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RESULT: { result: <OVERALL_RESULT_DATA>, (dataRows: <ROW_RESULT_DATA>*|, subgroups: [{ result: <SUBGROUP_RESULT_DATA> dataRows: <ROW_RESULT_DATA>* }]) } RESULT_DATA: { estimable: true|false, estimable logScale: true|false, mean: 0.0, (NOTE: ON THE SCALE OF ANALYSIS, SO LOG SCALE FOR LOG SCALE OUTCOMES) se: 0.0, ciStart: 0.0, (NOTE: ON THE SCALE OF ANALYSIS, SO LOG SCALE FOR LOG SCALE OUTCOMES) ciEnd: 0.0, (NOTE: ON THE SCALE OF ANALYSIS, SO LOG SCALE FOR LOG SCALE OUTCOMES) weight: 0.0 } ROW_RESULT_DATA extends RESULT_DATA: { id: "<studyDataRowId>", (NOTE: this is not included in the meta-analysis API output, but is added by ReviewDB.) studyId, applicability: "SUBGROUP_ONLY" | "OVERALL_ONLY" | "SUBGROUP_AND_OVERALL", (notIncludedInTotal: true)? (NOTE: used to indicate that a subgroup row is not included in the calculation of the total) } SUBGROUP_RESULT_DATA extends RESULT_DATA: { id: "<subgroupAnalysisId>", (NOTE: this is not included in the meta-analysis API output, but is added by ReviewDB.) heterogeneity: { chiSquared: 0.0, degreesOfFreedom: 0, iSquared: 0.0, p: 0.0, (tauSquared: 0.0)? (NOTE: FOR RANDOM EFFECTS) }, overallEffect: { z: 0.0, p: 0.0 }, (experimental: { total: 0 }, control: { total: 0 })? } OVERALL_RESULT_DATA extends SUBGROUP_RESULT_DATA: { (subgroupDifferences: { chiSquared: 0.0, degreesOfFreedom: 0, iSquared: 0.0, p: 0.0},)? (experimental: { total: 0 }, control: { total: 0 })? } |
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RESULT: { diagnosticDataRows: [ <DIAGNOSTIC_RESULT_TEST_DATA_ROW>* ] | diagnosticSubgroups: [{ meanD: 0.0, a: 0.0, b: 0.0, diagnosticDataRows: [ <DIAGNOSTIC_RESULT_TEST_DATA_ROW>ROW_FOR_SUBGROUP>* ] },...] } DIAGNOSTIC_RESULT_TEST_DATA_ROW: { sensitivity: 0.0, sensCiStart: 0.0, sensCiEnd: 0.0, specificity: 0.0, specCiStart: 0.0, specCiEnd: 0.0 } DIAGNOSTIC_RESULT_TEST_DATA_ROW_FOR_SUBGROUP extends DIAGNOSTIC_RESULT_TEST_DATA_ROW: { d: 0.0, s: 0.0, weight: 0.0, scaleSpec: 0.0, scaleSens: 0.0 } |
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(NOTE: both dataRows and subgroups should be provided when the overall results should be based on a separate analysis, e.g. subgroups with studies split by intervention.) INPUT: [{ options: { dataType: "DICHOTOMOUS"|"CONTINUOUS"|"CONTRAST"|"OBSERVED_EXPECTED", (NOTE: CONTRAST maps to INVERSE_VARIANCE in RM5/ and CONTRAST_LEVEL in Review DB) method: "MH"|"GIV"|"PETO", effectMeasure: "MD"|"SMD"|"LOR"|"LRR"|"RD"|"PetoLOR"|"Generic", model: "FIXED"|"RANDOM", heterogeneityEstimator: "DL"|"REML", ciLevelRows: 0.90|0.95|0.99, ciLevelTotals: 0.90|0.95|0.99, swapEvents: true|false, logData: true|false, totals: "YES"|"SUB"|"NO" }, dataRows: [ <DICHOTOMOUS_DATA>*|<CONTINUOUS_DATA>*|<CONTRAST_DATA>*|<OBSERVED_EXPECTED_DATA>* ]|, subgroups: [{ dataRows: [ <DICHOTOMOUS_DATA>*|<CONTINUOUS_DATA>*|<CONTRAST_DATA>*|<OBSERVED_EXPECTED_DATA>* ] },...] }] DICHOTOMOUS_DATA: { studyId, experimental: { events: 0, total: 0 }, control: { events: 0, total: 0 } } CONTINUOUS_DATA: { studyId, experimental experimental: { total: 0, mean: 0.0, sd: 0.0 }, control: { total: 0, mean: 0.0, sd: 0.0 } } CONTRAST_DATA: { estimatestudyId, estimate: 0.0, se: 0.0 (experimental: { total: 0 }, control: { total: 0 })? } OBSERVED_EXPECTED_DATA: { studyId, oe oe: 0.0, variance: 0.0, (experimental: { events: 0, total: 0 }, control: { events: 0, total: 0 })? } |
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