ipd0.1.4 package

Inference on Predicted Data

A

Calculation of the matrix A based on single dataset

augment.ipd

Augment Data from an IPD Fit

calc_lhat_glm

Estimate PPI++ Power Tuning Parameter

compute_cdf_diff

Empirical CDF Difference

compute_cdf

Empirical CDF of the Data

est_ini

Initial estimation

glance.ipd

Glance at an IPD Fit

ipd-package

ipd: Inference on Predicted Data

ipd

Inference on Predicted Data (ipd)

link_grad

Gradient of the link function

link_Hessian

Hessians of the link function

log1pexp

Log1p Exponential

logistic_get_stats

Logistic Regression Gradient and Hessian

mean_psi_pop

Sample expectation of PSPA psi

mean_psi

Sample expectation of psi

ols_get_stats

OLS Gradient and Hessian

ols

Ordinary Least Squares

optim_est

One-step update for obtaining estimator

optim_weights

One-step update for obtaining the weight vector

postpi_analytic_ols

PostPI OLS (Analytic Correction)

postpi_boot_logistic

PostPI Logistic Regression (Bootstrap Correction)

postpi_boot_ols

PostPI OLS (Bootstrap Correction)

ppi_logistic

PPI Logistic Regression

ppi_mean

PPI Mean Estimation

ppi_ols

PPI OLS

ppi_plusplus_logistic_est

PPI++ Logistic Regression (Point Estimate)

ppi_plusplus_logistic

PPI++ Logistic Regression

ppi_plusplus_mean_est

PPI++ Mean Estimation (Point Estimate)

ppi_plusplus_mean

PPI++ Mean Estimation

ppi_plusplus_ols_est

PPI++ OLS (Point Estimate)

ppi_plusplus_ols

PPI++ OLS

ppi_plusplus_quantile_est

PPI++ Quantile Estimation (Point Estimate)

ppi_plusplus_quantile

PPI++ Quantile Estimation

ppi_quantile

PPI Quantile Estimation

print.ipd

Print IPD Fit

print.summary.ipd

Print Summary of IPD Fit

psi

Estimating equation

pspa_logistic

PSPA Logistic Regression

pspa_mean

PSPA Mean Estimation

pspa_ols

PSPA OLS Estimation

pspa_poisson

PSPA Poisson Regression

pspa_quantile

PSPA Quantile Estimation

pspa_y

PSPA M-Estimation for ML-predicted labels

rectified_cdf

Rectified CDF

rectified_p_value

Rectified P-Value

reexports

Objects exported from other packages

Sigma_cal

Variance-covariance matrix of the estimation equation

sim_data_y

Simulate the data for testing the functions

simdat

Data generation function for various underlying models

summary.ipd

Summarize IPD Fit

tidy.ipd

Tidy an IPD Fit

wls

Weighted Least Squares

zconfint_generic

Normal Confidence Intervals

zstat_generic

Compute Z-Statistic and P-Value

Performs valid statistical inference on predicted data (IPD) using recent methods, where for a subset of the data, the outcomes have been predicted by an algorithm. Provides a wrapper function with specified defaults for the type of model and method to be used for estimation and inference. Further provides methods for tidying and summarizing results. Salerno et al., (2024) <doi:10.48550/arXiv.2410.09665>.

  • Maintainer: Stephen Salerno
  • License: MIT + file LICENSE
  • Last published: 2025-01-07