Risks of using pre-event time scale and ordinal scale measurements in COVID-19 clinical trials

BACKGROUND. The article shows the results of literature search and analysis of endpoints of interventional clinical trials of phase III-IV of the treatment of hospitalized patients with coronavirus disease (COVID-19) and of its prevention. MATERIALS AND METHODS. Among 102 trials found, ordinal scales were used in 60 trials, time-to-event outcome measures were used in 54 trials, both scales – in 49 trials. Time-to-event endpoints were related to hospitalization/intensive care unit term, discontinuation of oxygen therapy, and clinical improvement standardized on ordinal scales. At the same time, the early discontinuation of oxygen therapy and the early discharge create risks to the biometric measurement. RESULTS AND DISCUSSION. Statistical calculations showed the association of the number of new COVID-19 hospital admissions per day with the percentage of free beds, but not only with the number of new coronavirus infection cases in general, the number of deaths and the number of people recovering from COVID-19 per day in different regions of Ukraine. These results may indicate that resource-dependence and organizational aspects affect the hospitalization of patients with COVID-19. CONCLUSIONS. Therefore, to ensure that the discharge or discontinuation of oxygen therapy was due solely to a positive clinical outcome, data on changes of number of beds, access to oxygen supplies as well as data relevant to determination of the desired clinical outcome (body temperature, oxygen saturation, severity of symptoms, etc.) should be collected. It is recommended to collect biomarker data after discharge, if possible.

Rating Norms Should be Calculated from Cumulative Link Mixed Effects Models

Studies which provide norms of Likert ratings typically report per-item summary statistics. Traditionally, these summary statistics comprise the mean and the standard deviation (SD) of the ratings, and the number of observations. Such summary statistics can preserve the rank order of items, but provide distorted estimates of the relative distances between items because of the ordinal nature of Likert ratings. Inter-item relations in such ordinal scales can be more appropriately modelled by cumulative-link mixed effects models (CLMMs). In a series of simulations, and with a reanalysis of an existing rating norms dataset, we show that CLMMs can be used to more accurately norm items, and can provide summary statistics analogous to the traditionally reported means and SDs, but which are disentangled from participants’ response biases. CLMMs can be applied to solve important statistical issues that exist for more traditional analyses of rating norms.

Alternative Measures of Political Efficacy: The Quest for Cross-Cultural Invariance With Ordinally Scaled Survey Items

In this paper, we examine the measurement of citizens’ beliefs that politicians and political systems are responsive (external efficacy) and that citizens see themselves sufficiently skilled to participate in politics (internal efficacy). This paper demonstrates techniques that allow researchers to establish the cross-context validity of conceptually important ordinal scales. In so doing, we show an alternative set of efficacy indicators to those commonly appearing on cross-national surveys to be more promising from a validity standpoint. Through detailed discussion and application of multi-group analysis for ordinal measures, we demonstrate that a measurement model linking latent internal and external efficacy factors performs well in configural and parameter invariance testing when applied to representative samples of respondents in the United States and Great Britain. With near full invariance achieved, differences in latent variable means are meaningful and British respondents are shown to have lower levels of both forms of efficacy than their American counterparts. We argue that this technique may be particularly valuable for scholars who wish to establish the suitability of ordinal scales for direct comparison across nations or cultures.

Understanding the ramifications of quantitative ordinal scales on accuracy of estimates of disease severity and data analysis in plant pathology

The severity of plant diseases, traditionally defined as the proportion of the plant tissue exhibiting symptoms, is a key quantitative variable to know for many diseases but is prone to error. Plant pathologists face many situations in which the measurement by nearest percent estimates (NPEs) of disease severity is time-consuming or impractical. Moreover, rater NPEs of disease severity are notoriously variable. Therefore, NPEs of disease may be of questionable value if severity cannot be determined accurately and reliably. In such situations, researchers have often used a quantitative ordinal scale of measurement—often alleging the time saved, and the ease with which the scale can be learned. Because quantitative ordinal disease scales lack the resolution of the 0 to 100% scale, they are inherently less accurate. We contend that scale design and structure have ramifications for the resulting analysis of data from the ordinal scale data. To minimize inaccuracy and ensure that there is equivalent statistical power when using quantitative ordinal scale data, design of the scales can be optimized for use in the discipline of plant pathology. In this review, we focus on the nature of quantitative ordinal scales used in plant disease assessment. Subsequently, their application and effects will be discussed. Finally, we will review how to optimize quantitative ordinal scales design to allow sufficient accuracy of estimation while maximizing power for hypothesis testing.

Career Awareness in the Study of Malay Language Program

Awareness of the career to be pursued can be present as early as childhood and can vary according to knowledge and interest. Most of today's children are more focused on achieving excellence in education, but still vague in the career that will be pursued. This situation persisted when they continued their studies at higher education and they realized that the choice of field of study was not in line with their ambitions. Usually, these children choose a field based on their results rather than settling for the required degree for the field of interest. Therefore, this study was conducted to determine the extent of students’ understanding of the scope and career prospects in Malay language. Students were distributed with a set of questionnaires containing 54 items using ordinal scales of semantic difference types. The findings of the study showed that 34(56.7%) of the students studied chose this field of study as the main choice. Students also showed a high level of knowledge about careers in the Malay language which they studied (M=3.92; SD=0.57). Students have also listed a total of 14 careers in the field of Malay language they are familiar with.

Clinicians’ heuristic assessments of radiographs compared with Kellgren-Lawrence and Ahlbäck ordinal grading: an exploratory study of knee radiographs using paired comparisons

ObjectivesOrdinal scales provide means for communicating the severity of a condition, but they are affected by cognitive biases, they introduce statistical problems and they sacrifice resolution. Clinicians discern more details than contained in scales, for example, when assessing radiographs, but clinicians’ distinctions are often based on experience-based rules of thumb, that is, heuristics. The objectives of this study are to compare clinicians’ heuristic assessments to ordinal grading, to identify case elements that influence clinicians’ judgements and to present a method for quantifying heuristic assessments.DesignClinicians were presented with 17 207 random pairs from a set of 1087 knee radiographs. For each pair, the radiograph with more severe osteoarthritis was selected. The Bradley-Terry model was used to calculate an osteoarthritis strength parameter for each radiograph. Similarly, strength parameters were determined for 12 morphological features with five additional features being considered either present or absent. All radiographs were also graded according to conventional ordinal systems (Kellgren-Lawrence and Ahlbäck). Relations between clinicians’ judgements and (1) the heuristics-based osteoarthritis strength, (2) conventional ordinal systems and (3) morphological features were investigated.ResultsReceiver operating characteristic analysis showed that the Bradley-Terry model provided a good description of clinicians’ assessments (area under the curve (AUC)=0.97, 95% CI 0.968 to 0.972). Morphological features (AUC=0.90, 95% CI 0.900 to 0.908) provided a superior description of clinicians’ choices compared with conventional ordinal systems (AUC=0.88, 95% CI 0.878 to 0.887 and AUC=0.80, 95% CI 0.796 to 0.809) for Ahlbäck and Kellgren-Lawrence, respectively). The features most strongly associated with osteoarthritis strength were medial joint space width, flattening of the medial femoral and tibial condyles, medial osteophytes and alignment.ConclusionsHeuristics-based assessments give a better distinction than conventional grading systems of knee osteoarthritis. The example presents a general approach to evaluate which features are part of experts’ heuristics. The data suggest that experts discern more details than included in conventional ordinal grading systems. Quantitative heuristic assessments may replace ordinal scales.