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

Cluster Sampling Method01:20

Cluster Sampling Method

12.0K
Appropriate sampling methods ensure that samples are drawn without bias and accurately represent the population. Because measuring the entire population in a study is not practical, researchers use samples to represent the population of interest.
To choose a cluster sample, divide the population into clusters (groups) and then randomly select some of the clusters. All the members from these clusters are in the cluster sample. For example, if you randomly sample four departments from your...
12.0K
Stratified Sampling Method01:16

Stratified Sampling Method

12.1K
Sampling is a technique to select a portion (or subset) of the larger population and study that portion (the sample) to gain information about the population. The sampling method ensures that samples are drawn without bias and accurately represent the population. Because measuring the entire population in a study is not practical, researchers use samples to represent the population of interest.
To choose a stratified sample, divide the population into groups called strata and then take a...
12.1K
Systematic Sampling Method01:17

Systematic Sampling Method

10.4K
Sampling is a technique to select a portion (or subset) of the larger population and study that portion (the sample) to gain information about the population. Data are the result of sampling from a population. The sampling method ensures that samples are drawn without bias and accurately represent the population. Because measuring the entire population in a study is not practical, researchers use samples to represent the population of interest.
Systematic sampling is one of the simplest methods...
10.4K
One-Compartment Open Model: Wagner-Nelson and Loo Riegelman Method for ka Estimation01:24

One-Compartment Open Model: Wagner-Nelson and Loo Riegelman Method for ka Estimation

569
This lesson introduces two critical methods in pharmacokinetics, the Wagner-Nelson and Loo-Riegelman methods, used for estimating the absorption rate constant (ka) for drugs administered via non-intravenous routes. The Wagner-Nelson method relates ka to the plasma concentration derived from the slope of a semilog percent unabsorbed time plot. However, it is limited to drugs with one-compartment kinetics and can be impacted by factors like gastrointestinal motility or enzymatic degradation.
On...
569
Errors and Mistakes in Surveying01:19

Errors and Mistakes in Surveying

115
Errors and mistakes in surveying refer to inaccuracies in measurements and data recording. The errors are deviations from the actual value caused by human sensory limitations, equipment flaws, or environmental effects. These errors are typically unintentional and can result from the inherent imperfections in the instruments used, atmospheric conditions, or the observer’s inability to perceive exact measurements. On the other hand, mistakes are caused by the surveyor's lack of...
115
Convenience Sampling Method00:55

Convenience Sampling Method

8.9K
Sampling is a technique to select a portion (or subset) of the larger population and study that portion (the sample) to gain information about the population. Data are the result of sampling from a population. The sampling method ensures that samples are drawn without bias and accurately represent the population.
Convenience sampling is a non-random method of sample selection; this method selects individuals that are easily accessible and may result in biased data. For example, a marketing...
8.9K

You might also read

Related Articles

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

Sort by
Same author

Pharmacokinetics of Ribociclib in Subjects With Hepatic Impairment.

Journal of clinical pharmacology·2021
Same author

Determination of Factors Affecting Dengue Occurrence in Representative Areas of China: A Principal Component Regression Analysis.

Frontiers in public health·2021
Same author

Neuroendocrine prostate cancer has distinctive, non-prostatic HOX code that is represented by the loss of HOXB13 expression.

Scientific reports·2021
Same author

Earthworm-Inspired Ultradurable Superhydrophobic Fabrics from Adaptive Wrinkled Skin.

ACS applied materials & interfaces·2021
Same author

Targeting macrophage liver X receptors by hydrogel-encapsulated T0901317 reduces atherosclerosis without effect on hepatic lipogenesis.

British journal of pharmacology·2021
Same author

A neural network based MRAC scheme with application to an autonomous nonlinear rotorcraft in the presence of input saturation.

ISA transactions·2021
Same journal

Gene-environment interaction analysis under the Cox model.

Annals of the Institute of Statistical Mathematics·2025
Same journal

Generation of all randomizations using circuits.

Annals of the Institute of Statistical Mathematics·2023
Same journal

Nonparametric tests for multistate processes with clustered data.

Annals of the Institute of Statistical Mathematics·2022
Same journal

Semiparametric modelling of two-component mixtures with stochastic dominance.

Annals of the Institute of Statistical Mathematics·2022
Same journal

Weighted Estimating Equations for Additive Hazards Models with Missing Covariates.

Annals of the Institute of Statistical Mathematics·2019
Same journal

Sparse and Efficient Estimation for Partial Spline Models with Increasing Dimension.

Annals of the Institute of Statistical Mathematics·2015
See all related articles
  1. Home
  3. Matrix Completion Under Complex Survey Sampling.
  1. Home
  3. Matrix Completion Under Complex Survey Sampling.

Related Experiment Video

Measuring the Structure, Composition, and Change of Underwater Environments with Large-area Imaging
09:19

Measuring the Structure, Composition, and Change of Underwater Environments with Large-area Imaging

Published on: April 18, 2025

606

Matrix completion under complex survey sampling.

Xiaojun Mao1, Zhonglei Wang2, Shu Yang3

  • 1School of Mathematical Sciences, Ministry of Education Key Laboratory of Scientific and Engineering Computing, Shanghai Jiao Tong University, Shanghai 200240, People's Republic of China.

Annals of the Institute of Statistical Mathematics
|August 30, 2023

View abstract on PubMed

Summary
This summary is machine-generated.

This study introduces a novel matrix completion method for complex survey sampling to address multivariate nonresponse. The new approach improves estimation accuracy, outperforming existing methods in simulations for health status assessment.

Keywords:
Asymptotic upper boundAugmented inverse probability weighting estimatorLow-rank structureMissingness at random

More Related Videos

Sampling Soils in a Heterogeneous Research Plot
07:11

Sampling Soils in a Heterogeneous Research Plot

Published on: January 7, 2019

34.6K
Candidate Gene Testing in Clinical Cohort Studies with Multiplexed Genotyping and Mass Spectrometry
05:53

Candidate Gene Testing in Clinical Cohort Studies with Multiplexed Genotyping and Mass Spectrometry

Published on: June 21, 2018

10.2K

Related Experiment Videos

Measuring the Structure, Composition, and Change of Underwater Environments with Large-area Imaging
09:19

Measuring the Structure, Composition, and Change of Underwater Environments with Large-area Imaging

Published on: April 18, 2025

606
Sampling Soils in a Heterogeneous Research Plot
07:11

Sampling Soils in a Heterogeneous Research Plot

Published on: January 7, 2019

34.6K
Candidate Gene Testing in Clinical Cohort Studies with Multiplexed Genotyping and Mass Spectrometry
05:53

Candidate Gene Testing in Clinical Cohort Studies with Multiplexed Genotyping and Mass Spectrometry

Published on: June 21, 2018

10.2K

Area of Science:

  • Statistics
  • Survey Methodology
  • Data Science

Background:

  • Multivariate nonresponse is a significant challenge in complex survey sampling, leading to biased inferences if ignored.
  • Existing imputation methods often focus on row-wise or column-wise approaches, failing to leverage the full data structure.

Purpose of the Study:

  • To propose a new matrix completion method for complex survey sampling that simultaneously exploits row and column patterns.
  • To develop a computationally efficient method for parameter identification and estimation under complex survey designs.
  • To provide a robust estimator for parameters of interest with a derived error bound.

Main Methods:

  • A column-space-decomposition model is employed, treating the data matrix as a whole to capture simultaneous row and column patterns.
  • A low-rank structured matrix incorporating demographic covariates is used for the finite population.
  • An augmented inverse probability weighting estimator is utilized for parameter estimation.

    • Main Results:

    • The proposed matrix completion method demonstrated superior performance with a smaller mean squared error compared to existing competitors in simulation studies.
    • The derived variance estimator for the proposed method performed well, indicating reliability.
    • The method was successfully applied to assess the health status of the U.S. population.

    Conclusions:

    • The novel matrix completion method effectively addresses multivariate nonresponse in complex surveys by utilizing the entire data matrix.
    • The proposed approach offers improved estimation accuracy and reliable variance estimation for survey data.
    • This method provides a valuable tool for analyzing complex survey data, as demonstrated by its application to U.S. health status assessment.