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

Guidelines For Measuring Vital Signs01:19

Guidelines For Measuring Vital Signs

2.9K
Following these guidelines can help nurses accurately measure vital signs, assess changes in patient conditions, and provide timely treatment when necessary. Adhering closely to the guidelines ensures the accuracy and reliability of the results.
Before taking a patient's vital signs, a nurse would consider and assess the patient's comfort level and ensure appropriate equipment is available.
2.9K
The Integrated Rate Law: The Dependence of Concentration on Time02:39

The Integrated Rate Law: The Dependence of Concentration on Time

42.6K
While the differential rate law relates the rate and concentrations of reactants, a second form of rate law called the integrated rate law relates concentrations of reactants and time. Integrated rate laws can be used to determine the amount of reactant or product present after a period of time or to estimate the time required for a reaction to proceed to a certain extent. For example, an integrated rate law helps determine the length of time a radioactive material must be stored for its...
42.6K
Chronopharmacokinetics: Time-Dependent Pharmacokinetics01:20

Chronopharmacokinetics: Time-Dependent Pharmacokinetics

416
Chronopharmacokinetics studies the temporal change in drug absorption and elimination. These changes can be cyclical or non-cyclical. Cyclical changes occur over a regular interval, while non-cyclical changes occur over a longer, irregular period.
Time-dependent pharmacokinetics refers to non-cyclical changes in drug rate processes over a period of time. It can lead to nonlinear pharmacokinetics, where the relationship between drug concentration and time is not proportional. Non-cyclical...
416
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

209
Body: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...
209
Bioavailability Study Design: Single Versus Multiple Dose Studies01:11

Bioavailability Study Design: Single Versus Multiple Dose Studies

249
Bioavailability studies are essential for understanding how a drug is absorbed, distributed, metabolized, and excreted in the body. These studies assess the extent and rate at which the active pharmaceutical agent becomes available at the site of action. The design of bioavailability studies can involve single-dose or multiple-dose regimens, each with distinct advantages and limitations.Single-dose studies are the preferred approach due to their simplicity and reduced drug exposure for...
249
Theory of Attribution II: Kelley's Covariation Theory01:29

Theory of Attribution II: Kelley's Covariation Theory

615
Attribution theory plays a crucial role in social psychology, helping to explain how individuals interpret the causes of behavior. One prominent model within this field is Harold Kelley's covariation theory, which provides a systematic approach to determining whether internal traits or external circumstances drive a person's actions. The model posits that individuals rely on three key types of information—consensus, consistency, and distinctiveness—to make these judgments.Consensus:...
615

You might also read

Related Articles

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

Sort by
Same author

Predicting clinical progression in patients with relapsing remitting multiple sclerosis retrospectively using a myelin content proxy.

Multiple sclerosis and related disorders·2026
Same author

The Experiences of Family Caregivers Whose Relative Is Relocating From a Regular Nursing Home to an Innovative Living Arrangement: A Qualitative Study.

Scandinavian journal of caring sciences·2026
Same author

Experiences From Older Patients Regarding Their Transition From the Acute Hospital to Their Home: A Phenomenological Study.

International journal of integrated care·2026
Same author

"It's about better doctors": exploring the purpose, structure, and function of competency committees in medical school.

Academic medicine : journal of the Association of American Medical Colleges·2026
Same author

Inside Their Minds: A Multi-Institutional Exploration into the Decision-Making of Medical School Competency Committee Members.

Perspectives on medical education·2026
Same author

Hierarchical imputation of categorical variables in the presence of systematically and sporadically missing data.

Research synthesis methods·2026

Related Experiment Video

Updated: Feb 8, 2026

Measurements of CO2 Fluxes at Non-Ideal Eddy Covariance Sites
09:05

Measurements of CO2 Fluxes at Non-Ideal Eddy Covariance Sites

Published on: June 24, 2019

8.4K

Guidelines for multiple imputations in repeated measurements with time-dependent covariates: a case study.

Frans E S Tan1, Shahab Jolani1, Hilde Verbeek2

  • 1Department of Methodology and Statistics, CAPHRI Care and Public Health Research Institute, Maastricht University, Maastricht, The Netherlands.

Journal of Clinical Epidemiology
|July 3, 2018
PubMed
Summary

Multiple imputation effectively handles missing data in longitudinal studies, especially with time-varying variables. This method offers a robust solution for complex datasets, improving data analysis accuracy.

Keywords:
Longitudinal designMultiple imputationObservational studyOverparametrizationPartly missing time-varying covariatesR-MICE

More Related Videos

Real Time and Repeated Measurement of Skeletal Muscle Growth in Individual Live Zebrafish Subjected to Altered Electrical Activity
11:41

Real Time and Repeated Measurement of Skeletal Muscle Growth in Individual Live Zebrafish Subjected to Altered Electrical Activity

Published on: June 16, 2022

2.5K
A Protocol for the Use of Remotely-Supervised Transcranial Direct Current Stimulation tDCS in Multiple Sclerosis MS
08:18

A Protocol for the Use of Remotely-Supervised Transcranial Direct Current Stimulation tDCS in Multiple Sclerosis MS

Published on: December 26, 2015

18.1K

Related Experiment Videos

Last Updated: Feb 8, 2026

Measurements of CO2 Fluxes at Non-Ideal Eddy Covariance Sites
09:05

Measurements of CO2 Fluxes at Non-Ideal Eddy Covariance Sites

Published on: June 24, 2019

8.4K
Real Time and Repeated Measurement of Skeletal Muscle Growth in Individual Live Zebrafish Subjected to Altered Electrical Activity
11:41

Real Time and Repeated Measurement of Skeletal Muscle Growth in Individual Live Zebrafish Subjected to Altered Electrical Activity

Published on: June 16, 2022

2.5K
A Protocol for the Use of Remotely-Supervised Transcranial Direct Current Stimulation tDCS in Multiple Sclerosis MS
08:18

A Protocol for the Use of Remotely-Supervised Transcranial Direct Current Stimulation tDCS in Multiple Sclerosis MS

Published on: December 26, 2015

18.1K

Area of Science:

  • Statistics
  • Biostatistics
  • Longitudinal Data Analysis

Background:

  • Missing data is a common challenge in observational studies with repeated measurements.
  • Standard methods may be insufficient for complex missing data patterns, particularly with time-varying covariates.

Purpose of the Study:

  • To provide guidelines for managing missing data in repeated measures.
  • To address practical aspects of imputation for complex, partly missing time-varying variables.

Main Methods:

  • Utilized the Maastricht Study as a case study with 115 participants and 84 momentary assessments.
  • Employed a multiple imputation procedure with restrictions on variable relationships over time.
  • Leveraged the R-MICE statistical package for handling complex missing data.

Main Results:

  • Multiple imputation demonstrated superiority in addressing missing observations in both outcomes and independent variables.
  • The R-MICE package facilitated imputation for complex datasets, overcoming limitations of other software.

Conclusions:

  • Direct likelihood approaches suffice for missing outcome data but not for partly missing time-varying covariates.
  • Multiple imputation is essential for valid inferences when dealing with missing time-varying covariates and repeated measurements in observational studies.