Fit Poolwise Regression Models

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Documentation for package ‘pooling’ version 1.1.2

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pooling-package Fit Poolwise Regression Models
cond_logreg Conditional Logistic Regression with Measurement Error in One Covariate
dat_cond_logreg Dataset for Examples in cond_logreg
dat_p_gdfa Dataset for Examples in p_gdfa
dat_p_linreg_yerrors Dataset for Examples in p_linreg_yerrors
dat_p_ndfa Dataset for Examples in p_ndfa
form_pools Created a Pooled Dataset from a Subject-Specific One
pdat1 Dataset for Examples in p_dfa_xerrors and p_logreg_xerrors
pdat2 Dataset for Examples in p_dfa_xerrors2 and p_logreg_xerrors2
plot_dfa Plot Log-OR vs. X for Normal Discriminant Function Approach
plot_dfa2 Plot Log-OR vs. X for Gamma Discriminant Function Approach
plot_gdfa Plot Log-OR vs. X for Gamma Discriminant Function Approach
plot_ndfa Plot Log-OR vs. X for Normal Discriminant Function Approach
poolcost_t Visualize Total Costs for Pooling Design as a Function of Pool Size
poolcushion_t Visualize T-test Power for Pooling Design as Function of Processing Error Variance
pooling Fit Poolwise Regression Models
poolpower_t Visualize T-test Power for Pooling Design
poolvar_t Visualize Ratio of Variance of Each Pooled Measurement to Variance of Each Unpooled Measurement as Function of Pool Size
p_dfa_xerrors Discriminant Function Approach for Estimating Odds Ratio with Normal Exposure Measured in Pools and Potentially Subject to Errors
p_dfa_xerrors2 Discriminant Function Approach for Estimating Odds Ratio with Gamma Exposure Measured in Pools and Potentially Subject to Errors
p_gdfa Gamma Discriminant Function Approach for Estimating Odds Ratio with Exposure Measured in Pools and Potentially Subject to Multiplicative Lognormal Errors
p_gdfa_constant Gamma Discriminant Function Approach for Estimating Odds Ratio with Exposure Measured in Pools and Potentially Subject to Multiplicative Lognormal Errors (Constant Odds Ratio Version)
p_gdfa_nonconstant Gamma Discriminant Function Approach for Estimating Odds Ratio with Exposure Measured in Pools and Potentially Subject to Multiplicative Lognormal Errors (Non-constant Odds Ratio Version)
p_linreg_yerrors Linear Regression of Y vs. Covariates with Y Measured in Pools and (Potentially) Subject to Additive Normal Errors
p_logreg Poolwise Logistic Regression
p_logreg_xerrors Poolwise Logistic Regression with Normal Exposure Subject to Errors
p_logreg_xerrors2 Poolwise Logistic Regression with Gamma Exposure Subject to Errors
p_ndfa Normal Discriminant Function Approach for Estimating Odds Ratio with Exposure Measured in Pools and Potentially Subject to Additive Normal Errors
p_ndfa_constant Normal Discriminant Function Approach for Estimating Odds Ratio with Exposure Measured in Pools and Potentially Subject to Additive Normal Errors (Constant Odds Ratio Version)
p_ndfa_nonconstant Normal Discriminant Function Approach for Estimating Odds Ratio with Exposure Measured in Pools and Potentially Subject to Additive Normal Errors (Non-constant Odds Ratio Version)
simdata Dataset for a Paper Under Review
test_pe Test for Underestimated Processing Error Variance in Pooling Studies