Related Experiment Video
Updated: Jun 10, 2026
08:40
Isokinetic Robotic Device to Improve Test-Retest and Inter-Rater Reliability for Stretch Reflex Measurements in Stroke Patients with Spasticity
Published on: June 12, 2019
Expected monotonicity--a desirable property for evidence measures?
Susan E Hodge1, Veronica J Vieland
1Division of Epidemiology, NY State Psychiatric Institute, Columbia School of Physicians and Surgeons, New York, NY 10032, USA. seh2 @ columbia.edu
Human Heredity
|July 29, 2010
Summary
Evidential consistency is crucial for genetic studies like genome-wide association studies (GWAS). This study finds that common evidence measures, including expected monotonicity (ExpM), often fail this consistency principle, suggesting limitations in current statistical approaches.
Area of Science:
- Genetics
- Statistical genetics
- Bioinformatics
Background:
- Evidential consistency, where evidence measures approach the true answer with more data, is vital for genetic studies.
- Previous research indicated that many statistical measures used in genetic analysis fail this principle.
- This highlights a need to evaluate and develop robust evidence measures for genetic data analysis.
Purpose of the Study:
- To investigate the expected monotonicity (ExpM) criterion for evidence measures in genetic analysis.
- To assess the performance of likelihood ratio (LR)-based evidence measures under the ExpM criterion.
- To explore alternative consistency criteria and desirable properties of evidence measures.
Main Methods:
- Utilized a simple binomial statistical model.
- Evaluated four likelihood ratio (LR)-based evidence measures.
- Examined the expected monotonicity (ExpM) criterion for these measures.
Main Results:
- Most evaluated evidence measures, including ExpM, did not consistently satisfy the expected monotonicity criterion.
- Observed counterintuitive behavior in some evidence measures.
- Demonstrated desirable properties of the simple LR and its connection to integrated LRs.
Conclusions:
- The expected monotonicity (ExpM) criterion may not be a suitable requirement for evidence measures in genetic analysis.
- Alternative consistency criteria, such as those satisfied by integrated LR and posterior probability of linkage, are more promising.
- The findings suggest a need for reassessment of evidence measurement in genetic studies.
More Related Videos
Related Concept Videos
01:21Dose Response Curve: Conventional Versus Nonmonotonic
The correlation between a drug's dosage and its impact on a biological system is a cornerstone of pharmacology and toxicology. Conventional dose–response curves, which include graded and quantal relationships, are key to this understanding. Graded dose–response curves depict the spectrum of a biological reaction to different doses within an individual, indicating that as the drug dosage increases, so does the intensity of the response. On the other hand, quantal dose–response relationships...
00:55Ordinal Level of Measurement
The way a set of data is measured is called its level of measurement. Correct statistical procedures depend on a researcher being familiar with levels of measurement. For analysis, data are classified into four levels of measurement—nominal, ordinal, interval, and ratio.
Data measured using an ordinal scale are similar to nominal scale data, but there is one major difference. The ordinal scale data can be ordered. An example of ordinal scale data is a list of the top five national parks in the...
Data measured using an ordinal scale are similar to nominal scale data, but there is one major difference. The ordinal scale data can be ordered. An example of ordinal scale data is a list of the top five national parks in the...
01:26Convergence of Sequences
A sequence is a function defined on the natural numbers that assigns a value to each index. It can be understood as an ordered list of terms generated one after another. In mathematical analysis, an important question is whether the terms of a sequence approach a single real number as the index becomes very large. When this happens, the sequence is said to converge, and the value approached is called the limit. From a graphical perspective, convergence means that the plotted terms approach a...
01:52Regression Toward the Mean
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 researchers try to extrapolate results...
00:57Weighted Mean
While taking the arithmetic, geometric, or harmonic mean of a sample data set, equal importance is assigned to all the data points. However, all the values may not always be equally important in some data sets. An intrinsic bias might make it more important to give more weightage to specific values over others.
For example, consider the number of goals scored in the matches of a tournament. While computing the average number of goals scored in the tournament, it may be more important to...
For example, consider the number of goals scored in the matches of a tournament. While computing the average number of goals scored in the tournament, it may be more important to...
01:24BIBO stability of continuous and discrete -time systems
System stability is a fundamental concept in signal processing, often assessed using convolution. For a system to be considered bounded-input bounded-output (BIBO) stable, any bounded input signal must produce a bounded output signal. A bounded input signal is one where the modulus does not exceed a certain constant at any point in time.
To determine the BIBO stability, the convolution integral is utilized when a bounded continuous-time input is applied to a Linear Time-Invariant (LTI) system.
To determine the BIBO stability, the convolution integral is utilized when a bounded continuous-time input is applied to a Linear Time-Invariant (LTI) system.