diff --git a/README.md b/README.md index 3b54929..fe2872c 100644 --- a/README.md +++ b/README.md @@ -30,10 +30,6 @@ This repository contains all code files related to our ROSALI/Resiuals Cohort st ### Analyzed Datasets -**noDIF_noConf / XXX_N.csv** - Analysis for scenario XXX_N by PCM __without__ accounting for DIF nor confusion -**DIF_noConf / XXX_N.xls** - Analysis for scenario XXX_N by PCM __with__ DIF accounted for but not confusion -**ROSALI-DIF_noConf / XXX_N_original.xls** - Analysis for scenario XXX_N by PCM __with__ DIF accounted for after detection by ROSALI but not accounting for confusion -**RESIDUALS_noConf / XXX_N_original.xls** - Analysis for scenario XXX_N by PCM __with__ DIF accounted for after detection by Andrich & Hagquist's residuals method but not accounting for confusion **noDIF / XXX_N.csv** - Analysis for scenario XXX_N by PCM __without__ accounting for DIF and confusion accounted for **DIF / XXX_N.xls** - Analysis for scenario XXX_N by PCM __with__ DIF and confusion accounted for diff --git a/catalogue.md b/catalogue.md index 310dbfc..ddd1f09 100644 --- a/catalogue.md +++ b/catalogue.md @@ -2,13 +2,13 @@ ## Scenarios without DIF -| | **J** | | **M** | | -| -------------- | ----- | ----- | ----- | ----- | -| | **4** | **7** | **2** | **4** | -| **Scenario 1** | X | | X | | -| **Scenario 2** | X | | | X | -| **Scenario 3** | | X | X | | -| **Scenario 4** | | X | | X | +| | **J** | | **Epsilon** | | +| -------------- | ----- | ----- | ----- | ----- | +| | **4** | **7** | **0.2** | **0.5** | +| **Scenario 101** | X | | X | | +| **Scenario 102** | X | | | X | +| **Scenario 103** | | X | X | | +| **Scenario 104** | | X | | X | Each scenario has 5 subscenarios: @@ -20,25 +20,25 @@ Each scenario has 5 subscenarios: ## Scenarios with DIF -| | **J** | | **M** | | **Nb items DIF** | | | **DIF size** | | +| | **J** | | **Epsilon** | | **Nb items DIF** | | | **DIF size** | | | --------------- | ----- | ----- | ----- | ----- | ---------------- | ----- | ----- | -------------- | ------- | -| | **4** | **7** | **2** | **4** | **1** | **2** | **3** | **0.3** | **0.5** | -| **Scenario 5** | X | | X | | X | | | X | | -| **Scenario 6** | X | | | X | X | | | X | | -| **Scenario 7** | X | | X | | X | | | | X | -| **Scenario 8** | X | | | X | X | | | | X | -| **Scenario 9** | X | | X | | | X | | X | | -| **Scenario 10** | X | | | X | | X | | X | | -| **Scenario 11** | X | | X | | | X | | | X | -| **Scenario 12** | X | | | X | | X | | | X | -| **Scenario 13** | | X | X | | | X | | X | | -| **Scenario 14** | | X | | X | | X | | X | | -| **Scenario 15** | | X | X | | | X | | | X | -| **Scenario 16** | | X | | X | | X | | | X | -| **Scenario 17** | | X | X | | | | X | X | | -| **Scenario 18** | | X | | X | | | X | X | | -| **Scenario 19** | | X | X | | | | X | | X | -| **Scenario 20** | | X | | X | | | X | | X | +| | **4** | **7** | **0.2** | **0.5** | **1** | **2** | **3** | **0.3** | **0.5** | +| **Scenario 105** | X | | X | | X | | | X | | +| **Scenario 106** | X | | | X | X | | | X | | +| **Scenario 107** | X | | X | | X | | | | X | +| **Scenario 108** | X | | | X | X | | | | X | +| **Scenario 109** | X | | X | | | X | | X | | +| **Scenario 110** | X | | | X | | X | | X | | +| **Scenario 111** | X | | X | | | X | | | X | +| **Scenario 112** | X | | | X | | X | | | X | +| **Scenario 113** | | X | X | | | X | | X | | +| **Scenario 114** | | X | | X | | X | | X | | +| **Scenario 115** | | X | X | | | X | | | X | +| **Scenario 116** | | X | | X | | X | | | X | +| **Scenario 117** | | X | X | | | | X | X | | +| **Scenario 118** | | X | | X | | | X | X | | +| **Scenario 119** | | X | X | | | | X | | X | +| **Scenario 120** | | X | | X | | | X | | X | Each scenario has 7 subscenarios: @@ -56,3 +56,31 @@ Each scenario has 7 subscenarios: - **Adverse effects example** - G - H1 true, effect size -0.4, DIF -0.3/0.5 on traitement group - **Adverse effects example** + + +## Confusion simulation details + +8 covariates are simulated for each scenario, each defined by their odds ratio on treatment and odds ratio on outcome: + +**OR_TT^X**: Odds ratio describing the increase in probability of patients being treated when covariate X is positive. +**OR_Y^X**: Odds ratio describing the increase in average outcome when covariate X is positive. + +Covariates are simulated as in *Sturmer et al, 2021*: + + +| **Variables** | **OR_TT^X** | **OR_Y^X** | +| -------------- | ----- | ----- | +| **X_1** | 2.0 | 1.0 | +| **X_2** | 1.5 | 1.0 | +| **X_3** | 1.0 | 2.0 | +| **X_4** | 1.0 | 1.5 | +| **X_5** | Epsilon | Epsilon | +| **X_6** | 1.5 x Epsilon | 1.5 x Epsilon | +| **X_7** | 1.0 / 10 | 1.0 / 10 | +| **X_8** | 1.0 / 0.1 | 1.0 / 10 | + +**X_1** and **X_2** are thus *Instrumental variables*, **X_3** and **X_4** are *Risk factors for the outcome* and **X_5** and **X_6** are *Cofounders*. + +**X_7** and **X_8** are unobserved tail-end cofounders indicating rare treatment decisions for extreme propensity score values in each group. Untreated patients with very high propensity of treatment will be very likely to have **X_7**=1 (patients that should have been treated but weren't due to frailty). Treated patients with very low propensity of treatment will be very likely to have **X_8**=1 (patients that should not have been treated but were due to severe condition). + +For each replication, observed covariates explained treatment with an AUC drawn randomly between 0.65 and 0.85 (average: 0.75).