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Study design

Method comparison study requirements and dataset layout.

Requirements

  • 2 quantitative variables.
  • A recommended minimum of at least 40 cases.
  • Each measurement in singlicate or replicate.

Paired dataset layout

Use a column for each method (Method 1, Method 2); each row has the measurement by each method for an item (Subject).

Subject (optional) Method 1 Method 2
1 120 121
2 113 118
3 167 150
4 185 181
5 122 122
… … …

Paired dataset layout with replicates

Use multiple columns for the replicates of each method (Method 1, Method 2); each row has the replicate measurements by each method for an item (Subject).

Subject (optional) Method 1 Method 2
1 120 122 121 120
2 113 110 118 119
3 167 170 150 155
4 185 188 181 180
5 122 123 122 130
… … … … …

Paired dataset layout with matched replicates

Use a column for each method (Method 1, Method 2); each row has the measurements by each methods for an item (Subject), with multiple rows for replicates of each item.

Subject Method 1 Method 2
1 120 121
1 122 120
2 113 118
2 110 119
3 167 150
3 170 155
4 185 181
4 188 180
5 122 122
5 123 130
… … …

Matched dataset layout

Use a column for the measurement variable (Measured value), a column for the method variable (Method), and a column for the item variable (Subject); each row has the measurement for a method for an item (Subject), with multiple rows for replicates of each item.

Subject Method Measured value
1 X 120
1 X 122
1 Y 121
1 Y 120
2 X 113
2 X 110
2 Y 118
2 Y 119
3 X 167
3 X 170
3 Y 150
3 Y 155
4 X 185
4 X 188
4 Y 181
4 Y 180
5 X 122
5 X 123
5 Y 122
5 Y 130
… … …
Available in Analyse-it Editions
Method Validation edition
Ultimate edition

  •  What is Analyse-it?
  •  What's new?
  •  Administrator's Guide
  •  User's Guide
  •  Statistical Reference Guide
  •  Distribution
  •  Compare groups
  •  Compare pairs
  •  Contingency tables
  •  Correlation and association
  •  Principal component analysis (PCA)
  •  Factor analysis (FA)
  •  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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Statistical analysis and method validation software for Microsoft Excel.

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