Fitting ordinary linear regression (method comparison)

Fit a ordinary least square regression to estimate the relationship between a test method and a reference method when the reference method is measured without error.

  1. Select a cell in the dataset.
  2. On the Analyse-it ribbon tab, in the Statistical Analyses group, click Method Comparison, and then click the fit:
    Option Description
    Ordinary Least Square Fit an ordinary regression where the test method measurement error SD is constant throughout the measuring interval.
    Weighted Least Squares Fit an ordinary regression where the test method measurement error CV is constant throughout the measuring interval.
    The analysis task pane opens.
  3. If the data are in 2 variables:
    1. In the X drop-down list, select the comparative or reference measurement procedure variable.
    2. In the Y drop-down list, select the test measurement procedure variable.
    Note: If the variables consist of replicate measurements, select the variable name that spans all the replicate columns.
  4. If the data are in 2 variables with a separate variable identifying replicates of each item:
    1. In the X drop-down list, select the comparative or reference measurement procedure variable.
    2. In the Y drop-down list, select the test measurement procedure variable.
    3. In the Item drop-down list, select the variable identifying each item.
  5. If the data are in a single variable with a separate variable matching each item and a variable identifying the method:
    1. In the Model drop-down menu, select Matched Pairs.
    2. In the Y drop-down list, select the measurement variable.
    3. In the Item drop-down list, select the item variable that identifies each item.
    4. In the Method drop-down list, select the method variable.
  6. If the items are measured in replicate, in the Replicates group, select:
    Option Description
    1st X, 1st Y Uses only the 1st X replicate and 1st Y replicate in the regression.
    Mean X, 1st Y Uses the Mean of X replicates and the 1st Y replicate in the regression.
    Mean X, Mean Y Uses the Mean of the X replicates and the Mean of the Y replicates in the regression.
    Note: All items must have the same number of replicates. Items that do not are excluded from analysis.
  7. Click Calculate.