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Related Concept Videos

Fisher's Exact Test01:08

Fisher's Exact Test

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Fisher's exact test is a statistical significance test widely used to analyze 2x2 contingency tables, particularly in situations where sample sizes are small. Unlike the chi-squared test, which approximates P-values and assumes minimum expected frequencies of at least five in each cell, Fisher's exact test calculates the exact probability (P-value) of observing the data or more extreme results under the null hypothesis. This feature makes it especially valuable when the assumptions of...
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Behrens–Fisher Test00:57

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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.
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Spearman's Rank Correlation Test01:20

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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.
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Friedman Two-way Analysis of Variance by Ranks01:21

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Friedman's Two-Way Analysis of Variance by Ranks is a nonparametric test designed to identify differences across multiple test attempts when traditional assumptions of normality and equal variances do not apply. Unlike conventional ANOVA, which requires normally distributed data with equal variances, Friedman's test is ideal for ordinal or non-normally distributed data, making it particularly useful for analyzing dependent samples, such as matched subjects over time or repeated measures...
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F Distribution01:19

F Distribution

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The F distribution was named after Sir Ronald Fisher, an English statistician. The F statistic is a ratio (a fraction) with two sets of degrees of freedom; one for the numerator and one for the denominator. The F distribution is derived from the Student's t distribution. The values of the F distribution are squares of the corresponding values of the t distribution. One-Way ANOVA expands the t test for comparing more than two groups. The scope of that derivation is beyond the level of this...
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Identifying Statistically Significant Differences: The F-Test01:14

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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...
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The Modified Fisher Scale Lacks Interrater Reliability.

Christopher Melinosky1, Hope Kincaid2, Jan Claassen3

  • 1Department of Neurology, Lehigh Valley Health Network, 1250 S Cedar Crest Blvd, Suite 405, Allentown, PA, USA. christopher.melinosky@lvhn.org.

Neurocritical Care
|November 17, 2020
PubMed
Summary
This summary is machine-generated.

The modified Fisher scale (mFS) for cerebral vasospasm has moderate interrater reliability. Developing online training tools could improve the mFS scale

Keywords:
Aneurysmal subarachnoid hemorrhageCerebral aneurysmCerebral ischemiaCerebral vasospasmComputed tomographyComputerized tomography (CT)Intracranial hemorrhageIntracranial vasospasmNeuroimagingReproducibility of results

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Area of Science:

  • Neurology
  • Radiology
  • Clinical Research

Background:

  • The modified Fisher scale (mFS) is crucial for risk stratification of cerebral vasospasm following subarachnoid hemorrhage (SAH).
  • The mFS is a common data element used by the National Institute of Neurological Disorders and Stroke SAH Working Group.
  • Limited studies have assessed the interrater reliability of the mFS.

Purpose of the Study:

  • To assess the interrater reliability of the modified Fisher scale (mFS) among neurointensivists.
  • To identify potential areas for improvement in the application of the mFS for SAH research.

Main Methods:

  • A survey was distributed to neurointensivists via convenience and snowball sampling, including through the Neurocritical Care Society website.
  • The survey contained 15 CT scans for mFS grading, questions on scale criteria definitions, and physician demographics.
  • Kendall's coefficient of concordance was employed to evaluate interrater reliability of mFS grading.

Main Results:

  • Forty-six neurocritical care specialists participated, with high fellowship training and certification rates.
  • A significant percentage of participants demonstrated misunderstanding of mFS criteria regarding blood thickness and intraventricular blood.
  • The overall interrater reliability for the mFS was found to be moderate (Kendall's W = 0.586, p < 0.0005).

Conclusions:

  • There is only moderate agreement among raters when grading the modified Fisher scale.
  • Development of online training modules is recommended to enhance mFS reliability.
  • Standardization of mFS use in SAH research is needed.