Topic
Ridit scoring
About: Ridit scoring is a research topic. Over the lifetime, 95 publications have been published within this topic receiving 1564 citations.
Papers published on a yearly basis
Papers
TL;DR: In this article, a ridit analysis of data from the Cornell Automotive Crash Injury Research Program (ACIR) is presented to illustrate the problems that come up in actual studies, problems ranging from difficulties due to peculiarities and imperfections of the basic data to questions of presentation and interpretation of the results.
Abstract: In many scientific studies in the biological and behavioral sciencesprobably in a majority of such studies-the scientist has to work with a response variable which falls in the "borderland" between dichotomous classifications (e.g. "lived"-"died," "yes"-"no") and refined measurement systems (i.e. measurements which are highly reproducable at different times or at different places). Sometimes the response variable is a subjective scale (i.e. a well ordered series of categories such as "minor," "moderate," "severe"). At other times the response variable takes numerical values but the measurement system is heavily dependent on the quality of experimental material, details of protocol, or the technical skill of the scientist. These "borderland" response variables may not be adequately analysed by the chi-square family of statistical methods and at the same time the t-test family of techniques may not be appropriate. In this situation ridit analysis may serve as a "missing link" between the two traditional families of statistical methods. This paper is addressed to scientists who are working with "borderland" response variables. It will contain no mathematical derivations (these will appear in a subsequent paper [1]). Its purpose is to explain and illustrate how to use ridit analysis in a scientific study. For this purpose a ridit analysis of data from the Cornell Automotive Crash Injury Research Program (ACIR) will be presented. This material will serve to illustrate the various problems that come up in actual studies, problems ranging from difficulties due to peculiarities and imperfections of the basic data to questions of presentation and interpretation of the results. The ACIR analysis will also show the role of ridit analysis in achieving the objectives of a scientific study. In this particular case the analysis throws light on a major public health problem-the carnage due to auto accidents. Nowadays the catalogue of statistical methods is so very extensive that a working scientist is somewhat less than overjoyed at the prospect
648 citations
TL;DR: Ridit analysis is presented as an appropriate method of analyzing dental clinical data which fall somewhere between the purely categorical (e.g., improved vs. not improved) and the bona fide quantitative scales of measurement.
Abstract: Ridit analysis is presented as an appropriate method of analyzing dental clinical data which fall somewhere between the purely categorical (e.g., improved vs. not improved) and the bona fide quantitative (e.g., mg % salivary calcium) scales of measurement. The key feature of the method is the estimation of the probability that a randomly-selected patient from one treatment group is "better-off" than a randomly-selected patient from another. Methods are presented for testing statistical significance and constructing confidence intervals. The method is illustrated on data from a comparative clinical trial of ibuprofen, aspirin and placebo in the relief of post-extraction pain. There were no significant differences in efficacy among the active treatments, but each was significantly superior to placebo.
83 citations
1 Jan 2007
TL;DR: Two methods, i.e. grey relational analysis and RIDIT analysis, which can be used to analyse data from Likert scale surveys are illustrated and it is found that the results derived from applying the aforementioned methods are very much consistent with each other.
Abstract: Likert scale is one of the most frequently used measures in social sciences to gather data on attitudes, perceptions, values, intentions, habits and behaviour changes. This paper illustrates two methods, i.e. grey relational analysis and RIDIT analysis, which can be used to analyse data from Likert scale surveys. It is found that the results derived from applying the aforementioned methods are very much consistent with each other. Characteristics of the two methods and guidelines for choosing between the two for data analysis are also discussed in this paper. Mathematics Subject Classification: 62P25
77 citations
TL;DR: PARCAT is a computer program which implements alternative tests for average partial association in three-way contingency tables within the framework of the product multiple hypergeometric probability model.
68 citations
TL;DR: It is safe to regard a drop of more than two rows with head moving as abnormal and the DIE test has the potential to delineate some patients who have no caloric reduction.
Abstract: The Dynamic Illegible E (DIE) test measures visual acuity with head held still while reading a specially designed visual acuity chart of E's. The head is then moved passively and the change in visual acuity is recorded. The DIE test has previously been shown to be very useful for assessing patients with aminoglycoside ototoxicity. In the present study, statistical analysis using multiple regression showed that the degree of abnormality in the DIE test during horizontal and vertical head movement was correlated with the degree of caloric reduction. Ridit analysis allows comparison between a number of naturally ordered categories. The ridit analysis showed significant differences between groups of patients with varying degrees of caloric reduction. There was also a significant difference in DIE test scores between a group of normals with no history of otoneurological complaint and an age- and sex-matched population of dizzy patients with normal caloric results. As none of our 110 normal patients had more than a one row drop while reading the DIE test with head moving, we feel that it is safe to regard a drop of more than two rows with head moving as abnormal. Perhaps even a mild caloric reduction represents relatively severe vestibular damage and the DIE test has the potential to delineate some patients who have no caloric reduction.
64 citations
Related Topics (5)
Performance Metrics
| Year | Papers |
|---|---|
| 2021 | 3 |
| 2020 | 5 |
| 2019 | 4 |
| 2018 | 3 |
| 2017 | 8 |
| 2016 | 3 |