Package: sensitivityCalibration 0.0.1
Bo Zhang
sensitivityCalibration: A Calibrated Sensitivity Analysis for Matched Observational Studies
Implements the calibrated sensitivity analysis approach for matched observational studies. Our sensitivity analysis framework views matched sets as drawn from a super-population. The unmeasured confounder is modeled as a random variable. We combine matching and model-based covariate-adjustment methods to estimate the treatment effect. The hypothesized unmeasured confounder enters the picture as a missing covariate. We adopt a state-of-art Expectation Maximization (EM) algorithm to handle this missing covariate problem in generalized linear models (GLMs). As our method also estimates the effect of each observed covariate on the outcome and treatment assignment, we are able to calibrate the unmeasured confounder to observed covariates. Zhang, B., Small, D. S. (2018). <arxiv:1812.00215>.
Authors:
sensitivityCalibration_0.0.1.tar.gz
sensitivityCalibration_0.0.1.tar.gz(r-4.5-noble)sensitivityCalibration_0.0.1.tar.gz(r-4.4-noble)
sensitivityCalibration_0.0.1.tgz(r-4.4-emscripten)sensitivityCalibration_0.0.1.tgz(r-4.3-emscripten)
sensitivityCalibration.pdf |sensitivityCalibration.html✨
sensitivityCalibration/json (API)
| # Install 'sensitivityCalibration' in R: |
| install.packages('sensitivityCalibration', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org')) |
- NHANES_blood_lead - Second hand smoking and blood lead levels dataset from NHANES III.
- NHANES_blood_lead_small - A random subset of NHANES_blood_lead data.
- NHANES_blood_lead_small_matched - NHANES_blood_lead_small data after matching.
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated 6 years agofrom:ddf0339c8b. Checks:OK: 2. Indexed: yes.
| Target | Result | Date |
|---|---|---|
| Doc / Vignettes | OK | Aug 24 2024 |
| R-4.5-linux | OK | Aug 24 2024 |
Exports:calibrate_animcalibrate_oneCI_block_bootEM_Algorithmfind_borderfind_delta
Dependencies:askpassbase64encbootbslibcachemclicolorspacecorpcorcpp11crosstalkcurldata.tableDBIdigestdplyrevaluatefansifarverfastmapfontawesomefsgenericsggplot2ggrepelgluegtablehighrhtmltoolshtmlwidgetshttrisobandjquerylibjsonliteknitrlabelinglaterlatticelazyevallifecyclemagrittrMASSMatrixmemoisemgcvmimeminqamitoolsmunsellnlmenumDerivopensslpillarpkgconfigplotlypromisespurrrR6rappdirsRColorBrewerRcppRcppArmadillorelaimporlangrmarkdownsassscalessplitstackshapestringistringrsurveysurvivalsystibbletidyrtidyselecttinytexutf8vctrsviridisLitewithrxfunyaml
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Make the dynamic calibration plot. | calibrate_anim |
| Make the calibration plot. | calibrate_one |
| Construct the 95% confidence interval of the treatment effect given the set of sensitivity parameters. | CI_block_boot |
| Estimate the treatment effect for a matched dataset given the set of sensitivity parameters. | EM_Algorithm |
| Find the lambda-delta boundary for a fixed sensitivity parameter p. | find_border |
| Estimate the maximum delta for fixed sensitivity parameters p and lambda. | find_delta |
| Second hand smoking and blood lead levels dataset from NHANES III. | NHANES_blood_lead |
| A random subset of NHANES_blood_lead data. | NHANES_blood_lead_small |
| NHANES_blood_lead_small data after matching. | NHANES_blood_lead_small_matched |