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Updated: May 20, 2025

Sequencing of Bacterial Microflora in Peripheral Blood: our Experience with HIV-infected Patients
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Sequencing of Bacterial Microflora in Peripheral Blood: our Experience with HIV-infected Patients

Published on: June 11, 2011

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意大利和移民居民死亡率的社会经济不平等:基于人口的纵向研究

Martina Ventura1, Alessio Petrelli1, Anteo Di Napoli1

  • 1National Institute for Health, Migration and Poverty (INMP), Italy.

Journal of migration and health
|March 24, 2025
PubMed
概括

社会经济死亡率梯度在意大利人中很强,但在来自高移民压力国家的移民中较弱. 这凸显了针对移民健康的具体风险和文化因素考虑的定制社会政策的必要性.

关键词:
教育水平 教育水平移民 移民 移民意大利意大利意大利意大利意大利意大利死亡率 死亡率 死亡率职业类别 职业类别 职业类别 职业类别社会经济不平等社会经济不平等

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Statistical Methods for Analyzing Epidemiological Data

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:
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Comparing the Survival Analysis of Two or More Groups

Survival analysis is a cornerstone of medical research, used to evaluate the time until an event of interest occurs, such as death, disease recurrence, or recovery. Unlike standard statistical methods, survival analysis is particularly adept at handling censored data—instances where the event has not occurred for some participants by the end of the study or remains unobserved. To address these unique challenges, specialized techniques like the Kaplan-Meier estimator, log-rank test, and...
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Actuarial Approach

The actuarial approach, a statistical method originally developed for life insurance risk assessment, is widely used to calculate survival rates in clinical and population studies. This method accounts for participants lost to follow-up or those who die from causes unrelated to the study, ensuring a more accurate representation of survival probabilities.
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Introduction To Survival Analysis

Survival analysis is a statistical method used to study time-to-event data, where the "event" might represent outcomes like death, disease relapse, system failure, or recovery. A unique feature of survival data is censoring, which occurs when the event of interest has not been observed for some individuals during the study period. This requires specialized techniques to handle incomplete data effectively.
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Kaplan-Meier Approach01:24

Kaplan-Meier Approach

The Kaplan-Meier estimator is a non-parametric method used to estimate the survival function from time-to-event data. In medical research, it is frequently employed to measure the proportion of patients surviving for a certain period after treatment. This estimator is fundamental in analyzing time-to-event data, making it indispensable in clinical trials, epidemiological studies, and reliability engineering. By estimating survival probabilities, researchers can evaluate treatment effectiveness,...
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Truncation in Survival Analysis

Truncation in survival analysis refers to the exclusion of individuals or events from the dataset based on specific criteria related to the time of the event. This exclusion can happen in two primary forms: left truncation and right truncation.
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