Reference intervals can be used to verify or determine a reference interval (also known as a reference range or normal range) from a sample of normal subjects from the population.
The requirements of the test are:
Data in existing Excel worksheets can be used and should be arranged in the List dataset layout. The dataset must contain a continuous scale variable containing the observations of the method.
When entering new data we recommend using New Dataset to create a new reference interval dataset.
To start the reference interval analysis:
Excel 97, 2000, 2002 & 2003: Select any cell in the range containing the dataset to analyse, then click Analyse on the Analyse-it toolbar, then click Reference Interval.
The report shows the number of observations analysed and the range of observations for the method.
Descriptive statistics, including the mean, median, SD, Skewness/Kurtosis, and a normality test are shown for assessing whether the data is normally distributed. If the data is normally distributed, allowing the parametric reference interval method to be used, the mean & median should be similar and the normality test p-value should be non-significant. Otherwise the non-parametric (or the parametric log-transformed) reference interval method should be used. If the parametric (log transformed) method is used the statistics are based on the log transformed data.
The reference interval upper and lower limits are then shown, with corresponding confidence intervals. A histogram (see below) shows the frequency of observations of the method with a normal overlay (if a parametric reference interval method is used) and the reference interval. Confidence intervals for the reference limits are shown if requested.
The normal quantile plot (see below) shows the observations of the method (X axis) against the expected normal quantile (Y axis), the number of SDs from the mean where such an observation would be expected to lie in normal distribution. When the sample is normal the points will form a straight-line, very close to the ideal normal straight-line shown in red.
If the parametric method is used to calculate the reference interval the normality test, histogram and normal quantile plot should be used to verify the data is normally distributed. If the log transformed parametric method is used the normal quantile plot and additional histogram show the distribution of the log transformed data, which again should be assessed for normality.
An existing reference interval can be verified using as few as 20 observations.
To verify a reference interval:
The goal when verifying an existing reference interval is for less than 10% of observations to lie outside the claimed reference interval. Outside claimed interval shows the actual percent of observations outside the range. The histogram (see below) shows the claimed reference interval.