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Comment: Changed label to name for grouping and groups (GitHub #217), added groupingDataset (GitHub #187), added order for operation (GitHub #200)

This example shows the definition and results for a single analysis, "Comparison of Age by Treatment", including the definitions of the grouping factor and method referenced by the analysis.   This example illustrates the use of just the groupingId attribute of the ResultGroup class to associate a result with a grouping factor that does not generate a result for each group in the grouping factor.

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Lines 1-1819:

Show the definition of the single subject grouping factors factor referenced by the analysis: the "Treatment" subject grouping factor, which has 3 groups: "Placebo", "Xanomeline Low Dose", and "Xanomeline High Dose". This grouping factor is not data-driven (dataDriven = false on lines 3line 6).

Lines 1921-2729:

Show the definition of the method referenced by the analysis, "Analysis of variance group comparison for a continuous variable", which has a single operation ("P-value").

Lines 2931-3840:

Show the definition of the analysis:

  • Lines 3234-3335: Show that this is an analysis of the AGE variable in the ADSL dataset.
  • Line 3436: Shows the reference to the "Analysis of variance group comparison for a continuous variable" method.
  • Lines 3537-3840: Show the reference to the single grouping factor, which is marked as not producing a result for each group in the grouping factor (resultsByGroup = false, shown on line 3739).
Lines 4041-4446

Show the single result for the analysis, represented as an instance of the OperationResult class containing:

  • The identifier value of the statistical operation performed, which is in the the operationId attribute.
  • In the resultGroups attribute, a reference to the only the grouping factor group associated with the result (indicated by the value of the groupingId attribute). The association to the "Treatment" grouping factor can be used as an indication that this is a treatment-related result.
  • The raw result value in the rawValue attribute, and
  • In the formattedValue attribute, the result value formatted according to the pattern specified in the resultPattern attribute of the operation referenced by the operationId value. The specified patterns are pattern is shown on row 2628.
Code Block
titleYAML Example
linenumberstrue
analysisGroupings:
- id: AnlsGrouping_01_Trt
  dataDrivenname: falseTreatment
  labelgroupingDataset: TreatmentADSL
  groupingVariable: TRT01A
  dataDriven: false
  groups:
  - id: AnlsGrouping_01_Trt_1
    labelname: Placebo
    order: 1
    ...
  - id: AnlsGrouping_01_Trt_2
    labelname: Xanomeline Low Dose
    order: 2 
    ...
  - id: AnlsGrouping_01_Trt_3
    labelname: Xanomeline High Dose
    order: 3 
    ...
methods:
- id: Mth04_ContVar_Comp_Anova
  name: Analysis of variance group comparison for a continuous variable
  operations:
  - id: Mth04_ContVar_Comp_Anova_1_pval
    name: P-value
    label: p-value
    order: 1
    resultPattern: X.XXXX
  ...
analyses:
- id: An03_01_Age_Comp_ByTrt
  name: Comparison of Age by Treatment
  version: 1
  dataset: ADSL
  variable: AGE
  methodId: Mth04_ContVar_Comp_Anova
  orderedGroupings:
  - order: 1
    resultsByGroup: false
    groupingId: AnlsGrouping_01_Trt
  results:
  - operationId: Mth04_ContVar_Comp_Anova_1_pval
    resultGroups:
    - groupingId: AnlsGrouping_01_Trt
    rawValue: '0.5934357753'
    formattedValue: '0.5934'
  ...
...

The results result for this analysis could be represented in tabular format as shown in the following table , where the groupingId and groupId values from the 2 two instances of the ResultGroup class found in the resultGroups attribute for each result are represented in separate pairs of columns ("groupingId1"/"groupId1" and "groupingId2"/"groupId2") so that each result is represented on a single row:

Dataset2
operationIdgroupingId1groupId1groupingId2groupId2rawValueformattedValue
Mth01_CatVar_Summ_ByGrp_1_nAnlsGrouping_01_TrtAnlsGrouping_01_Trt_1AnlsGrouping_02_SexAnlsGrouping_02_Sex_13333
Mth01_CatVar_Summ_ByGrp_1_nAnlsGrouping_01_TrtAnlsGrouping_01_Trt_1AnlsGrouping_02_SexAnlsGrouping_02_Sex_25353
Mth01_CatVar_Summ_ByGrp_1_nAnlsGrouping_01_TrtAnlsGrouping_01_Trt_2AnlsGrouping_02_SexAnlsGrouping_02_Sex_13434
Mth01_CatVar_Summ_ByGrp_1_nAnlsGrouping_01_TrtAnlsGrouping_01_Trt_2AnlsGrouping_02_SexAnlsGrouping_02_Sex_25050
Mth01_CatVar_Summ_ByGrp_1_nAnlsGrouping_01_TrtAnlsGrouping_01_Trt_3AnlsGrouping_02_SexAnlsGrouping_02_Sex_14444
Mth01_CatVar_Summ_ByGrp_1_nAnlsGrouping_01_TrtAnlsGrouping_01_Trt_3AnlsGrouping_02_SexAnlsGrouping_02_Sex_24040
Mth01_CatVar_Summ_ByGrp_2_pctAnlsGrouping_01_TrtAnlsGrouping_01_Trt_1AnlsGrouping_02_SexAnlsGrouping_02_Sex_138.3720930232558( 38.4)
Mth01_CatVar_Summ_ByGrp_2_pctAnlsGrouping_01_TrtAnlsGrouping_01_Trt_1AnlsGrouping_02_SexAnlsGrouping_02_Sex_261.6279069767442( 61.6)
Mth01_CatVar_Summ_ByGrp_2_pctAnlsGrouping_01_TrtAnlsGrouping_01_Trt_2AnlsGrouping_02_SexAnlsGrouping_02_Sex_140.4761904761905( 40.5)
Mth01_CatVar_Summ_ByGrp_2_pctAnlsGrouping_01_TrtAnlsGrouping_01_Trt_2AnlsGrouping_02_SexAnlsGrouping_02_Sex_259.5238095238095( 59.5)
Mth01_CatVar_Summ_ByGrp_2_pctAnlsGrouping_01_TrtAnlsGrouping_01_Trt_3AnlsGrouping_02_SexAnlsGrouping_02_Sex_152.3809523809524( 52.4)
Mth01_CatVar_Summ_ByGrp_2_pctAnlsGrouping_01_TrtAnlsGrouping_01_Trt_3AnlsGrouping_02_SexAnlsGrouping_02_Sex_247.6190476190476( 47.6)

value of the id attribute of the analysis is shown in the "analysisId" column:

Dataset2
analysisIdoperationIdgroupingIdrawValueformattedValue
An03_01_Age_Comp_ByTrtMth04_ContVar_Comp_Anova_1_pvalAnlsGrouping_01_Trt0.59343577530.5934

Alternatively, to aid readability, each of the identifier values could be used to retrieve and include additional the name or label (or any other descriptive information) from the definitions of the operations, grouping factors, and groupsoperation and grouping factor:

Dataset2
analysisIdoperationIdoperation_labelgroupingId1groupingIdgrouping_label1groupId1group_label1groupingId2grouping_label2groupId2group_label2namerawValueformattedValue
Mth01_CatVar_Summ_ByGrp_1_nnAnlsGrouping_01_TrtTreatmentAnlsGrouping_01_Trt_1PlaceboAnlsGrouping_02_SexSexAnlsGrouping_02_Sex_1Male3333
An03_01_Age_Comp_ByTrtMth04_ContVar_Comp_Anova_1_pvalp-valueMth01_CatVar_Summ_ByGrp_1_nnAnlsGrouping_01_TrtTreatmentAnlsGrouping_01_Trt_1PlaceboAnlsGrouping_02_SexSexAnlsGrouping_02_Sex_2Female5353
Mth01_CatVar_Summ_ByGrp_1_nnAnlsGrouping_01_TrtTreatmentAnlsGrouping_01_Trt_2Xanomeline Low DoseAnlsGrouping_02_SexSexAnlsGrouping_02_Sex_1Male3434
Mth01_CatVar_Summ_ByGrp_1_nnAnlsGrouping_01_TrtTreatmentAnlsGrouping_01_Trt_2Xanomeline Low DoseAnlsGrouping_02_SexSexAnlsGrouping_02_Sex_2Female5050
Mth01_CatVar_Summ_ByGrp_1_nnAnlsGrouping_01_TrtTreatmentAnlsGrouping_01_Trt_3Xanomeline High DoseAnlsGrouping_02_SexSexAnlsGrouping_02_Sex_1Male4444
Mth01_CatVar_Summ_ByGrp_1_nnAnlsGrouping_01_TrtTreatmentAnlsGrouping_01_Trt_3Xanomeline High DoseAnlsGrouping_02_SexSexAnlsGrouping_02_Sex_2Female4040
Mth01_CatVar_Summ_ByGrp_2_pct%AnlsGrouping_01_TrtTreatmentAnlsGrouping_01_Trt_1PlaceboAnlsGrouping_02_SexSexAnlsGrouping_02_Sex_1Male38.3720930232558( 38.4)
Mth01_CatVar_Summ_ByGrp_2_pct%AnlsGrouping_01_TrtTreatmentAnlsGrouping_01_Trt_1PlaceboAnlsGrouping_02_SexSexAnlsGrouping_02_Sex_2Female61.6279069767442( 61.6)
Mth01_CatVar_Summ_ByGrp_2_pct%AnlsGrouping_01_TrtTreatmentAnlsGrouping_01_Trt_2Xanomeline Low DoseAnlsGrouping_02_SexSexAnlsGrouping_02_Sex_1Male40.4761904761905( 40.5)
Mth01_CatVar_Summ_ByGrp_2_pct%AnlsGrouping_01_TrtTreatmentAnlsGrouping_01_Trt_2Xanomeline Low DoseAnlsGrouping_02_SexSexAnlsGrouping_02_Sex_2Female59.5238095238095( 59.5)
Mth01_CatVar_Summ_ByGrp_2_pct%AnlsGrouping_01_TrtTreatmentAnlsGrouping_01_Trt_3Xanomeline High DoseAnlsGrouping_02_SexSexAnlsGrouping_02_Sex_1Male52.3809523809524( 52.4)
0.59343577530.5934Mth01_CatVar_Summ_ByGrp_2_pct%AnlsGrouping_01_TrtTreatmentAnlsGrouping_01_Trt_3Xanomeline High DoseAnlsGrouping_02_SexSexAnlsGrouping_02_Sex_2Female47.6190476190476( 47.6)