R: Quantify the Robustness of Causal Inferences

# Quantify the Robustness of Causal Inferences

## Documentation for package ‘konfound’ version 1.0.3

- DESCRIPTION file
- User guides, package vignettes and other documentation
- Package NEWS
- Package README

## Help Pages

binary_dummy_data | Binary dummy data
cal_delta_star | Calculate delta star for sensitivity analysis
cal_rxy | Calculate rxy based on ryxGz, rxz, and ryz
cal_rxz | Calculate R2xz based on variances and standard error
cal_ryz | Calculate R2yz based on ryxGz and R2
chisq_p | Perform a Chi-Square Test
concord1 | Concord1 data
get_kr_df | Extract Degrees of Freedom for Fixed Effects in a Linear Mixed-Effects Model
konfound | Konfound Analysis for Various Model Types
konfound_glm | Konfound Analysis for Generalized Linear Models
konfound_glm_dichotomous | Konfound Analysis for Generalized Linear Models with Dichotomous Outcomes
konfound_lm | Konfound Analysis for Linear Models
konfound_lmer | Konfound Analysis for Linear Mixed-Effects Models
mkonfound | Meta-Analysis and Sensitivity Analysis for Multiple Studies
mkonfound_ex | Example data for the mkonfound function
output_df | Output data frame based on model estimates and thresholds
output_print | Output printed text with formatting
output_table | Output a Tidy Table from a Model Object
pkonfound | Perform sensitivity analysis for published studies
plot_correlation | Plot Correlation Diagram
plot_threshold | Plot Effect Threshold Diagram
tkonfound | Perform Sensitivity Analysis on 2x2 Tables
tkonfound_fig | Draw Figures for Change in Effect Size in 2x2 Tables
verify_reg_Gzcv | Verify regression model with control variable Z
verify_reg_uncond | Verify unconditional regression model
zzz | Package Initialization Functions and Utilities