Package: tipr 1.0.2.9000

Lucy DAgostino McGowan

tipr: Tipping Point Analyses

The strength of evidence provided by epidemiological and observational studies is inherently limited by the potential for unmeasured confounding. We focus on three key quantities: the observed bound of the confidence interval closest to the null, the relationship between an unmeasured confounder and the outcome, for example a plausible residual effect size for an unmeasured continuous or binary confounder, and the relationship between an unmeasured confounder and the exposure, for example a realistic mean difference or prevalence difference for this hypothetical confounder between exposure groups. Building on the methods put forth by Cornfield et al. (1959), Bross (1966), Schlesselman (1978), Rosenbaum & Rubin (1983), Lin et al. (1998), Lash et al. (2009), Rosenbaum (1986), Cinelli & Hazlett (2020), VanderWeele & Ding (2017), and Ding & VanderWeele (2016), we can use these quantities to assess how an unmeasured confounder may tip our result to insignificance.

Authors:Lucy D'Agostino McGowan [aut, cre], Malcolm Barrett [aut]

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tipr/json (API)
NEWS

# Install 'tipr' in R:
install.packages('tipr', repos = c('https://r-causal.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Bug tracker:https://github.com/r-causal/tipr/issues

Datasets:

On CRAN:

4.98 score 33 stars 58 scripts 406 downloads 36 exports 13 dependencies

Last updated 10 months agofrom:ba218310fe. Checks:OK: 7. Indexed: yes.

TargetResultDate
Doc / VignettesOKNov 18 2024
R-4.5-winOKNov 18 2024
R-4.5-linuxOKNov 18 2024
R-4.4-winOKNov 18 2024
R-4.4-macOKNov 18 2024
R-4.3-winOKNov 18 2024
R-4.3-macOKNov 18 2024

Exports:%>%adjust_coefadjust_coef_with_binaryadjust_coef_with_continuousadjust_coef_with_r2adjust_hradjust_hr_with_binaryadjust_hr_with_continuousadjust_oradjust_or_with_binaryadjust_or_with_continuousadjust_rradjust_rr_with_binaryadjust_rr_with_continuouse_valueobserved_bias_orderobserved_bias_tblobserved_bias_tipobserved_covariate_e_valuer_valuetiptip_btip_ctip_coeftip_coef_with_continuoustip_coef_with_r2tip_hrtip_hr_with_binarytip_hr_with_continuoustip_ortip_or_with_binarytip_or_with_continuoustip_rrtip_rr_with_continuoustip_with_binarytip_with_continuous

Dependencies:clifansigluelifecyclemagrittrpillarpkgconfigpurrrrlangsensemakrtibbleutf8vctrs

Readme and manuals

Help Manual

Help pageTopics
Adjust an observed regression coefficient for a normally distributed confounderadjust_coef adjust_coef_with_continuous
Adjust an observed coefficient from a regression model with a binary confounderadjust_coef_with_binary
Adjust a regression coefficient using the partial R2 for an unmeasured confounder-exposure relationship and unmeasured confounder- outcome relationshipadjust_coef_with_r2
Adjust an observed hazard ratio for a normally distributed confounderadjust_hr adjust_hr_with_continuous
Adjust an observed hazard ratio with a binary confounderadjust_hr_with_binary
Adjust an observed odds ratio for a normally distributed confounderadjust_or adjust_or_with_continuous
Adjust an observed odds ratio with a binary confounderadjust_or_with_binary
Adjust an observed risk ratio for a normally distributed confounderadjust_rr adjust_rr_with_continuous
Adjust an observed risk ratio with a binary confounderadjust_rr_with_binary
Calculate an E-valuee_value
Example Data (Continuous Outcome)exdata_continuous
Example Data (Risk Ratio)exdata_rr
Order observed bias data frame for plottingobserved_bias_order
Create a data frame to assist with creating an observed bias plotobserved_bias_tbl
Create a data frame to combine with an observed bias data frame demonstrating a hypothetical unmeasured confounderobserved_bias_tip
Calculate the Observed Covariate E-valueobserved_covariate_e_value
Robustness valuer_value
Tip a result with a normally distributed confounder.tip tip_c tip_with_continuous
Tip a linear model coefficient with a continuous confounder.tip_coef tip_coef_with_continuous
Tip a regression coefficient using the partial R2 for an unmeasured confounder-exposure relationship and unmeasured confounder- outcome relationshiptip_coef_with_r2
Tip an observed hazard ratio with a normally distributed confounder.tip_hr tip_hr_with_continuous
Tip an observed hazard ratio with a binary confounder.tip_hr_with_binary
Tip an observed odds ratio with a normally distributed confounder.tip_or tip_or_with_continuous
Tip an observed odds ratio with a binary confounder.tip_or_with_binary
Tip an observed risk ratio with a normally distributed confounder.tip_rr tip_rr_with_continuous
Tip an observed risk ratio with a binary confounder.tip_rr_with_binary
Tip a result with a binary confounder.tip_b tip_with_binary