attrition bias


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attrition bias

A systematic error caused by the selective occurrence and biased handling of protocol deviations and losses to followup, which may lead to results that differ from a study’s true values.
 
Preventive measures
Trialists should ensure low dropout rates, high compliance rates and minimise missing outcomes data.
References in periodicals archive ?
A Wald test for nonrandom attrition is a useful starting point for models where attrition bias is of concern.
The differences that we find between the standard selection results and our full information comparison method suggest to the applied researcher that using a parametric selectivity model may not always be reliable in detecting attrition bias when no information about the outcome variable is available for attritors.
Instead of restricting ourselves to any preconceived notions of where the attrition bias might occur (for example, in the estimate of the gender effect) and estimating only those associated interaction terms, we chose to enter the interaction terms in a forward stepwise fashion.
Attrition bias is, therefore, a potential problem in this experiment that may undermine the randomization of the experimental design.
"However, we took several steps to reduce any potential attrition bias using advanced statistical techniques."
Using the AHRQ methods guide for assessment, we measured selection bias, performance bias, detection bias, attrition bias, and reporting bias.
Random sequence Allocation generation concealment (selection bias) (selection bias) Cox 1994 - + Saeed 1995 + + Scolapio 1999 + + Shemesh 1990 - + Yamamoto 1992 - + Blinding of Blinding of participants outcome and personnel asssessment (performance bias) (detection bias) Cox 1994 + + Saeed 1995 + + Scolapio 1999 + + Shemesh 1990 + + Yamamoto 1992 + + Incomplete Selective Other bais outcome data reporting (attrition bias) (reporting bais) Cox 1994 - - + Saeed 1995 + - + Scolapio 1999 - - + Shemesh 1990 - - + Yamamoto 1992 - - + Figure 4: Symptomatic relief: forest plot.
A clinical study with inappropriate study design may result in multiple biases, such as selection bias, performance bias, attrition bias, detection bias, and reporting bias [2].
Cochrane Collaboration tool for assessing risk of bias was used to assess the quality of randomized controlled trials, using the following criteria: (1) randomization sequence generation: assessment for selection bias; (2) allocation concealment: assessment of selection bias; (3) level of blinding (blinding of participants and blinding of outcome assessment): assessment for performance bias and detection bias; (4) incomplete outcome data: assessment for attrition bias; and (5) selective reporting: assessment for reporting bias.10
This is where ITT should appear--it is a measure of attrition bias (incomplete outcome data).