Digest of document properties for data aggregation

Find a list of property keys available for data aggregation in the Dose-Response Analysis Package add-on.

Label Description Key
General: Document Title {String} Title of the Document. http://purl.org/dc/terms/title
General: Date {DateTime} Date http://stegmannsystems.com/bioassay/date
Regression Model {String} Regression Model http://www.stegmannsystems.com/bioassay/coa_model
Settings: Dose transformation {String} Dose transformation http://ssy/settings/doseTransformation
General: Assay element name {String} Assay element name http://ssy/general/assayElementName
General: Assay Element Type {String} Assay element type http://stegmannsystems.com/bioassay/elementtype
Setting: Concentration Unit {String} Concentration Unit http://ssy/settings/concentrationUnit
Settings: Response Unit {String} Response Unit http://ssy/settings/responseUnit
Settings: Preparation scheme information {String} Preparation scheme information http://ssy/settings/preparationSchemeInformation
Settings: Preparation scheme type {String} Preparation scheme type http://ssy/settings/preparationSchemeType
Number of outliers {Numeric} Number of outliers http://ssy/numberOfOutliers
Overall Test Result {String} Number of outliers http://stegmannsystems.com/bioassay/OverallTestResult
Regression: Parameter estimate upper asymptote {Numeric} Parameter estimate upper asymptote http://ssy/regression/parameterA
Regression: Standard error upper asymptote {Numeric} Standard error upper asymptote http://ssy/regression/standardErrorA
Regression: Lower confidence limit upper asymptote {Numeric} Lower confidence limit upper asymptote http://ssy/regression/lowerConfidenceLimitA
Regression: Upper confidence limit upper asymptote {Numeric} Upper confidence limit upper asymptote http://ssy/regression/upperConfidenceLimitA
Regression: Confidence interval width [%] upper asymptote {Numeric} Confidence interval width [%] upper asymptote http://ssy/regression/confidenceIntervalWidthPercentageA
Regression: Parameter estimate B parameter {Numeric} Parameter estimate B parameter http://ssy/regression/parameterB
Regression: Standard error B parameter {Numeric} Standard error B parameter http://ssy/regression/standardErrorB
Regression: Lower confidence limit B parameter {Numeric} Lower confidence limit B parameter http://ssy/regression/lowerConfidenceLimitB
Regression: Upper confidence limit B parameter {Numeric} Upper confidence limit B parameter http://ssy/regression/upperConfidenceLimitB
Regression: Confidence interval width [%] B parameter {Numeric} Confidence interval width [%] B parameter http://ssy/regression/confidenceIntervalWidthPercentageB
Regression: Parameter estimate C parameter {Numeric} Parameter estimate C parameter http://ssy/regression/parameterC
Regression: Standard error C parameter {Numeric} Standard error C parameter http://ssy/regression/standardErrorC
Regression: Lower confidence limit C parameter {Numeric} Lower confidence limit C parameter http://ssy/regression/lowerConfidenceLimitC
Regression: Upper confidence limit C parameter {Numeric} Upper confidence limit C parameter http://ssy/regression/upperConfidenceLimitC
Regression: Confidence interval width [%] C parameter {Numeric} Confidence interval width [%] C parameter http://ssy/regression/confidenceIntervalWidthPercentageC
Regression: Parameter estimate lower asymptote {Numeric} Parameter estimate lower asymptote http://ssy/regression/parameterD
Regression: Standard error lower asymptote {Numeric} Standard error lower asymptote http://ssy/regression/standardErrorD
Regression: Lower confidence limit lower asymptote {Numeric} Lower confidence limit lower asymptote http://ssy/regression/lowerConfidenceLimitD
Regression: Upper confidence limit lower asymptote {Numeric} Upper confidence limit lower asymptote http://ssy/regression/upperConfidenceLimitD
Regression: Confidence interval width [%] lower asymptote {Numeric} Confidence interval width [%] lower asymptote http://ssy/regression/confidenceIntervalWidthPercentageD
Regression: Parameter estimate asymmetry parameter {Numeric} Parameter estimate asymmetry parameter http://ssy/regression/parameterG
Regression: Standard error asymmetry parameter {Numeric} Standard error asymmetry parameter http://ssy/regression/standardErrorG
Regression: Lower confidence limit asymmetry parameter {Numeric} Lower confidence limit asymmetry parameter http://ssy/regression/lowerConfidenceLimitG
Regression: Upper confidence limit asymmetry parameter {Numeric} Upper confidence limit asymmetry parameter http://ssy/regression/upperConfidenceLimitG
Regression: Confidence interval width [%] asymmetry parameter {Numeric} Confidence interval width [%] asymmetry parameter http://ssy/regression/confidenceIntervalWidthPercentageG
Regression: Parameter estimate slope (linear models) {Numeric} Parameter estimate slope (linear models) http://ssy/regression/parameterM
Regression: Standard error slope (linear models) {Numeric} Standard error slope (linear models) http://ssy/regression/standardErrorM
Regression: Lower confidence limit slope (linear models) {Numeric} Lower confidence limit slope (linear models) http://ssy/regression/lowerConfidenceLimitM
Regression: Upper confidence limit slope (linear models) {Numeric} Upper confidence limit slope (linear models) http://ssy/regression/upperConfidenceLimitM
Regression: Confidence interval width [%] slope (linear models) {Numeric} Confidence interval width [%] slope (linear models) http://ssy/regression/confidenceIntervalWidthPercentageM
Regression: Parameter estimate intercept {Numeric} Parameter estimate intercept http://ssy/regression/parameterN
Regression: Standard error intercept {Numeric} Standard error intercept http://ssy/regression/standardErrorN
Regression: Lower confidence limit intercept {Numeric} Lower confidence limit intercept http://ssy/regression/lowerConfidenceLimitN
Regression: Upper confidence limit intercept {Numeric} Upper confidence limit intercept http://ssy/regression/upperConfidenceLimitN
Regression: Confidence interval width [%] intercept {Numeric} Confidence interval width [%] intercept http://ssy/regression/confidenceIntervalWidthPercentageN
Regression: Parameter estimate difference of asymptotes {Numeric} Parameter estimate difference of asymptotes http://ssy/regression/parameterDifferenceOfAsymptotes
Regression: Parameter estimate ratio of asymptotes {Numeric} Parameter estimate ratio of asymptotes http://ssy/regression/parameterRatioOfAsymptotes
Regression: Covariance A/D {Numeric} Covariance A/D http://ssy/regression/covarianceAD
Regression: R2 {Numeric} R2 http://ssy/regression/rSquared
Regression: R2 adjusted {Numeric} R2 adjusted http://ssy/regression/adjustedRSquared
Regression: Final tolerance {Numeric} Final tolerance http://ssy/regression/finalTolerance
ANOVA: Degrees of Freedom Residual Error {Numeric} Degrees of Freedom Residual Error http://stegmannsystems.com/bioassay/anova_reserror_df
ANOVA: Sum of Squares Residual Error {Numeric} Sum of Squares Residual Error http://stegmannsystems.com/bioassay/anova_reserror_ss
ANOVA: Mean Square Residual Error {Numeric} Mean Square Residual Error http://stegmannsystems.com/bioassay/anova_reserror_meansq
ANOVA: Degrees of Freedom Pure Error {Numeric} Degrees of Freedom Pure Error http://stegmannsystems.com/bioassay/anova_pureerror_df
ANOVA: Sum of Squares Pure Error {Numeric} Sum of Squares Pure Error http://stegmannsystems.com/bioassay/anova_pureerror_ss
ANOVA: Mean Square Pure Error {Numeric} Mean Square Pure Error http://stegmannsystems.com/bioassay/anova_pureerror_meansq
ANOVA: Degrees of Freedom Model {Numeric} Degrees of Freedom Model http://stegmannsystems.com/bioassay/anova_model_df
ANOVA: Sum of Squares Model {Numeric} Sum of Squares Model http://stegmannsystems.com/bioassay/anova_model_ss
ANOVA: Mean Square Model {Numeric} Mean Square Model http://stegmannsystems.com/bioassay/anova_model_meansq
ANOVA: Degrees of Freedom Model {Numeric} Degrees of Freedom Model http://stegmannsystems.com/bioassay/anova_total_df
ANOVA: Sum of Squares Model {Numeric} Sum of Squares Model http://stegmannsystems.com/bioassay/anova_total_ss
ANOVA: Mean Square Model {Numeric} Mean Square Model http://stegmannsystems.com/bioassay/anova_total_meansq
ANOVA: Degrees of Freedom Non-Linearity {Numeric} Degrees of Freedom Non-Linearity http://stegmannsystems.com/bioassay/anova_lof_df
ANOVA: Sum of Squares Non-Linearity {Numeric} Sum of Squares Non-Linearity http://stegmannsystems.com/bioassay/anova_lof_ss
ANOVA: Mean Square Non-Linearity {Numeric} Mean Square Non-Linearity http://stegmannsystems.com/bioassay/anova_lof_meansq
ANOVA: F-Ratio Model {Numeric} F-Ratio Model http://stegmannsystems.com/bioassay/anova_model_fratio
ANOVA: F-Ratio Non-Linearity {Numeric} F-Ratio Non-Linearity http://stegmannsystems.com/bioassay/anova_lof_fratio
Interpolation: Concentration value mean {Numeric} Concentration value mean http://ssy/interpolation/concentrationValueMean
Interpolation: Stock solution concentration value mean {Numeric} Stock solution concentration value mean http://ssy/interpolation/StockSolutionConcentrationMean
Interpolation: Source material concentration value mean {Numeric} Source material concentration value mean http://ssy/interpolation/SourceMaterialConcentrationMean
Interpolation: Minimal concentration value {Numeric} Minimal concentration value http://ssy/interpolation/minimalConcentrationValue
Interpolation: Minimal stock solution concentration value mean {Numeric} Minimal stock solution concentration value mean http://ssy/interpolation/minimalStockSolutionConcentration
Interpolation: Minimal source material concentration value mean {Numeric} Minimal source material concentration value mean http://ssy/interpolation/minimalSourceMaterialConcentration
Interpolation: Maximal concentration value {Numeric} Maximal concentration value http://ssy/interpolation/maximalConcentrationValue
Interpolation: Maximal stock solution concentration value mean {Numeric} Maximal stock solution concentration value mean http://ssy/interpolation/maximalStockSolutionConcentration
Interpolation: Maximal source material concentration value mean {Numeric} Maximal source material concentration value mean http://ssy/interpolation/maximalSourceMaterialConcentration
Interpolation: Recovery {Numeric} Recovery http://ssy/interpolation/recovery
Interpolation: Relative interpolation interval width {Numeric} Relative interpolation interval width http://ssy/interpolation/interpolationIntervalWidth_relative
Interpolation: Absolute interpolation interval width (working concentration) {Numeric} Absolute interpolation interval width (working concentration) http://ssy/interpolation/interpolationIntervalWidth_workingConcentration
Interpolation: Absolute interpolation interval width (absolute concentration) {Numeric} Absolute interpolation interval width (absolute concentration) http://ssy/interpolation/interpolationIntervalWidth_absoluteConcentration
Regression: EC20 {Numeric} EC20 http://ssy/regression/ec20
Regression: EC50 {Numeric} EC50 http://ssy/regression/ec50
Regression: EC80 {Numeric} EC80 http://ssy/regression/ec80
Regression: Response at EC20 {Numeric} Response at EC20 http://ssy/regression/responseAtEc20
Regression: Response at EC50 {Numeric} Response at EC50 http://ssy/regression/responseAtEc50
Regression: Response at EC80 {Numeric} Response at EC80 http://ssy/regression/responseAtEc80
Regression: Backcalculated response at EC20 {Numeric} Backcalculated response at EC20 http://ssy/regression/backcalculatedResponseAtEc20
Regression: Backcalculated response at EC50 {Numeric} Backcalculated response at EC50 http://ssy/regression/backcalculatedResponseAtEc50
Regression: Backcalculated response at EC80 {Numeric} Backcalculated response at EC80 http://ssy/regression/backcalculatedResponseAtEc80
Regression: Transduction Value {Numeric} Transduction Value http://ssy/regression/transductionValue