 

 

 

 

 

The importance of the problem, including theoretical or practical implications, is clearly and succinctly stated.

Method
The unit of randomization and the procedure used to generate the random assignment sequence, including details of any restriction (e.g., blocking, stratification) are fully and clearly described.
Clearly stated whether and how the sequence was concealed until experimental manipulations were assigned, including who
• Generated the assignment sequence
• Enrolled participants
• Assigned participants to groups.
Clearly reported whether participants, those administering the experimental manipulations, and those assessing the outcomes were aware of condition assignments. Provided a clear statement regarding how any masking (if it took place) was accomplished and whether and how the success of masking was evaluated.
Clearly described statistical methods used to compare groups on primary outcomes.
Clearly described statistical methods used for additional analyses, such as subgroup comparisons and adjusted analysis.
Clearly described statistical methods used for mediation or moderation analyses if conducted.

Results and Discussion
Clear descriptions of results of all inferential tests conducted, including exact p values if null hypothesis statistical testing methods were used, including the minimally sufficient set of statistics (e.g., dfs, mean square [MS] effect, MS error) needed to construct the tests.
Clear descriptions of effect-size estimates and confidence intervals on estimates that correspond to each inferential test conducted, when possible.
Clear differentiation between primary hypotheses and their tests and estimates, secondary hypotheses and their tests and estimates, and exploratory hypotheses and their tests and estimates.
Clearly described estimation problems (e.g., failure to converge, bad solution spaces) or analytic anomalies that were detected and solutions to those problems.
Clearly reported any problems with statistical assumptions and/or data distributions that could affect the validity of findings.
Provided a clear statement of support or nonsupport for all hypotheses, whether primary or secondary, including
• Distinction by primary and secondary hypotheses
• Discussion of the implications of exploratory analyses in terms of both substantive findings and error rates that may be uncontrolled.
Provided clear interpretation of the results, taking into account
• Sources of potential bias and threats to internal and statistical validity
• Imprecision of measurement protocols
• Overall number of tests or overlap among tests
• Adequacy of sample sizes and sampling validity.

The post Statistical methods used to compare groups on primary outcomes. first appeared on COMPLIANT PAPERS.

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