Record linkage by the unique personal identification numbers ensured correct linkage of records.
In addition, bioinformatic tools, such as GOAT, depend heavily for their predictions on the numbers of annotated genes, their correct annotation and correct linkage to GO terms, parameters which are constantly changing.
For linkage between in-hospital death data and the Vital Statistics registry, the same combination achieved a linkage rate of 93.1% and a correct linkage rate of 98.9%.
Among the three combinations, the combination of surname, sex, and date of birth had the highest linkage rate of 88.0% and 93.1%, and the second highest correct linkage rate of 96.9% and 98.9% between the population registry and Vital Statistics registry, and between the hospital discharge data and Vital Statistics registry in 2001, respectively.
The correct linkage rate of record linkage among records that were linked between the Vital Statistics registry and population registry data for each approach is presented in Table 2.
The identification of sequence differences between homeologous genes from the same variety may in fact be the only way to specifically map homeologous genes to the correct linkage group of soybean.
Third, there was correct linkage based on a combination of 'matching variables' (consisting of maternal and newborn characteristics) that were individually matched in a meticulous manner.
For the second question, correct linkage depends on the amount of personal identifying information available on the records being linked.
Adding first name to the combination of identifiers increased the correct linkage rate no more than 1%, but at the cost of decreasing the linkage rate almost 10%.
Adding the first name to the combination of the three identifiers above increased correct linkage by less than 1%, but at the cost of lowering the linkage rate almost by 10%.
