M–R

Select the 'yes' option from the drop-down list to use the development assays to develop margins.

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This section allows you to select the tests for which you want to develop margins. Expand the node to add or view information.

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Model parameters are simulated and tested until one of the following occurs:

• The number of valid configurations found reaches the number set in Max configurations.
• The number of simulations performed reaches the number set in Max simulations.

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Model parameters are simulated and tested until one of the following occurs:

• The number of valid configurations found reaches the number set in Max configurations.
• The number of simulations performed reaches the number set in Max simulations.

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Enter the Maximal response to be used to calculate the transduction unit.

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Select the model you require for visualization.

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Uses the 3-parameter logistic-fit regression model with fixed lower asymptote. Select a different model from the drop-down list if you require.

The model is defined by the following equation:

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Uses the 3-parameter logistic-fit regression model with fixed upper asymptote. Select a different model from the drop-down list if you require.

The model is defined by the following equation:

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Uses the 4-parameter logistic-fit regression model. Select a different model from the drop-down list if you require.

The model is defined by the following equation:

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Uses the 5-parameter logistic-fit regression model. Select a different model from the drop-down list if you require.

The model is defined by the following equation:

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Uses the Linear regression model. Select a different model from the drop-down list if you require.

The model is defined by the following equation:

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This section allows you to define a Multi-dose scheme. Multi-dose schemes contain settings on dilution sequence, Number of replicates, and Predilution factors.

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Enter the factor to be multiplied with the standard deviation.

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Enter a name for this column.

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Enter a name for this document.

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Enter a name for the Control sample.

Examples: 'Assay control', 'Control 3', 'Ctr'

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Enter a name for the Data selection scheme.

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Enter a name for this document.

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Enter a name for the Multi-dose scheme.

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Enter a name for this Report group.

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Enter a name for the Single-dose scheme.

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Enter a name for the Standard sample.

Examples: 'Standard', 'Std', 'Reference standard'

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Enter a name for the Test sample.

Examples: 'Preparation 1', 'Unknown 3', 'Test 2'

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Enter a name for the test strategy.

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Performs analysis without response adjustment.

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Does not perform a logarithmic transformation of the dose values at the beginning of the calculation.

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No dose transformation will be performed at the start of the calculation.

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Performs analysis without response normalization.

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Performs No outlier detection for assay elements (samples) that reference this Data selection scheme. Select a different option from the drop-down list if you require outlier detection.

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Performs analysis without response transformation.

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Normalize your response values by Fixed value or by Assay element.

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Example: Use this feature to divide by the mean absorbance of maximum binding wells.

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Enter a number to specify how many replicates the referencing assay elements (samples) require for each dose step.

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Enter a number to specify how many dose steps this sequence requires.

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Enter the amount of source material to be used.

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Enter the liquid volume in which the source material is to be dissolved.

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Enter the quantity of analyte contained in one unit of source material.

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Enter the concentration of the stock solution.

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This section allows you to modify the data table that displays observation data in the Observations editor.

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Displays the Observation group ID.

When you create an assay element, a unique Observation group ID is automatically assigned. Since Observation group IDs are required to be unique within assays, we do not recommend to change them manually.

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Select how you want to obtain observation data.

The following options are available from the drop-down list:

• User input: Enter data manually.
• Aggregation: Specify document references to aggregate data from documents.
• Import: Not supported.

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Select how you want to obtain observation data. The following options are available:

• User input: Enter data manually.
• Aggregation: Specify document references to aggregate data from documents.
• Import: Not supported.

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Select whether outlier testing is to be performed Before response data processing or After response data processing.

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This section allows you to provide information on an operator.

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To add an Operator name or reference: Select the required option from the drop-down list, and enter the name or reference.

To assign a role to the operator: Add the Role element from the Creatable elements pane, and enter the required role.

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Enter the name of the operator.

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Select an operator document.

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Select how detected outliers are to be processed.

The following options are available from the drop-down list:

• Remove outlier: Outlying response values are excluded from regression.
• Remove outlier step: All response values that belong to the step and assay element combinations where outliers occur are excluded from regression.
• Replace outlier: Outlying response values are replaced by the arithmetic mean of the valid response values of the corresponding step and assay element combination.
• Mark outlier: Outlying response values are included in regression, but they are marked as outliers in plots and reports.

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Enter the significance level (alpha) for the p-value of the test. A common value is 0.05.

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Select the Parameter to be examined by this test.

Please consult the help page of the test for additional information.

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Enter the percentile for which you want to test.

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Enter the (response) Percentile of which the concentration is to be interpolated.

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Select the plate whose response values are to be modified during response data processing.

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Enter a single predilution factor. The calculation uses the reciprocal value (1 / Predilution factor).

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This section allows you to enter the Predilution factors required to calculate the first dose of the dilution sequence. You can define multiple predilution factors.

To add a predilution factor: Double-click Predilution factor in the Creatable elements pane.

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This section allows you to enter multiple predilution factors.

To add a predilution factor: Double-click Predilution factor in the Creatable elements pane.

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Assign a Preparation scheme to this assay element.

Preparation schemes define dilution sequences (in multi-dose schemes), Number of replicates per sequence step, and Predilution factors of assay elements.

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This section allows you to set up multiple Preparation schemes to define doses and dimensions of your treatments.

Expand the node to add or view information.

Dose-response analysis documents provide two types of preparation schemes:

• Multi-dose schemes: Define samples (assay elements) with a known dose sequence. The calculation performs a regression for each sample (assay element) that has a Multi-dose preparation scheme.
• Single-dose schemes: Define samples (assay elements) with an unknown dose. The calculation performs a regression for the Standard sample and uses the resulting regression curve or line to interpolate a dose value for each single-dose sample.

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Define a section property filter to be used for data aggregation.

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Select a Property key to identify the data to be aggregated.

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Currently, no information available.

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Select a Property scope from the drop-down list.

The following options are available to specify the source of the aggregated property:

• Document
• Section

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Uses a partial dose range for concentration calculation that begins at Step start and ends at Step stop.

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Use this test for the following models:

• 4-parameter logistic fit
• 4-parameter logistic fit with included blanks
• 5-parameter logistic fit

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This section allows you to provide information on a reagent.

Expand the node to add or view information.

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Enter the reagent batch or lot number, a combination of numbers, letters, and/or symbols. It identifies a batch (or lot), which allows you to infer the production and distribution history.

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Enter the class of the reagent such as the drug class.

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Enter a description of the reagent. Tip: You can enter multiline text.

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Enter information to identify the reagent.

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Enter a name for the reagent. Tip: You can enter a reference to a reagent document instead. Select the Reagent reference option from the drop-down list.

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Select a reagent document. Tip: You can enter a reagent name instead. Select the Reagent name option from the drop-down list.

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Enter the reagent sub-batch or sub-lot number, a combination of numbers, letters, and/or symbols. It identifies a sub-batch (or sub-lot), which allows you to infer the production and distribution history.

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Enter the variant of the reagent.

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Set Recursive to 'yes' if you want to repeat the test (with previously found outliers excluded) as long as outliers are detected and the number of values is greater than or equal to 3.

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Enable this feature if you want to fit the regression by using the mean of the response values for each sequence step rather than individual response values.

Expand the node to add or view information.

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Select a Report group from the drop-down list.

Report groups allow you to combine assay elements for displaying them in overlay plots, aggregating their statistics, and printing them next to each other in reports.

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Define a Report group. You can then reference this group in assay elements to combine them for calculating an average, performing regression analysis, displaying them in overlay plots, and printing them next to each other in reports.

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This section allows you to set up multiple Report groups. You can then assign assay elements to these groups to display them in overlay plots, to aggregate their statistics, and to print them next to each other in reports.

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This section allows you to define how your response data is to be processed prior to fitting the regression model. You set up a sequence of response data processing steps.

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Four types of response data processing are available:

• Adjustment
• Normalization
• Transformation
• Replicate averaging

By default, four response data processing steps are displayed - one of each type. By default, all four steps are disabled. Enable the steps you require.

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Enter a decimal number to be used as greatest value of the y-axis in simulation plots.

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Enter a decimal number to be used as least value of the y-axis in simulation plots.

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Defines the least and greatest value of the y-axis used for simulation plots.

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Specify an upper and/ or lower limit for the response values to be included.

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Enter the role of the operator.

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Select the sort order you want to apply to the data rows.

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Select the sort order you want to apply to the data rows.

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