pooling-package |
Fit Poolwise Regression Models |
dat1 |
Dataset with Simulated (Y, C) Values for Examples in dfa_xerrors and logreg_xerrors |
dat1_xtilde |
Dataset with Simulated Xtilde Values for Examples in dfa_xerrors and logreg_xerrors |
dfa_xerrors |
Discriminant Function Approach for Estimating Odds Ratio with Normal Exposure Subject to Measurement Error |
gamma_constantscale |
Fit Constant-Scale Gamma Model for Y vs. Covariates |
lognormal |
Fit Lognormal Regression for Y vs. Covariates |
logreg_xerrors |
Logistic Regression with Normal Exposure Subject to Errors |
pdat1 |
Dataset with Simulated (Y, Xtilde, C) Values for Examples in p_dfa_xerrors and p_logreg_xerrors |
pdat2 |
Dataset with Simulated (Y, Xtilde) Values for Examples in p_dfa_xerrors2 and p_logreg_xerrors2 |
pdat2_c |
Dataset with Simulated C Values 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 |
poolcost_t |
Visualize Total Costs for Pooling Design as a Function of Pool Size |
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 Subject to Errors |
p_dfa_xerrors2 |
Discriminant Function Approach for Estimating Odds Ratio with Gamma Exposure Measured in Pools and Subject to 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 |
test_pe |
Test for Underestimated Processing Error Variance in Pooling Studies |