OBJECTIVE: Temporomandibular disorder (TMD) is the term used to describe a pathology (dysfunction and pain) in the masticatory muscles and temporomandibular joint (TMJ). There is an apparent upward trend in the publication of dental research and a need to continually improve the quality of research. Therefore, this study was conducted to analyse the use of sample size and effect size calculations in a TMD randomised controlled trial.
METHODS: The period was restricted to the full 5 years, i.e., papers published in 2019, 2020, 2021, 2022, and 2023. The filter article type-\"Randomized Controlled Trial\" was used. The studies were graded on a two-level scale: 0-1. In the case of 1, sample size (SS) and effect size (ES) were calculated.
RESULTS: In the entire study sample, SS was used in 58% of studies, while ES was used in 15% of studies.
CONCLUSIONS: Quality should improve as research increases. One factor that influences quality is the level of statistics. SS and ES calculations provide a basis for understanding the results obtained by the authors. Access to formulas, online calculators and software facilitates these analyses. High-quality trials provide a solid foundation for medical progress, fostering the development of personalized therapies that provide more precise and effective treatment and increase patients\' chances of recovery. Improving the quality of TMD research, and medical research in general, helps to increase public confidence in medical advances and raises the standard of patient care.

Recycling agents provide better additions of reclaimed asphalt pavement (RAP) in the production of new asphalt mixtures. Alternative and residual materials that have the potential as asphalt binder viscosity reducers have gained visibility in the field of paving due to the perspective of circular economy in recycled mixtures. Soybean oil sludge fatty acid is a material produced from soybean oil sludge, a waste generated in the soybean oil refining step. Thus, this paper investigated the physical, chemical, and rheological effects of the asphalt binder PG 64-XX modified by the fatty acid of soybean oil sludge in the contents of 6% and 7% by weight of the binder. The modified binder samples were submitted to penetration tests, softening point, rotational viscosity, performance grade (PG), before and after short-term aging (RTFO), and multiple stress creep and recovery (MSCR). A control asphalt mixture and recycled asphalt mixtures produced with 40% RAP and fatty acid-modified binders were subjected to tensile strength, induced moisture damage, resilient modulus, and fatigue life. A Student\'s t statistical test verified the significance of the data, as well as the estimation of production costs of these asphalt mixtures. The use of the fatty acid significantly reduced the stiffness and viscosity of the control asphalt binder, decreasing the mixing temperatures at 14 °C and 17 °C to 6% and 7%, respectively. Using higher fatty acid contents from soybean oil sludge significantly improved the performance of recycled mixtures in tensile strength, moisture damage, and fatigue life. The production cost of recycled asphalt mixtures was lower than that of the control mixture.

A general framework is set up to study the asymptotic properties of the intent-to-treat Wilcoxon-Mann-Whitney test in randomized experiments with nonignorable noncompliance. Under location-shift alternatives, the Pitman efficiencies of the intent-to-treat Wilcoxon-Mann-Whitney and [Formula: see text] tests are derived. It is shown that the former is superior if the compliers are more likely to be found in high-density regions of the outcome distribution or, equivalently, if the noncompliers tend to reside in the tails. By logical extension, the relative efficiency of the two tests is sharply bounded by least and most favourable scenarios in which the compliers are segregated into regions of lowest and highest density, respectively. Such bounds can be derived analytically as a function of the compliance rate for common location families such as Gaussian, Laplace, logistic and [Formula: see text] distributions. These results can help empirical researchers choose the more efficient test for existing data, and calculate sample size for future trials in anticipation of noncompliance. Results for nonadditive alternatives and other tests follow along similar lines.

An overwhelming majority of articles in psychology compare means, often between multiple groups. However, sometimes we do not know the exact group membership, but only a probability to be in one of the groups. Such information may come from classifiers trained on other datasets, prevalence of group memberships for some parts of the sample, multi-level situations where the group membership is only known as a ratio in an upper level, or expert ratings (e.g., whether a person has a pathological condition or not). We present a simple method that allows to compare group means in the absence of exact knowledge about group membership and investigate the loss of information depending on the probability values theoretically and in a large-scale simulation.

Lateral canthotomy is a low incidence but high-risk procedure that is expected to be within the scope of practice for every emergency department physician. Due to the low incidence of this procedure, training residents may prove difficult and costly. The purpose of this study was to evaluate a synthetic, low-fidelity, low-cost, eye model to train and improve confidence in performing a lateral canthotomy. This is the first study that we know of that uses a 5 point Likert scale, two-sample t-test to assess the value of using such a model for lateral canthotomy training. Our results showed that using such a model for the training of lateral canthotomy did in fact improve the competence and confidence of performing this procedure.

With the conventional 2D exam of clinical cases, the diagnosis is penalized by the lack of data, not only for vertical or transverse or asymmetrical problems, but for classical cases of anteroposterior dysharmonies. In these cases, the effectively used parameter, ANB angle, seems insufficient. So the authors elaborated a 3D biometry tool. The program of morphological analysis is able to deliver a complete description of dysharmony, supported by Cone Beam data capture. In the first part of this article the authors present the foundation of the model: anatomical reference, skeletal landmarks, teeth location by inertia matrix calculus, parameters, diagnosis and aid to treatment plan. The second part is the presentation, step by step, of the program in function, analyzing a great case of Class II hyperdivergent, border line surgery. All along the diagnosis way, the authors make the assistant discover all the documents given by the computer about complete 3D diagnosis and aid to treatment plan.

We could study Cone Beam documents of patients consulting in ORL with standard Angle Class I occlusion (45 ND), patients consulting in orthodontics with an orthodontic Class II (51 APNS) and patients with a surgical Class II (83 APS). The used 3D biometry calculates systematically a 164 set of parameters able to take into account all kinds of disharmonies; among which 38 parameters are specifically devoted to anterior-posterior \"off asymmetry\" pathologies. Then the specific Artificial Intelligence (AI) programs treat morphological data and give textual diagnoses. Analysis of the global sample aims to control the efficiency, separating different sub-samples one each other: t test appreciates efficiency of each parameter to recognize clinical sub-sample. The correlation coefficient, r, between each parameter and pseudo Angle molars Class II (GMMy-Gmmy) give the importance of its tie with Class II pathology. Presentation of parameters medium values in each sub-group gives the medium profiles. By direct comparison of patient\'s parameters values with medium profile, it is possible to locate patient\'s pathology. So we can take in account new parameters like arches upper/lower gap, anterior bases upper/lower gap, compensatingparameters... It is then possible to make more secure the clinical decision.

While the applied psychology community relies on statistics to assist drawing conclusions from quantitative data, the methods being used mostly today do not reflect several of the advances in statistics that have been realized over the past decades. We show in this paper how a number of issues with how statistical analyses are presently executed and reported in the literature can be addressed by applying more modern methods. Unfortunately, such new methods are not always supported by widely available statistical packages, such as SPSS, which is why we also introduce a new software platform, called ILLMO (for Interactive Log-Likelihood MOdeling), which offers an intuitive interface to such modern statistical methods. In order to limit the complexity of the material being covered in this paper, we focus the discussion on a fairly simple, but nevertheless very frequent and important statistical task, i.e., comparing two experimental conditions.

Objective. This study aimed to research the impact that a coal mine lighting environment has on human safety behavior in an underground coal mine. Methods. We built a coal mine lighting simulation experiment system including both general lighting and local lighting divided into six different illumination gradients (0, 10, 30, 50, 75 and 100 lx) to test and analyze the effects of general illumination gradients on human fatigue, attention, reaction and eye-hand coordination with SPSS version 22.0. Results. Illuminance has a significant effect on human fatigue, attention, reaction ability and eye-hand coordination ability. Specifically, human fatigue is negatively correlated and the other indicators are positively correlated with the increase of illuminance. Notably, attention distribution ability seems to be most significantly influenced by illuminance according to this study, followed by human fatigue, reaction and eye-hand coordination ability. Conclusion. The results of the study indicate that illumination of the general lighting environment is expected to be controlled at a gradient of at least 50-75 lx or above in the coal mine environment where there is both general lighting and local lighting to reduce the incidence of accidents.

The seasonality of demographic data has been of great interest. It depends mainly on the climatic conditions, and the findings may vary from study to study. Commonly, the studies are based on monthly data. The population at risk plays a central role. For births or deaths over short periods, the population at risk is proportional to the lengths of the months. Hence, one must analyze the number of births (and deaths) per day. If one studies the seasonality of multiple maternities, the population at risk is the total monthly number of confinements and the number of multiple maternities in a given month must be compared with the monthly number of all maternities. Consequently, when one considers the monthly rates of multiple maternities, the monthly number of births is eliminated and one obtains an unaffected seasonality measure of the rates. In general, comparisons between the seasonality of different data sets presuppose standardization of the data to indices with common means, mainly 100. If one assumes seasonality as \'non-flatness\' throughout a year, a chi-squared test would be an option, but this test calculates only the heterogeneity and the same test statistic can be obtained for data sets with extreme values occurring in consecutive months or in separate months. Hence, chi-squared tests for seasonality are weak because of this arbitrariness and cannot be considered a model test. When seasonal models are applied, one must pay special attention to how well the applied model fits the data. If the goodness of fit is poor, nonsignificant models obtained can erroneously lead to statements that the seasonality is slight, although the observed seasonal fluctuations are marked. In this study, we investigate how the application of seasonal models can be applied to different demographic variables.