Transferring reference limits

Transfer a reference limit or reference interval from one method or laboratory to another.

1. Select a cell in the dataset.
2. On the Analyse-it ribbon tab, in the Statistical Analyses group, click Diagnostic, and then under the Reference Interval heading, click Transference.
   The analysis task pane opens.
3. In the Y drop-down list, select the variable.
4. Optional: To split the reference values by factors such as gender or age:
   1. On the Analyse-it ribbon tab, in the Reference Interval group, click Partition
   2. In the Factors list, select the factor variables.
   3. In the Partitions list, select a partition.

      The tasks change to the analysis options for that partition.

   4. Optional: By default, the analysis options are the same for each partition, set the specific analysis options for the partition as required.
   5. Repeat steps 4.c through 4.d for each partition.
5. In the Reference level and Reference interval edit boxes, type the reference level as a percentage and the upper/lower reference limits.
6. Optional: If transferring from another measurement procedure, under the Linear transformation heading, in the Constant and Proportional edit boxes, type the constant and proportional average bias (available from the method comparison study) to translate the old reference limits to the new measurement procedure.
7. Select the Hypothesis test check box.
8. In the Hypotheses drop-down list, select the null and alternative hypotheses.

   The default null hypothesis is that the proportion of observations in the reference interval is equal to the reference level (95% default) against the alternative hypothesis that there are more or fewer observations in the interval. CLSI EP28-A3 performs a one-sided hypothesis test that proportion inside the interval is greater than or equal to 95% against the alternative that less than 95% are inside the interval.

9. In the Significance level edit box, type the maximum probability of rejecting the null hypothesis when in fact it is true (typically 5% or 1%).

   You need at least 20 samples for a one-sided hypothesis test at the 5% significance level. More samples are required to be able to detect a significant difference for the two-sided hypothesis test, or when a smaller significance level is required.

10. If you selected partition factors, in the Partitions list, select another partition, and then repeat steps 5 through 9 for all partitions.
11. Click Calculate.