Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Randomized Experiments01:13

Randomized Experiments

9.2K
The randomization process involves assigning study participants randomly to experimental or control groups based on their probability of being equally assigned. Randomization is meant to eliminate selection bias and balance known and unknown confounding factors so that the control group is similar to the treatment group as much as possible. A computer program and a random number generator can be used to assign participants to groups in a way that minimizes bias.
Simple randomization
Simple...
9.2K
Friedman Two-way Analysis of Variance by Ranks01:21

Friedman Two-way Analysis of Variance by Ranks

531
Friedman's Two-Way Analysis of Variance by Ranks is a nonparametric test designed to identify differences across multiple test attempts when traditional assumptions of normality and equal variances do not apply. Unlike conventional ANOVA, which requires normally distributed data with equal variances, Friedman's test is ideal for ordinal or non-normally distributed data, making it particularly useful for analyzing dependent samples, such as matched subjects over time or repeated measures...
531
Experimental Designs01:16

Experimental Designs

18.4K
An experimental design is a systematic process that allows researchers to evaluate the relationship between dependent and independent variables. There are three widely used types of experimental design - pre-experimental design, true experimental design, and quasi-experimental design. In pre-experimental design, the researcher compares the data before and after some interventions or treatments. The true-experimental design has more than one purposefully created group, a commonly measured...
18.4K
Regression Toward the Mean01:52

Regression Toward the Mean

7.3K
Regression toward the mean (“RTM”) is a phenomenon in which extremely high or low values—for example, and individual’s blood pressure at a particular moment—appear closer to a group’s average upon remeasuring. Although this statistical peculiarity is the result of random error and chance, it has been problematic across various medical, scientific, financial and psychological applications. In particular, RTM, if not taken into account, can interfere when...
7.3K
Multiple Regression01:25

Multiple Regression

4.2K
Multiple regression assesses a linear relationship between one response or dependent variable and two or more independent variables. It has many practical applications.
Farmers can use multiple regression to determine the crop yield based on more than one factor, such as water availability, fertilizer, soil properties, etc. Here, the crop yield is the response or dependent variable as it depends on the other independent variables. The analysis requires the construction of a scatter plot...
4.2K
Bioequivalence Experimental Study Designs: Repeated Measures, Cross-Over, Carry-Over, and Latin Square Designs01:15

Bioequivalence Experimental Study Designs: Repeated Measures, Cross-Over, Carry-Over, and Latin Square Designs

363
Bioequivalence experimental study designs play a pivotal role in testing the effectiveness of various treatments. Key among these are the repeated measures, cross-over, carry-over, and Latin square designs. In the repeated measures design, each subject receives all treatments, allowing for temporal comparisons. This type of design is useful in reducing variability but requires careful planning to avoid bias.The cross-over design, an economical method, involves sequential administration of...
363

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Promoting Family/Friend Involvement in Care Planning in Care Homes: A Qualitative Exploration of the Usefulness and Relevance of an Information Resource.

Health expectations : an international journal of public participation in health care and health policy·2026
Same author

Independent Head-to-Head Comparison of Commercial Artificial Intelligence Devices for Lung Cancer Detection on Chest Radiographs.

Radiology·2026
Same author

Continuity of care in UK primary care: a scoping review of measures, challenges, and future interventions.

Primary health care research & development·2026
Same author

Improved prostate diffusion imaging using deep learning denoising and phase correction with ultra-high-density coil array.

Radiology advances·2026
Same author

The Use of the Rox Index to Guide High-Flow Nasal Cannula Therapy and the Need for Intubation Is Associated With Meaningful Patient Outcomes.

CHEST critical care·2026
Same author

Sotatercept for Decompensated Pulmonary Arterial Hypertension Requiring VA ECMO: First Canadian ICU Experience.

Pulmonary circulation·2026
Same journal

Tau protein as a regulator of mitochondrial function and dynamics.

Proceedings of the National Academy of Sciences of the United States of America·2026
Same journal

A scalable, dividing cell model for the robust propagation and quantification of human sporadic Creutzfeldt-Jakob disease prions.

Proceedings of the National Academy of Sciences of the United States of America·2026
Same journal

Epigenetic regulation of mesenchymal BMP signaling directs postnatal organ innervation.

Proceedings of the National Academy of Sciences of the United States of America·2026
Same journal

Single-shot wide-field biochemical imaging at 1 kHz frame rate.

Proceedings of the National Academy of Sciences of the United States of America·2026
Same journal

Morphogenesis and topological evolution of a frustrated nematic liquid crystal under confinement.

Proceedings of the National Academy of Sciences of the United States of America·2026
Same journal

B cell-intrinsic CXCR3 drives efficient generation of ectopic pulmonary germinal center responses to influenza A virus infection.

Proceedings of the National Academy of Sciences of the United States of America·2026
See all related articles

Related Experiment Video

Updated: Mar 13, 2026

Characterization of Complex Systems Using the Design of Experiments Approach: Transient Protein Expression in Tobacco as a Case Study
20:24

Characterization of Complex Systems Using the Design of Experiments Approach: Transient Protein Expression in Tobacco as a Case Study

Published on: January 31, 2014

17.2K

High-dimensional regression adjustments in randomized experiments.

Stefan Wager1,2, Wenfei Du3, Jonathan Taylor3

  • 1Department of Statistics, Stanford University, Stanford, CA 94305; swager@stanford.edu tibs@stanford.edu.

Proceedings of the National Academy of Sciences of the United States of America
|October 30, 2016
PubMed
Summary
This summary is machine-generated.

This study shows that regression adjustments provide efficient treatment effect estimates in high-dimensional randomized experiments. A new cross-estimation method ensures unbiased estimates using various regression techniques, including machine learning.

Keywords:
high-dimensional confoundersrandomized trialsregression adjustment

More Related Videos

The Innovation Arena: A Method for Comparing Innovative Problem-Solving Across Groups
14:14

The Innovation Arena: A Method for Comparing Innovative Problem-Solving Across Groups

Published on: May 13, 2022

6.4K
Lexical Decision Task for Studying Written Word Recognition in Adults with and without Dementia or Mild Cognitive Impairment
06:48

Lexical Decision Task for Studying Written Word Recognition in Adults with and without Dementia or Mild Cognitive Impairment

Published on: June 25, 2019

9.9K

Related Experiment Videos

Last Updated: Mar 13, 2026

Characterization of Complex Systems Using the Design of Experiments Approach: Transient Protein Expression in Tobacco as a Case Study
20:24

Characterization of Complex Systems Using the Design of Experiments Approach: Transient Protein Expression in Tobacco as a Case Study

Published on: January 31, 2014

17.2K
The Innovation Arena: A Method for Comparing Innovative Problem-Solving Across Groups
14:14

The Innovation Arena: A Method for Comparing Innovative Problem-Solving Across Groups

Published on: May 13, 2022

6.4K
Lexical Decision Task for Studying Written Word Recognition in Adults with and without Dementia or Mild Cognitive Impairment
06:48

Lexical Decision Task for Studying Written Word Recognition in Adults with and without Dementia or Mild Cognitive Impairment

Published on: June 25, 2019

9.9K

Area of Science:

  • Statistics
  • Econometrics
  • Machine Learning

Background:

  • Estimating treatment effects in randomized experiments with high-dimensional covariates is challenging.
  • Existing methods may lack efficiency or generalizability in complex data settings.

Purpose of the Study:

  • To develop efficient and valid methods for treatment effect estimation in high-dimensional randomized experiments.
  • To propose a robust estimation technique applicable across various regression models.

Main Methods:

  • Utilizing risk-consistent regression adjustments for efficient average treatment effect (ATE) estimation.
  • Introducing cross-estimation, a novel method for finite-sample-unbiased ATE estimation.
  • Extending methods to incorporate adaptive specification search (cross-validation) and machine learning (random forests, neural networks).

Main Results:

  • Demonstrated that a wide range of regression adjustments yield efficient ATE estimates.
  • Established the validity of high-dimensional regression adjustments for inference in broader settings.
  • Showcased the effectiveness of cross-estimation with methods like LASSO, elastic net, and subset selection.

Conclusions:

  • High-dimensional regression adjustments are powerful tools for valid and efficient treatment effect estimation.
  • Cross-estimation offers a practical solution for obtaining unbiased estimates, enhancing the reliability of experimental findings.
  • The proposed framework accommodates advanced machine learning techniques, broadening applicability in complex data analysis.