参考值,测试复试可靠性,标准测量误差和指与鼻子测试的最小真实差异
Giovana Almeida Silva Santos1, Sara Petersen Monteiro1, Patrick Roberto Avelino2
1Department of Physical Therapy, Centro Universitário FUNCESI, Itabira, Minas Gerais, Brazil.
概括
指到鼻子测试证明了对评估运动协调的良好可靠性. 临床上显著的变化需要至少7分 (主导肢体) 或8分 (非主导肢体) 的差异.
科学领域:
- 神经学 神经学
- 康复医学 康复医学 康复医学
- 生物医学工程 生物医学工程
背景情况:
- 评估上肢运动协调在神经学和康复环境中至关重要.
- 指到鼻测试是一种常见的临床评估工具.
- 确定指到鼻测试的心理测量特性和参考值对于其准确应用至关重要.
研究的目的:
- 为了评估测试-重新测试的可靠性,标准测量误差 (SEM) 和指到鼻子测试的最小真实差异 (SRD).
- 根据性别,年龄和占主导地位的四肢分层建立指到鼻测试的规范性参考值.
主要方法:
- 165名参与者进行了手指到鼻子测试,在20秒内尽可能快地触摸目标.
- 测试-重复测试可靠性被评估在30个人超过5-7天使用类内相关系数 (ICC).
- 从每一个年龄组 (20-29岁至60岁以上) 和性别中至少收集了30名个体的参考值.
主要成果:
- 指对鼻测试表现出良好的测试重复测试可靠性 (ICC=0.92主导肢体,0.86非主导肢体).
- 发现了足够的SEM值 (<15%:9%占主导地位,11%非占主导地位的肢体).
- 确定SRD为主导肢体的7分和非主导肢体的8分.
结论:
- 指到鼻测试是评估上肢运动协调的可靠工具.
- 至少7分 (主导) 或8分 (非主导) 的变化被认为是临床上重要的最小差异.
- 基于性别,年龄和肢体优势的定义参考值将有助于临床实践和研究.
相关概念视频
Comparing Experimental Results: Student's t-Test
4.9K
The t-test is a statistical method used to compare the sample mean with a population mean or compare two means from two data sets. The test statistic is calculated from the standard deviation, mean, and number of measurements in the data set at a selected confidence interval and then compared to a table of critical values at this confidence level. If the test statistic is smaller than the critical value, the null hypothesis is accepted. In this case, we state that the difference between the...
4.9K
Identifying Statistically Significant Differences: The F-Test
3.0K
The F-test is used to compare two sample variances to each other or compare the sample variance to the population variance. It is used to decide whether an indeterminate error can explain the difference in their values. The underlying assumptions that allow the use of the F-test include the data set or sets are normally distributed, and the data sets are independent of each other. The test statistic F is calculated by dividing one variance by another. In other words, the square of one standard...
3.0K
Behrens–Fisher Test
245
The Behrens-Fisher test is a statistical method designed to address the Behrens-Fisher problem, which arises when comparing the means of two normally distributed populations with unequal variances. Unlike the Student's t-test, which assumes equal variances, the Behrens-Fisher test allows for mean comparison without this restrictive assumption. This flexibility makes it particularly valuable in scenarios where two independent samples exhibit normality but lack variance homogeneity.
This test...
This test...
245
Statistical Analysis: Overview
14.3K
When we take repeated measurements on the same or replicated samples, we will observe inconsistencies in the magnitude. These inconsistencies are called errors. To categorize and characterize these results and their errors, the researcher can use statistical analysis to determine the quality of the measurements and/or suitability of the methods.
One of the most commonly used statistical quantifiers is the mean, which is the ratio between the sum of the numerical values of all results and the...
One of the most commonly used statistical quantifiers is the mean, which is the ratio between the sum of the numerical values of all results and the...
14.3K
Uncertainty in Measurement: Accuracy and Precision
99.7K
Scientists typically make repeated measurements of a quantity to ensure the quality of their findings and to evaluate both the precision and the accuracy of their results. Measurements are said to be precise if they yield very similar results when repeated in the same manner. A measurement is considered accurate if it yields a result that is very close to the true or the accepted value. Precise values agree with each other; accurate values agree with a true value.
99.7K
Testing a Claim about Standard Deviation
2.9K
A complete procedure to test a claim about population standard deviation or population variance is explained here.
The hypothesis testing for the claim of population standard deviation (or variance) requires the data and samples to be random and unbiased. The population distribution also must be normal. There is no specific requirement on the sample size as the estimation is based on the chi-square distribution.
As a first step, the hypothesis (null and alternative) concerning the claim about...
The hypothesis testing for the claim of population standard deviation (or variance) requires the data and samples to be random and unbiased. The population distribution also must be normal. There is no specific requirement on the sample size as the estimation is based on the chi-square distribution.
As a first step, the hypothesis (null and alternative) concerning the claim about...
2.9K


