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

Multiple Allele Traits01:49

Multiple Allele Traits

38.0K
The Concept of Multiple Allelism
38.0K
What are Estimates?01:06

What are Estimates?

8.2K
It isn't easy to measure a parameter such as the mean height or the mean weight of a population. So, we draw samples from the population and calculate the mean height or mean weight of the individuals in the sample. This sample data acts as a representative measure of the population parameter. These sample statistics are known as estimates. 
The estimate for the mean of a sample is denoted by ͞x, whereas the mean of the population is designated as μ. Further, parameters such...
8.2K
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

1.1K
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...
1.1K
Estimation of k and VD of Aminoglycosides01:20

Estimation of k and VD of Aminoglycosides

227
Aminoglycosides are a class of antibiotics used to treat various bacterial infections. Clinicians must determine the elimination rate constant (k) and volume of distribution (VD) to optimize therapeutic efficacy and minimize toxicity. The k value represents the rate at which the drug is removed from the body, and the VD reflects the degree to which the drug distributes into body tissues. Accurately estimating these parameters allows healthcare professionals to tailor drug dosing to individual...
227
Subcellular Fractionation01:32

Subcellular Fractionation

8.8K
The homogenate obtained after cell lysis contains various membrane-bound organelles that can be further separated into pure fractions by subcellular fractionation. These isolates are used to study specific cellular components, analyze localized protein activity, and are even employed in diagnostics. Fractionation is typically achieved using centrifugation methods, the most common being density-gradient and differential centrifugation.
Differential Centrifugation
Differential centrifugation is...
8.8K
Estimation of the Physical Quantities01:05

Estimation of the Physical Quantities

7.5K
On many occasions, physicists, other scientists, and engineers need to make estimates of a particular quantity. These are sometimes referred to as guesstimates, order-of-magnitude approximations, back-of-the-envelope calculations, or Fermi calculations. The physicist Enrico Fermi was famous for his ability to estimate various kinds of data with surprising precision. Estimating does not mean guessing a number or a formula at random. Instead, estimation means using prior experience and sound...
7.5K

You might also read

Related Articles

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

Sort by
Same author

Reliability of end-tidal carbon dioxide as a surrogate for arterial carbon dioxide assessment in infants undergoing thoracoscopic surgery with one-lung ventilation.

BMC anesthesiology·2026
Same author

Glottic-level, anesthesia machine-based high-frequency ventilation as an oxygenation bridge for short pediatric gastroscopy under intravenous anesthesia: a nine-patient case series.

Journal of anesthesia·2026
Same author

Polyphenols from Pulses: Recent Advances in Gut Health Benefits and Strategies to Elevate Their Concentrations.

Nutrients·2026
Same author

NPC1 promotes HTNV replication by controlling innate immune response.

Frontiers in immunology·2026
Same author

Technical note: a novel fully visualized, glottic-sparing strategy for infant one-lung ventilation.

Minerva anestesiologica·2026
Same author

Causal effects among hypertension, osteoporosis, and metabolites: A Mendelian randomization study.

Journal of the Chinese Medical Association : JCMA·2026

Related Experiment Video

Updated: Jan 27, 2026

The Optical Fractionator Technique to Estimate Cell Numbers in a Rat Model of Electroconvulsive Therapy
07:55

The Optical Fractionator Technique to Estimate Cell Numbers in a Rat Model of Electroconvulsive Therapy

Published on: July 9, 2017

12.1K

Improved methods for estimating fraction of missing information in multiple imputation.

Qiyuan Pan1, Rong Wei2

  • 1National Center for Health Statistics (NCHS), 3311 Toledo Rd., Hyattsville, Maryland 20782, USA.

Cogent Mathematics & Statistics
|March 23, 2019
PubMed
Summary

Multiple imputation (MI) is popular for missing data. However, the current fraction of missing information (FMI) estimation method, γm, overestimates the true population value γ0, necessitating improved methods.

Keywords:
Applied MathematicsMathematics & StatisticsMathematics for Biology & MedicineNational Ambulatory Medical Care SurveySciencefraction of missing informationmissing datamultiple imputationnumber of imputations

More Related Videos

Leaf Area Index Estimation Using Three Distinct Methods in Pure Deciduous Stands
09:04

Leaf Area Index Estimation Using Three Distinct Methods in Pure Deciduous Stands

Published on: August 29, 2019

14.1K
Estimation of Nephron Number in Whole Kidney using the Acid Maceration Method
08:15

Estimation of Nephron Number in Whole Kidney using the Acid Maceration Method

Published on: May 22, 2019

10.6K

Related Experiment Videos

Last Updated: Jan 27, 2026

The Optical Fractionator Technique to Estimate Cell Numbers in a Rat Model of Electroconvulsive Therapy
07:55

The Optical Fractionator Technique to Estimate Cell Numbers in a Rat Model of Electroconvulsive Therapy

Published on: July 9, 2017

12.1K
Leaf Area Index Estimation Using Three Distinct Methods in Pure Deciduous Stands
09:04

Leaf Area Index Estimation Using Three Distinct Methods in Pure Deciduous Stands

Published on: August 29, 2019

14.1K
Estimation of Nephron Number in Whole Kidney using the Acid Maceration Method
08:15

Estimation of Nephron Number in Whole Kidney using the Acid Maceration Method

Published on: May 22, 2019

10.6K

Area of Science:

  • Statistics
  • Biostatistics
  • Data Science

Background:

  • Multiple imputation (MI) is a widely adopted statistical technique for addressing missing data in research.
  • The fraction of missing information (FMI) quantifies the impact of missing data, guiding analysis decisions.
  • Current estimation of FMI (γm) relies on the number of imputations (m) but lacks rigorous justification.

Purpose of the Study:

  • To evaluate the accuracy of the current sample-based FMI estimation method (γm).
  • To demonstrate the inherent overestimation of the population FMI (γ0) by γm.
  • To propose and validate improved methods for FMI estimation.

Main Methods:

  • Quantitative analysis demonstrating the relationship between the number of imputations (m) and the expected value of γm (E(γm)).
  • Theoretical evaluation showing E(γm) > γ0 for finite m.
  • Empirical validation using data from the 2012 Physician Workflow Mail Survey (National Ambulatory Medical Care Survey, USA).

Main Results:

  • The expected value of the sample FMI (E(γm)) decreases as the number of imputations (m) increases.
  • Consequently, γm systematically overestimates the true population FMI (γ0) for any finite m.
  • Three novel and improved FMI estimation methods were developed and tested.

Conclusions:

  • The current method for estimating FMI using multiple imputation is biased and overestimates the true impact of missing data.
  • Improved FMI estimation methods are necessary for accurate assessment of missing data in statistical analyses.
  • Empirical evidence supports the proposed improvements, enhancing the reliability of missing data diagnostics.