The prediction of single-frequency BIA variables from individual characteristics

V Bellizzi1, L Scalfi, V Terracciano

  • 1Nephrology Unit, Lauria Hospital, Naples, Italy.

Acta Diabetologica
|November 18, 2003
PubMed

Related Concept Videos

Determination of Expected Frequency01:08

Determination of Expected Frequency

Suppose one wants to test independence between the two variables of a contingency table. The values in the table constitute the observed frequencies of the dataset. But how does one determine the expected frequency of the dataset? One of the important assumptions is that the two variables are independent, which means the variables do not influence each other. For independent variables, the statistical probability of any event involving both variables is calculated by multiplying the individual...
Biostatistics: Overview01:20

Biostatistics: Overview

Biostatistics plays a crucial role in understanding and analyzing data in healthcare and biology. Biostatisticians conduct experiments, gather evidence, and draw meaningful conclusions using statistical methods and techniques. Different variables form the foundation of biostatistical analysis, allowing researchers to understand and interpret data effectively. These variables are classified into different types, each serving a specific purpose in statistical analysis.
Discrete variables are...
Expected Frequencies in Goodness-of-Fit Tests01:19

Expected Frequencies in Goodness-of-Fit Tests

A goodness-of-fit test is conducted to determine whether the observed frequency values are statistically similar to the frequencies expected for the dataset. Suppose the expected frequencies for a dataset are equal such as when predicting the frequency of any number appearing when casting a die. In that case, the expected frequency is the ratio of the total number of observations (n) to the number of categories (k).
Multiple Allele Traits02:19

Multiple Allele Traits

For the same gene multiple alleles can interact to influence phenotypes like the shape and protein composition of an individual cells.By studying allele interactions on the molecular and cellular levels researchers can understand the resulting phenotypes and complications of human conditions like sickle cell trait, improving treatment.The ABO blood group system is a common example of multiple alleles in humans. This system includes three alleles called IA, IB, and i alleles, which combine in...
Multiple Allele Traits02:19

Multiple Allele Traits

For the same gene multiple alleles can interact to influence phenotypes like the shape and protein composition of an individual cells.By studying allele interactions on the molecular and cellular levels researchers can understand the resulting phenotypes and complications of human conditions like sickle cell trait, improving treatment.The ABO blood group system is a common example of multiple alleles in humans. This system includes three alleles called IA, IB, and i alleles, which combine in...
Variability: Analysis01:11

Variability: Analysis

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...