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

Population Growth00:57

Population Growth

23.1K
Population size is dynamic, increasing with birth rates and immigration, and decreasing with death rates and emigration. In ideal conditions with unlimited resources, populations can increase exponentially, which plots as a J-shaped growth rate curve of population size against time. This type of curve is characteristic of newly-introduced invasive species, or populations that have suffered catastrophic declines and are rebounding.
23.1K
Testing a Claim about Population Proportion01:24

Testing a Claim about Population Proportion

2.9K
A complete procedure for testing a claim about a population proportion is provided here.
There are two methods of testing a claim about a population proportion: (1) Using the sample proportion from the data where a binomial distribution is approximated to the normal distribution and (2) Using the binomial probabilities calculated from the data.
The first method uses normal distribution as an approximation to the binomial distribution. The requirements are as follows: sample size is large...
2.9K
Sample Proportion and Population Proportion01:20

Sample Proportion and Population Proportion

5.6K
Collecting samples or responses from an entire population takes significant time and effort, so a researcher collects responses from only a sample of that population. Suppose a study needs to collect information about a specific mobile application. After sample collection, the researcher analyzes the data and discovers that most individuals in the sample use that specific mobile application. The sample proportion measures the number of individuals in a sample who either use or don't use the...
5.6K
Analysis of Population Pharmacokinetic Data01:12

Analysis of Population Pharmacokinetic Data

984
Analysis of population pharmacokinetic data involves studying the behavior of drugs within diverse populations to understand their pharmacokinetic parameters. Traditional pharmacokinetic methods typically involve collecting samples from a few individuals and estimating these parameters. While these methods are commonly used, they have limitations in capturing the variability in drug response among individuals or heterogeneous populations. Population pharmacokinetics is employed to address these...
984
Exponential Equations for Modeling Growth01:26

Exponential Equations for Modeling Growth

457
Exponential models are essential for describing rapid, multiplicative changes in natural systems, such as population growth. When a population doubles at regular intervals, the process can be modeled using a suitable base. For instance, a bacterial culture that doubles every three hours follows the model n(t)=n0⋅2t/3, where n(t) is the population at the time t.A more general model uses the natural base e, especially for continuous growth. This takes the form n(t)=n0⋅ert, where r is...
457
Regression Toward the Mean01:52

Regression Toward the Mean

6.3K
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...
6.3K

You might also read

Related Articles

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

Sort by
Same journal

Research Note on the Role of Infertility and Medically Assisted Reproduction on the Realization of Ideal Family Size in Japan.

Demography·2026
Same journal

Extreme Weather and Mortality of Vulnerable Urban Populations: An Examination of Temperature and Unclaimed Deaths in New York City.

Demography·2026
Same journal

Overlooked Potential? Childcare Services and Ukrainian Refugee Mothers in Germany.

Demography·2026
Same journal

Effect of First Births on Women's Employment in a Low-Income Context: Research Note Using Panel Data From Nepal.

Demography·2026
Same journal

Decomposing Differences in Cohort Health Expectancy by Cause and Age With Longitudinal Data.

Demography·2026
Same journal

Wildfires and Birth Outcomes: Evidence From Spain.

Demography·2026

Related Experiment Video

Updated: Apr 25, 2026

Predicting the Effectiveness of Population Replacement Strategy Using Mathematical Modeling
20:36

Predicting the Effectiveness of Population Replacement Strategy Using Mathematical Modeling

Published on: July 4, 2007

8.2K

Accounting for Race Response Change in Population Projections: A Research Note.

Carolyn A Liebler1

  • 1Department of Sociology, University of Minnesota, Minneapolis, MN, USA.

Demography
|April 24, 2026
PubMed
Summary

Realistic population projections are challenging for some race groups. This study introduces a new method accounting for race response changes, projecting significant growth for the American Indian and Alaska Native population.

Keywords:
American Indian and Alaska NativeCensusCohort component projection modelError of closureRace response change

More Related Videos

Using the Race Model Inequality to Quantify Behavioral Multisensory Integration Effects
08:13

Using the Race Model Inequality to Quantify Behavioral Multisensory Integration Effects

Published on: May 10, 2019

6.0K
Inverse Probability of Treatment Weighting Propensity Score using the Military Health System Data Repository and National Death Index
06:55

Inverse Probability of Treatment Weighting Propensity Score using the Military Health System Data Repository and National Death Index

Published on: January 8, 2020

14.3K

Related Experiment Videos

Last Updated: Apr 25, 2026

Predicting the Effectiveness of Population Replacement Strategy Using Mathematical Modeling
20:36

Predicting the Effectiveness of Population Replacement Strategy Using Mathematical Modeling

Published on: July 4, 2007

8.2K
Using the Race Model Inequality to Quantify Behavioral Multisensory Integration Effects
08:13

Using the Race Model Inequality to Quantify Behavioral Multisensory Integration Effects

Published on: May 10, 2019

6.0K
Inverse Probability of Treatment Weighting Propensity Score using the Military Health System Data Repository and National Death Index
06:55

Inverse Probability of Treatment Weighting Propensity Score using the Military Health System Data Repository and National Death Index

Published on: January 8, 2020

14.3K

Area of Science:

  • Demography
  • Population Studies
  • Sociology

Background:

  • Traditional demographic models struggle with accurate population projections for certain racial groups.
  • The Census Bureau's projections for the American Indian and Alaska Native (AIAN) population are notably underestimated.
  • Existing cohort component models fail to account for race response changes.

Purpose of the Study:

  • To introduce a novel strategy for incorporating net race response change into population projection models.
  • To improve the accuracy of demographic forecasts for racial and ethnic groups.
  • To provide a more realistic projection for the American Indian and Alaska Native population.

Main Methods:

  • Development of a modified cohort component model.
  • Inclusion of a "net race response change" variable.
  • Application of the model to the racially identified AIAN population in the United States (2020-2050).

Main Results:

  • The revised model projects the AIAN population to grow from 9.7 million in 2020 to 19.8 million by 2050.
  • This revised projection is significantly higher than previous estimates.
  • The study highlights the impact of race response change on population dynamics.

Conclusions:

  • Accounting for race response change is crucial for accurate demographic projections.
  • The proposed methodology offers a more realistic approach to forecasting population trends for diverse groups.
  • Future demographic research should integrate race response dynamics for improved accuracy.