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Related Concept Videos

Statistical Methods for Analyzing Epidemiological Data01:25

Statistical Methods for Analyzing Epidemiological Data

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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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Cross-Sectional Research01:50

Cross-Sectional Research

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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...
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Bias in Epidemiological Studies01:29

Bias in Epidemiological Studies

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Biases can arise at various stages of research, from study design and data collection to analysis and interpretation. Recognizing and addressing these biases is essential to ensure the validity and reliability of epidemiological findings.Broadly speaking, biases in epidemiology fall into three main categories: selection bias, information bias, and confounding. A more detailed description of possible biases is:  
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Regression Toward the Mean01:52

Regression Toward the Mean

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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...
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Longitudinal Studies01:26

Longitudinal Studies

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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...
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Anorexia Nervosa01:28

Anorexia Nervosa

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Anorexia nervosa is a complex and severe eating disorder characterized by an intense fear of weight gain, an unrelenting pursuit of thinness, and a distorted body image. It often leads to dangerously low body weight relative to an individual's age and height. This disorder is marked by significant physical and psychological consequences, making it one of the most life-threatening psychiatric illnesses.
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Related Experiment Video

Updated: Mar 29, 2026

Determining Gender-Based Differences in Retinal and Choroidal Thickness in Underweight Individuals via Swept-Source Optical Coherence Tomography
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Determining Gender-Based Differences in Retinal and Choroidal Thickness in Underweight Individuals via Swept-Source Optical Coherence Tomography

Published on: December 1, 2023

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Childhood Wasting and its Determinants: A Statistical Analysis Using Cross-sectional Survey Data

Mohyaldein Salih1, Ali Satty1, Faroug A Abdalla2

  • 1Department of Mathematics, College of Science, Northern Border University, Arar, Saudi Arabia.

Journal of Epidemiology and Global Health
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PubMed
Summary

No abstract available in PubMed .

Keywords:
MalnutritionMultiple indicator cluster survey (MICS)Survey logistic regressionWastingYemen

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