基于的最小重要差值通常对变化得分的分布敏感
Werner Vach1,2, Franziska Saxer3,4
1Department of Environmental Sciences, University of Basel, Spalenring 145, CH-4055, Basel, Switzerland. werner.vach@unibas.ch.
概括
大多数基于的方法来计算最小重要的差异 (MID) 对得分变化敏感. 未来的研究应该专注于MID计算方法,以避免这种敏感性,以便更好地进行干预比较.
科学领域:
- 生物统计学 生物统计学
- 临床试验方法论 临床试验方法论
- 健康 结果 研究 研究 结果
背景情况:
- 基于的方法被广泛用于确定结果变量的最小重要差异 (MID) 值.
- 对于MID值的各种构造方法的存在,对一致的应用提出了挑战.
- 需要最低要求来评估不同MID施工方法的充分性.
研究的目的:
- 调查建立的最小重要差异 (MID) 构造方法在多大程度上满足了对变化得分分布不敏感的要求.
- 确定MID构造方法,这些方法在研究中的特定患者干预的影响较小.
主要方法:
- 进行了一项模拟研究,以评估MID值的灵敏度.
- 评估了六种不同的MID建造方法,包括流行的和最近的方法.
- 对MID值对变化得分分布的敏感性是主要调查的度量.
主要成果:
- 在6种评估的MID构造方法中,有5种产生了对变化得分分布敏感的值.
- 这种敏感性引发了人们对从这些方法中得出的MID值的概括性和有用性的担忧.
- 对于变化得分分布不敏感的MID值可以使用基于根据变化得分的变量的条件分布的方法来实现.
结论:
- 该研究强调了在解释敏感建筑方法的MID值时需要谨慎.
- 未来对MID值的计算应该优先考虑对变化得分分布不敏感的构造方法.
- 采用可靠的MID计算方法将提高临床研究中干预措施的可比性.
相关概念视频
Significance Testing: Overview
3.4K
Significance testing is a set of statistical methods used to test whether a claim about a parameter is valid. In analytical chemistry, significance testing is used primarily to determine whether the difference between two values comes from determinate or random errors. The effect of a particular change in the measurement protocol, analyst, or sample itself can cause a deviation from the expected result. In the case of a suspected deviation/outlier, we need to be able to confirm mathematically...
3.4K
Testing a Claim about Standard Deviation
2.5K
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...
2.5K
Regression Toward the Mean
6.3K
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...
6.3K
Critical Values
6.9K
A critical value is a definite value obtained from a particular probability distribution at a predecided confidence level (or a predecided significance level) for a given population parameter. The critical value provides demarcation that separates the sample statistics that are likely to occur from the ones that are unlikely to occur based on the given probability distribution and the population parameter to be estimated. The critical value for normal distribution is obtained from the z...
6.9K
Sign Test for Matched Pairs
131
The sign test for matched pairs offers a robust method for comparing two paired samples, often for the effects of an intervention in one of them. This method is very useful in situations where the underlying distribution of the data is unknown. The test compares two related samples—often pre- and post-treatment measurements on the same subjects—to determine if there are significant differences in their median values.
To conduct the sign test, we first calculate the differences in...
To conduct the sign test, we first calculate the differences in...
131
Bonferroni Test
2.7K
The Bonferroni test is a statistical test named after Carlo Emilio Bonferroni, an Italian mathematician best known for Bonferroni inequalities. This statistical test is a type of multiple comparison test to determine which means are different than the rest. Bonferroni test can minimize the Type 1 error by reducing the significance level alpha, which otherwise increases with sample pairs.
The means of different samples are first paired in all possible combinations.
The null hypothesis of the...
The means of different samples are first paired in all possible combinations.
The null hypothesis of the...
2.7K


