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This provided a baseline for assessing the linkage quality of all blocked comparisons.
We tested various string comparison methods within the same probabilistic record linkage procedure and compared the linkage quality of each setting.
If empirical research investigated the effect on linkage quality of several of these options over time given different datasets and other parameters, linkage units would be better equipped to decide on the most appropriate option for their systems.
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A technical assessment of the record linkage quality for this project determined a false positive rate (invalid links) of 0.3% and a false negative rate (missed links) of <0.1%.
Typical measures of linkage quality have used samples of links to gain an estimate of quality, often able only to estimate the number of incorrect links created, with the number of links missed essentially unknown [ 25], or have used relative measures to estimate missed links [ 26] which allows relative comparison, but not absolute quality measures.
A systematic review of probabilistic linkage accuracy identified only six articles that had complete data on summary measures of linkage quality and found the sensitivity of linkage (ie the proportion of truly matched records detected) to range from 74%to98%8% and specificity (ie the proportion of truly unmatched records detected) to range from 99 to 100% [ 14].
Additionally, most assessments of linkage quality have concentrated on the capture of a single event, such as death or cancer registration [ 5- 7].
We report on the impact of linkage quality, cohort follow-up, and multisource outcome ascertainment on the incidence proportion of reported maltreatment before age 6 and hazard ratios of selected characteristics that are often available in birth cohort linkage studies of maltreatment.
The f-measure was used as the sole measure of linkage quality.
The impact of this data omission on research outcomes is uncertain and warrants further research into the effect of linkage quality and incomplete patient pathways on research outcomes.
Measuring the effect of data cleaning in linkage is complex, as there are a multitude of parameters which can be altered that could affect the outcome of linkage quality.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com