Basic↦Statistic Methodology↦Study Variables↦Definition
Was betrifft es? Warum ist das wichtig?
During study conduct different types of variables will be collected and analysed, including:
- Study outcome(s) variables: are variable that researchers want to investigate (i.e. understand, explain, or predict)
- Predictor variable: are variables potentially affecting study outcome(s) variables
- Confounding variable:: are variables that are associated with both the predictor and the outcome variables. They can therefore distort the apparent effect of an intervention. Example: a study investigates the effect of a treatment on survival. If older patients are more likely to receive the treatment, the difference in survival between treated and untreated patients may be partly due to age rather than the treatment itself
- Population variables: Are variables that describe the study population (e.g. age, gender, economic status, medical history)
Mehr
Study variables can be categorized as:
- Continuous variables (e.g. weight, lab values such as cholesterol-, blood pressure values)
- Categorical variables (e.g. such as the categorisation into bad/normal/good)
- Binary variables (e.g. expressed as binary categories such as, dead/alive, yes/no, normal/abnormal, accepted/rejected)
- Count variables (e.g. number of hospital visits)
- Time-to-event variables (e.g. time to initial cardiovascular event)
Was muss ich befolgen?
As a SP-INV, define:
- All variables that need to be collected for the study
- The timing (when), which variables (data collection) must be collected during study conduct (i.e. which variable are collect at baseline, visit 1, 2 …, end of study)
- Methods used for data collection (e.g. blood draw, participant questionnaires, interview regarding medical history, x-rays)
Consult with a data manager on how to set-up your study database (CDMA). Ensure the database complies with required laws and guidelines (e.g. audit trail, access protected).
Consult a statistician to define the methodology needed to analyse study outcome(s)/endpoints. Ensure the methodology is in accordance with the study objectives and design, while taking potential confounding variables into consideration.
Wo kann ich Hilfe anfordern?
Your local Research Support Centre↧ can assist you with experienced staff regarding this topic
Basel, Departement Klinische Forschung (DKF), dkf.unibas.ch
Lugano, Clinical Trials Unit (CTU-EOC), ctueoc.ch
Bern, Department of Clinical Research (DCR), dcr.unibe.ch
Geneva, Clinical Research Center (CRC), crc.hug.ch
Lausanne, Clinical Research Center (CRC), chuv.ch
St. Gallen, Clinical Trials Unit (CTU), h-och.ch
Zürich, Clinical Trials Center (CTC), usz.ch
References
ICH GCP E6(R3) – see in particular
- 3.1.4 Feasibility and data collection
- 3.10 Quality management
- 3.11.4.5.4c Monitoring and identifying errors in data collection
- 3.15.1c Data collection in the protocol
- 4.3.1 Procedures for the use of computerised systems
- Appendix B The clinical Study protocol – B.14.1 Specification regarding methods for data collection
- Ct Essential trial records: Document data collection
- Essential record table: Documentation of collection, processing shipment of body fluids/tissue samples
ICH Topic E9 Statistical Principals for Clinical Trials – see in particular
- 6.2 Choice of variables and data collection
- 3.6 Data capture and processing
- 5.3 Missing values and outliers
ICH Topic E8(R1) General considerations for clinical studies - see in particular
- 5.7 Study data