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Fitting Deming regression

Fit a Deming regression to estimate the relationship between a test method and a reference or comparative method when both variables are measured with 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 Deming Fit a Deming regression where the ratio of measurement error SD is constant throughout the measuring interval.
    Weighted Deming Fit a Deming regression where the ratio of 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. If the items are not measured in replicate, in the Variance ratio, edit box, type the ratio of the variances, or in the SD/CV X and SD/CV Y edit boxes, type the standard deviation or CV of the measurement error for each method.
    Note: The regression procedure uses all replicate measurements to estimate the precision of each method.
  8. Click Calculate.
Related concepts
Deming regression
Related tasks
Testing commutability of other materials
Checking the assumptions of the fit
Estimating the bias between methods at a decision level
Partitioning and reducing the measuring interval
Related reference
Dataset layout
Related information
CLSI. (2002). Method Comparison and Bias Estimation Using Patient Samples (EP9-A2). Clinical and Laboratory Standards Institute.
Available in Analyse-it Editions
Method Validation edition
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  •  What is Analyse-it?
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  •  Distribution
  •  Compare groups
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  •  Correlation and association
  •  Principal component analysis (PCA)
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  •  Item reliability
  •  Fit model
  •  Method comparison / Agreement
  •  Correlation coefficient
  •  Scatter plot
  •  Fit Y on X
  •  Fitting ordinary linear regression
  •  Fitting Deming regression
  •  Fitting Passing-Bablok regression
  •  Linearity
  •  Residual plot
  •  Checking the assumptions of the fit
  •  Average bias
  •  Estimating the bias between methods at a decision level
  •  Testing commutability of other materials
  •  Difference plot (Bland-Altman plot)
  •  Fit differences
  •  Plotting a difference plot and estimating the average bias
  •  Limits of agreement (LoA)
  •  Plotting the Bland-Altman limits of agreement
  •  Mountain plot (folded CDF plot)
  •  Plotting a mountain plot
  •  Partitioning and reducing the measuring interval
  •  Agreement measures for binary and semi-quantitative data
  •  Chance corrected agreement measures for binary and semi-quantitative data
  •  Agreement plot
  •  Estimating agreement between two binary or semi-quantitative methods
  •  Study design
  •  Study design for qualitative methods
  •  Measurement systems analysis (MSA)
  •  Reference interval
  •  Diagnostic performance
  •  Survival/Reliability
  •  Control charts
  •  Process capability
  •  Pareto analysis
  •  Study Designs
  •  Bibliography



Version 6.15
Published 18-Apr-2023
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