-What do we currently know about the research topic?
-What type of study are you conducting (descriptive, analytical, comparative, interventional, observational, etc.)?
-What variables will you use, and which subjects will be exposed to which variables?
-How often and when will the data be collected?
-How can you control all the factors that might affect prediction models and outcomes?
-Do you have to adjust design because of some feasibility issues? If so, what factors?
實驗對象
(selection criteria and methods)
-Ethical considerations (all animal or human studies must discuss factors like ethics committee approval of research protocol, informed consent of human subjects, etc.
-Study setting (time, place, etc.), where applicable.
-For living subjects (humans and animals): demographic and clinical conditions, gender, weight, species, age, special characteristics, living conditions, etc.
-Any preparations of subjects made before starting experiments.
-Sampling method, including target population, sampling frame, instruments used, and any stratification, clustering or weighting.
-Recruitment method and its effectiveness, including profiles of any subjects that refused (where applicable).
-For comparative studies: group allocation and randomization procedures.
-Follow-up procedures for longitudinal studies.
資料蒐集
(criteria and methods)
-Variables measured (identify only the key predictors and all outcomes of those variables).
-Methods and instruments used to collect data (include information such as an instrument’s manufacturer and model, calibration procedures, and other information necessary to allow others to reproduce your experimental results).
-Bias controls (e.g., blinding procedures).
資料分析
-Descriptive statistics (e.g., means, medians, standard deviations, etc.).
-Inferential methods (include confidence intervals, hypothetical testing methods, and regression models or other modeling procedures used).
-Methods used to address confounding observational studies.
-Interim analysis methods.
-Adjustments made to sampling methods and weighting procedures.
-Missing data.
-Sample size.
-Power determination.
-Software used.
