Sample size and its evolution in research

Objective: Sample size is one of the crucial and basic steps involved in planning any study. This article aims to study the evolution of sample size across the years from hundreds to thousands to millions and to a trillion in the near future (H-K-M-B-T). It also aims to understand the importance of sampling in the era of big data. Study Design - Primary Outcome measure, Methods, Results, and Interpretation: A sample size which is too small will not be a true representation of the population whereas a large sample size will involve putting more individuals at risk. An optimum sample size needs to be employed to identify statistically significant differences if they exist and obtain scientifically valid results. The design of the study, the primary outcome, sampling method used, dropout rate, effect size, power, level of significance, and standard deviation are some of the multiple factors which affect the sample size. All these factors need to be taken into account while calculating the sample size. Many sources are available for calculating sample size. Discretion needs to be used while choosing the right source. The large volumes of data and the corresponding number of data points being analyzed is redefining many industries including healthcare. The larger the sample size, the more insightful information, identification of rare side effects, lesser margin of error, higher confidence level, and models with more accuracy. Advances in the digital era have ensured that we do not face most of the obstacles faced traditionally with regards to statistical sampling, yet it has its own set of challenges. Hence, considerable efforts and time should be invested in selecting sampling techniques which are appropriate and reducing sampling bias and errors. This will ensure the reliability and reproducibility in the results obtained. Along with a large sample size, the focus should be on getting to know the data better, the sample frame and the context in which it was collected. We need to focus on creation of good quality data and structured systems to capture the sample. Good data quality management makes sure that the data are structured appropriately.

Sampling bias in Brazilian studies on transgender and gender diverse populations: the two-step measure for assessing gender identity in surveys

Correctly recognizing gender identity in population-based surveys is essential to develop effective public health strategies to improve the living conditions of transgender and gender-diverse populations, as well as to adequately collect data on cisgender individuals. This study aims to present the two-step measure as the best strategy for assessing gender identity in Brazilian surveys, thus we performed two separate analyses. Firstly, we conducted a systematic review concerning HIV-related care among Brazilian transgender and gender-diverse populations to assess the strategy used to identify participants’ gender identity. Secondly, we re-analyzed data from a recent survey that included Brazilian transgender populations, comparing characteristics and health outcomes from the sample identified by single-item and by the two-step measure. Concerning the systematic review, from 6,585 references, Brazilian research teams published seven articles, and only one study used the two-step measure. Regarding this survey, the two-step measure recognized 567 cisgender and 773 transgender and gender diverse participants among the 1,340 participants who answered the questionnaire, whereas the single-item measure was able to recognize only 540 transgender and gender diverse people. Furthermore, 31 transgender women self-identified as “transgender men” on the single-item measure. Therefore, although scarcely used in Brazil, the two-step measure is a more accurate strategy to recognize gender identity.

Dynamic Species Distribution Models in the Marine Realm: Predicting Year-Round Habitat Suitability of Baleen Whales in the Southern Ocean

Species distribution models (SDMs) relate species information to environmental conditions to predict potential species distributions. The majority of SDMs are static, relating species presence information to long-term average environmental conditions. The resulting temporal mismatch between species information and environmental conditions can increase model inference’s uncertainty. For SDMs to capture the dynamic species-environment relationships and predict near-real-time habitat suitability, species information needs to be spatiotemporally matched with environmental conditions contemporaneous to the species’ presence (dynamic SDMs). Implementing dynamic SDMs in the marine realm is highly challenging, particularly due to species and environmental data paucity and spatiotemporally biases. Here, we implemented presence-only dynamic SDMs for four migratory baleen whale species in the Southern Ocean (SO): Antarctic minke, Antarctic blue, fin, and humpback whales. Sightings were spatiotemporally matched with their respective daily environmental predictors. Background information was sampled daily to describe the dynamic environmental conditions in the highly dynamic SO. We corrected for spatial sampling bias by sampling background information respective to the seasonal research efforts. Independent model evaluation was performed on spatial and temporal cross-validation. We predicted the circumantarctic year-round habitat suitability of each species. Daily predictions were also summarized into bi-weekly and monthly habitat suitability. We identified important predictors and species suitability responses to environmental changes. Our results support the propitious use of dynamic SDMs to fill species information gaps and improve conservation planning strategies. Near-real-time predictions can be used for dynamic ocean management, e.g., to examine the overlap between habitat suitability and human activities. Nevertheless, the inevitable spatiotemporal biases in sighting data from the SO call for the need for improving sampling effort in the SO and using alternative data sources (e.g., passive acoustic monitoring) in future SDMs. We further discuss challenges of calibrating dynamic SDMs on baleen whale species in the SO, with a particular focus on spatiotemporal sampling bias issues and how background information should be sampled in presence-only dynamic SDMs. We also highlight the need to integrate visual and acoustic data in future SDMs on baleen whales for better coverage of environmental conditions suitable for the species and avoid constraints of using either data type alone.

Whole-genome analysis-based phylogeographic investigation of Streptococcus pneumoniae serotype 19A sequence type 320 isolates in Japan.

After the introduction of the seven-valent pneumococcal conjugate vaccine, the global spread of multidrug resistant serotype 19A-ST320 strains became a public health concern. In Japan, the main genotype of serotype 19A was ST3111, and the identification rate of ST320 was low. Although the isolates were sporadically detected in both adults and children, their origin remains unknown. Thus, by combining pneumococcal isolates collected in three nationwide pneumococcal surveillance studies conducted in Japan between 2008 and 2020, we analyzed 56 serotype 19A-ST320 isolates along with 931 global isolates, using whole-genome sequencing to uncover the transmission route of the globally distributed clone in Japan. The clone was frequently detected in Okinawa Prefecture, where the U.S. returned to Japan in 1972. Phylogenetic analysis demonstrated that the isolates from Japan were genetically related to those from the U.S.; therefore, the common ancestor may have originated in the U.S. In addition, Bayesian analysis suggested that the time to the most recent common ancestor of the isolates form Japan and the U.S. was approximately the 1990s to 2000, suggesting the possibility that the common ancestor could have already spread in the U.S. before the Taiwan 19F-14 isolate was first identified in a Taiwanese hospital in 1997. The phylogeographical analysis supported the transmission of the clone from the U.S. to Japan, but the analysis could be influenced by sampling bias. These results suggested the possibility that the serotype 19A-ST320 clone had already spread in the U.S. before being imported into Japan.

Improved parameter estimation and uncertainty propagation in Bayesian Radiocarbon-dated Event Count [REC] models

Data about the past contain chronological uncertainty that needs to be accounted for in statistical models. Recently a method called Radiocarbon-dated Event Count (REC) modelling has been explored as a way to improve the handling of chronological uncertainty in the context of statistical regression. REC modelling has so far employed a Bayesian hierarchical framework for parameter estimation to account for chronological uncertainty in count series of radiocarbon-dates. This approach, however, suffers from a couple of limitations. It is computationally inefficient, which limits the amount of chronological uncertainty that can be accounted for, and the hierarchical framework can produce biased, but highly precise parameter estimates. Here we report the results of an investigation in which we compared hierarchical REC models to an alternative with simulated data and a new R package called "chronup". Our results indicate that the hierarchical framework can produce correct high-precision estimates given enough data, but it is susceptible to sampling bias and has an inflated Type I error rate. In contrast, the alternative better handles small samples and fully propagates uncertainty into parameter estimates. In light of these results, we think the alternative method is more generally suitable for Palaeo Science applications.

Estimation of Blood Pressure, Pulse Rate, Waist Circumference, BMI and BMR among PCOS Individuals

Introduction: Polycystic ovarian syndrome (PCOS) is an endocrine disorder which will affect the female’s reproductive health, there are many risk factors found in the PCOS individuals such as irregular menstrual cycle, infertility, obesity, excess hair growth, hyperandrogenemia. The aim of the study is to estimate the blood pressure and pulse rate among PCOS individuals and to compare it with the normal subjects. Materials and Methods: A group of 20 PCOS individuals and 20 normal individuals have been chosen from Saveetha dental college with age of 18-25 years whose blood pressure, pulse rate, waist circumference, BMI, BMR are measured, the blood pressure and pulse rate were measured with a automatic blood pressure monitoring machine and the waist circumference was measured with a inch tape from last rib and the iliac crest at its small parameter. The simple random sampling method is used to minimize the sampling bias. Data was collected and analyzed by an independent sample‘t’ test. Results: When comparing with control healthy individuals, the systolic blood pressure (SBP) of PCOS individuals seem to be higher than the control subjects. The diastolic blood pressure (DBP) is also slightly higher for PCOS individuals. The pulse rate of normal individuals is higher than the PCOS individuals. The diastolic blood pressure had a significant value of about 0.002 which is less than 0.05 so it is significant Conclusion: From this study it is evident that when PCOS is seen in women it not only affects the gynecological sphere it also affects the cardiovascular activity which may even have fatal outcomes. So it is mandatory for the PCOS subjects to have a proper diet, proper sleep, physical activity, and very importantly to have a stress free life.

Digital Teaching Methodology among the Dental Students a Questionnaire Based Survey

Background: The implementation of digital technologies in dental curricula has started globally and reached varying levels of penetration counting on local resources and demands. One of the biggest challenges in digital education is the need to continuously adapt and adjust to the developments in technology and apply these to dental practice in communicating with dental professionals, medical doctors, dental technicians, and insurance providers, dental students need to be prepared to manage digitized data, ensure patient safety, and understand the advantages and limitations of conventional and digital processes. Aim: To create awareness about digital teaching methodology among the dental students. Materials and Methods: A cross-sectional survey was conducted among the adolescent population with a sample size of 120. A self administered structured questionnaire was prepared based on digital teaching methodology and consisted of 13 questions. It was circulated to participants through an online platform (google form). The statistics were done using SPSS software, chi-square test was used to check the association and P value of 0.05 was said to be statistically significant.The pros of the survey is that the adolescents of different lifestyles and cultures were surveyed. Children and adults were excluded from the survey. Simple random sampling method was the sampling method used to minimise the sampling bias. Results: The results showed that the dental students are aware about the digital teaching methodology. Conclusion: The people are aware of the digital teaching methodology. But more awareness needs to be spread so that digital handling can be improvised in the near future.

Magnetotail reconnection asymmetries in an ion-scale, Earth-like magnetosphere

We use a newly developed global Hall magnetohydrodynamic (MHD) code to investigate how reconnection drives magnetotail asymmetries in small, ion-scale magnetospheres. Here, we consider a magnetosphere with a similar aspect ratio to Earth but with the ion inertial length (δi) artificially inflated by a factor of 70: δi is set to the length of the planetary radius. This results in a magnetotail width on the order of 30 δi, slightly smaller than Mercury's tail and much smaller than Earth's with respect to δi. At this small size, we find that the Hall effect has significant impact on the global flow pattern, changing from a symmetric, Dungey-like convection under resistive MHD to an asymmetric pattern similar to that found in previous Hall MHD simulations of Ganymede's subsonic magnetosphere as well as other simulations of Mercury's using multi-fluid or embedded kinetic physics. We demonstrate that the Hall effect is sufficient to induce a dawnward asymmetry in observed dipolarization front locations and find quasi-periodic global-scale dipolarizations under steady, southward solar wind conditions. On average, we find a thinner current sheet dawnward; however, the measured thickness oscillates with the dipolarization cycle. During the flux-pileup stage, the dawnward current sheet can be thicker than the duskward sheet. This could be an explanation for recent observations that suggest Mercury's current sheet is actually thicker on the duskside: a sampling bias due to a longer lasting “thick” state in the sheet.