Package: ConfoundedMeta
Type: Package
Title: Sensitivity Analyses for Unmeasured Confounding in Meta-Analyses
Version: 1.2.0
Date: 2017-05-31
Author: Maya B. Mathur, Tyler J. VanderWeele
Maintainer: Maya B. Mathur <maya.z.mathur@gmail.com>
Description: Conducts sensitivity analyses for unmeasured confounding in
random-effects meta-analysis per Mathur & VanderWeele (in preparation).
Given output from a random-effects meta-analysis with a relative risk
outcome, computes point estimates and inference for: (1) the proportion
of studies with true causal effect sizes more extreme than a specified threshold
of scientific significance; and (2) the minimum bias factor and confounding
strength required to reduce to less than a specified threshold the proportion
of studies with true effect sizes of scientifically significant size.
Creates plots and tables for visualizing these metrics across a range of bias values.
Provides tools to easily scrape study-level data from a published forest plot or
summary table to obtain the needed estimates when these are not reported.
License: GPL-2
Imports: ggplot2 (>= 2.2.1), metafor, stats
RoxygenNote: 6.0.1
NeedsCompilation: no
Packaged: 2017-06-30 19:12:33 UTC; mmathur
Repository: CRAN
Date/Publication: 2017-07-09 06:16:14 UTC

Package: ConfoundedMeta
Type: Package
Title: Sensitivity Analyses for Unmeasured Confounding in Meta-Analyses
Version: 1.3.0
Date: 2017-05-31
Author: Maya B. Mathur, Tyler J. VanderWeele
Maintainer: Maya B. Mathur <maya.z.mathur@gmail.com>
Description: Conducts sensitivity analyses for unmeasured confounding in
random-effects meta-analysis per Mathur & VanderWeele (in preparation).
Given output from a random-effects meta-analysis with a relative risk
outcome, computes point estimates and inference for: (1) the proportion
of studies with true causal effect sizes more extreme than a specified threshold
of scientific significance; and (2) the minimum bias factor and confounding
strength required to reduce to less than a specified threshold the proportion
of studies with true effect sizes of scientifically significant size.
Creates plots and tables for visualizing these metrics across a range of bias values.
Provides tools to easily scrape study-level data from a published forest plot or
summary table to obtain the needed estimates when these are not reported.
License: GPL-2
Imports: ggplot2 (>= 2.2.1), metafor, stats
RoxygenNote: 6.0.1
NeedsCompilation: no
Packaged: 2017-08-14 12:40:06 UTC; mmathur
Repository: CRAN
Date/Publication: 2017-08-14 13:17:55 UTC