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Does analysis using last observation carried forward introduce bias in dementia research?
The use of last observation carried forward in analyses can introduce bias that may exaggerate the effectiveness of drugs. Last observation carried forward likely favours more toxic drugs such as cholinesterase inhibitors over less toxic drugs such as memantine.
Why use last observation carried forward?
If a person drops out of a study before it ends, then his or her last observed score on the dependent variable is used for all subsequent (i.e., missing) observation points. LOCF is used to maintain the sample size and to reduce the bias caused by the attrition of participants in a study.
What is last observation carried forward method?
Last Observation Carried Forward (LOCF) is a common statistical approach to the analysis of longitudinal repeated measures data where some follow-up observations may be missing.
What carry forward observation worst?
WOCF (Worst observation carried forward): this approach is the most conservative comparing to LOCF and BOCF. This technique has been used in analgesia drug as well as the trials with laboratory results as endpoint. For example, WOCF technique is mentioned in FDA Summary on Durolane.
What is LOCF in SAS?
The last observation carried forward (LOCF) method is a common way for imputing data with dropouts in clinical trial study. The last non-missing observed value is used to fill in missing values at a later time point.
Is the Last Observation Carried Forward ( LOCF ) method appropriate?
The use of the last observation carried forward (LOCF) method for imputing missing outcome data in randomized clinical trials has been much criticized and its shortcomings are well understood. However, only recently have published studies widely started using more appropriate imputation methods.
Can a meta-analysis be biased by LOCF?
However, only recently have published studies widely started using more appropriate imputation methods. Consequently, meta-analyses often include several studies reporting their results according to LOCF. The results from such meta-analyses are potentially biased and overprecise.
What’s the difference between LOCF and observed data?
LOCF uses the last value observed before dropout, regardless of when it occurred. (1) The FDA has traditionally viewed LOCF as the preferred method of analysis, considering it likely (but not certain) to be conservative and clearly better than using observed cases, where only the data observed are used.
Is the LOCF analysis valid in medical field?
An LOCF analysis is valid for estimating the treatment effect under very restrictive and usually unrealistic assumptions. In medical fields, disease progression is a definite feature and patients are expected to deteriorate over time, eg, in dementia, 4 assuming no progression after dropout is expected to give biased results.