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相关概念视频

Coefficient of Correlation01:12

Coefficient of Correlation

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The correlation coefficient, r, developed by Karl Pearson in the early 1900s, is numerical and provides a measure of strength and direction of the linear association between the independent variable x and the dependent variable y.
If you suspect a linear relationship between x and y, then r can measure how strong the linear relationship is.
What the VALUE of r tells us:
The value of r is always between –1 and +1: –1 ≤ r ≤ 1.
The size of the correlation r indicates the...
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Calculating and Interpreting the Linear Correlation Coefficient01:11

Calculating and Interpreting the Linear Correlation Coefficient

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The correlation coefficient, r, developed by Karl Pearson in the early 1900s, is numerical and provides a measure of strength and direction of the linear association between the independent variable, x, and the dependent variable, y. Hence, it is also known as the Pearson product-moment correlation coefficient. It can be calculated using the following equation:
5.9K
Correlation01:09

Correlation

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In statistics, two variables are said to be correlated if the values of one variable are associated with the other variable. Depending on the relationship between two variables, correlation can be of three types– positive correlation, negative correlation, and zero correlation.
Two variables, for example, a and b, are said to be positively correlated if both variables move in the same direction. In other words, a positive correlation exists between two variables, a and b, if:
11.6K
Correlations02:20

Correlations

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Correlation means that there is a relationship between two or more variables (such as ice cream consumption and crime), but this relationship does not necessarily imply cause and effect. When two variables are correlated, it simply means that as one variable changes, so does the other. We can measure correlation by calculating a statistic known as a correlation coefficient. A correlation coefficient is a number from -1 to +1 that indicates the strength and direction of the relationship between...
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Wilcoxon Signed-Ranks Test for Matched Pairs01:09

Wilcoxon Signed-Ranks Test for Matched Pairs

79
The Wilcoxon signed-rank test for matched pairs evaluates the null hypothesis by combining the ranks of differences with their signs. It essentially tests whether the median of the differences in a population of matched pairs is zero. Since the test incorporates more information than the sign test, it generally yields more trustable conclusions. This test also does not require the data to follow a normal distribution, but two conditions must be met for it to be applicable: (1) the data must...
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Spearman's Rank Correlation Test01:20

Spearman's Rank Correlation Test

656
Spearman's rank correlation test, also known as Spearman's rho, is a nonparametric method for assessing the strength and direction of association between two variables. This test is particularly valuable when the data distribution is unknown or when the assumption of normality does not hold. Named after the English psychologist and statistician Dr. Charles Edward Spearman, it serves as the nonparametric counterpart to Pearson's correlation coefficient.
Spearman's test calculates...
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一个基于人口的血红蛋白A1c和血红蛋白水平之间的相关性分析.

Tingyu Zhang1,2, Tianyi Shi3, Min Cao1

  • 1Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.

Journal of diabetes
|February 21, 2025
PubMed
概括

糖化血红素 (HbA1c) 水平与血红素的关系因性别和年龄而异. 这项研究阐明了这些复杂的关联,影响了糖尿病管理策略.

关键词:
雌激素 雌激素 雌激素 是一种血红蛋白 血红蛋白 是一个血红蛋白A1cc是什么意思

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科学领域:

  • 内分泌学 在内分泌学.
  • 临床化学 临床化学
  • 老年学是一门学科.

背景情况:

  • 糖化血红蛋白 (HbA1c) 对于监测糖尿病至关重要,但它的准确性可能会受到血红蛋白水平和红细胞寿命的影响.
  • 以前的研究还没有完全阐明HbA1c和血红蛋白之间的复杂关系.
  • 了解这种联系对于准确的血糖控制评估至关重要.

研究的目的:

  • 调查不同年龄和性别群体HbA1c和血红蛋白水平之间的相关性.
  • 为了澄清这些关键生物标志物之间的复杂,潜在的非线性关联.
  • 为了确定血红蛋白的性别特定的参考间隔.

主要方法:

  • 分析了中国西南地区217,991名参与者 (20-69岁) 的数据.
  • 标准化HbA1c和血红蛋白的测量.
  • 应用通用添加模型 (GAM) 来分析非线性关系并调整混因素.

主要成果:

  • 观察到HbA1c和血红蛋白之间存在显著的性别特异关联.
  • 在男性中,HbA1c随着血红蛋白的增加而下降.
  • 在女性中,更年期前 (≤45岁) 呈现负相关性,而更年期后 (>45岁) 呈现正相关性;HbA1c随着年龄的增长而增加,特别是在45岁以上的女性中.

结论:

  • HbA1c和血红蛋白之间的关系受到性别和年龄的显著影响.
  • 与雌激素相关的代谢变化可能会影响HbA1c水平,特别是在绝经后的女性中.
  • 这些发现对老年妇女的糖尿病管理和激素治疗考虑有影响.