全球繁荣研究第1波人口变化分析的分析方法
R Noah Padgett1,2, Matt Bradshaw3, Ying Chen1,2
1Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA.
BMC global and public health
|April 30, 2025
概括
本研究详细介绍了全球繁荣研究 (GFS) 中分析人口变化的统计方法. 它涵盖了复杂的抽样,缺失的数据,以及对可靠研究结果的元分析.
科学领域:
- 人口统计学 人口统计学
- 统计学方法论 统计学方法论
- 心理学科学 心理学科学
背景情况:
- 全球繁荣研究 (GFS) 第一波采用了复杂的统计和设计方法来分析人口变化.
- 了解人口变化对于解释人口层面的心理和福祉数据至关重要.
更多相关视频
09:01A Method for Investigating Age-related Differences in the Functional Connectivity of Cognitive Control Networks Associated with Dimensional Change Card Sort Performance
Published on: May 7, 2014
10.1K
06:52Using Cholesky Decomposition to Explore Individual Differences in Longitudinal Relations between Reading Skills
Published on: September 17, 2019
6.2K
相关概念视频
Longitudinal Studies
81
Longitudinal studies are also widely used in other medical and social science fields. For instance, in cardiovascular research, they can monitor patients' health over decades to identify risk factors for heart disease, such as high cholesterol or smoking, and evaluate the long-term effectiveness of preventive measures. Similarly, in mental health studies, researchers might follow individuals from adolescence into adulthood to understand the development and progression of conditions like...
81
Cross-Sectional Research
11.1K
In cross-sectional research, a researcher compares multiple segments of the population at the same time. If they were interested in people's dietary habits, the researcher might directly compare different groups of people by age. Instead of following a group of people for 20 years to see how their dietary habits changed from decade to decade, the researcher would study a group of 20-year-old individuals and compare them to a group of 30-year-old individuals and a group of 40-year-old...
11.1K
Longitudinal Research
11.8K
Sometimes we want to see how people change over time, as in studies of human development and lifespan. When we test the same group of individuals repeatedly over an extended period of time, we are conducting longitudinal research. Longitudinal research is a research design in which data-gathering is administered repeatedly over an extended period of time. For example, we may survey a group of individuals about their dietary habits at age 20, retest them a decade later at age 30, and then again...
11.8K
Variability: Analysis
114
Measures of variability are statistical metrics that reveal the dispersion pattern within a dataset. They are pivotal in biostatistics, providing insights into the heterogeneity within health and biological data. Variability signifies the degree to which data points diverge from one another, helping researchers understand the potential range of values and associated uncertainty within the data.
The range is a simple measure of variability, indicating the difference between the highest and...
The range is a simple measure of variability, indicating the difference between the highest and...
114
Observational Studies
8.1K
Observational studies are a type of analytical study where researchers observe events without any interventions. In other words, the researcher does not influence the response variable or the experiment's outcome.
There are three types of observational studies – Prospective, retrospective, and cross-sectional.
Prospective Study
Prospective studies, also known as longitudinal or cohort studies, are carried out by collecting future data from groups sharing similar characteristics. One...
There are three types of observational studies – Prospective, retrospective, and cross-sectional.
Prospective Study
Prospective studies, also known as longitudinal or cohort studies, are carried out by collecting future data from groups sharing similar characteristics. One...
8.1K
Statistical Methods for Analyzing Epidemiological Data
236
Epidemiological data primarily involves information on specific populations' occurrence, distribution, and determinants of health and diseases. This data is crucial for understanding disease patterns and impacts, aiding public health decision-making and disease prevention strategies. The analysis of epidemiological data employs various statistical methods to interpret health-related data effectively. Here are some commonly used methods:
236
