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P-values are widely used to assess scientific evidence in randomized clinical trials despite the controversy surrounding its appropriate use and interpretation. A p-value is uniformly distributed under the null hypothesis while a distribution of a p-value under the alternative hypothesis is a function of sample size and posited alternative value in cases where the normal approximation can be assumed. This gives a sense of how sample sizes and posited alternative values affect the distribution of the p-value under the alternative hypothesis and it helps to plan a more plausible study based on its aims during the design stage. In this article, we investigate the distribution of a p-value under the alternative hypothesis when the outcome is binary, focusing on the exact approach where the normal approximation is not applicable due to a small sample size. The characteristics of a p-value distribution under the alternative hypothesis were illustrated in various scenarios. Our investigation of the distribution showed a p-value at an alternative value can be useful, especially when there is not much information during the planning stage due to a lack of preliminary findings. [ABSTRACT FROM AUTHOR]

Aims: Advances in treatment have extended the life expectancy of patients with metastatic bone disease (MBD). Patients could experience more skeletal-related events (SREs) as a result of this progress. Those who have already experienced a SRE could encounter another local management for a subsequent SRE, which is not part of the treatment for the initial SRE. However, there is a noted gap in research on the rate and characteristics of subsequent SREs requiring further localized treatment, obligating clinicians to extrapolate from experiences with initial SREs when confronting subsequent ones. This study aimed to investigate the proportion of MBD patients developing subsequent SREs requiring local treatment, examine if there are prognostic differences at the initial treatment between those with single versus subsequent SREs, and determine if clinical, oncological, and prognostic features differ between initial and subsequent SRE treatments. Methods: This retrospective study included 3,814 adult patients who received local treatment – surgery and/or radiotherapy – for bone metastasis between 1 January 2010 and 31 December 2019. All included patients had at least one SRE requiring local treatment. A subsequent SRE was defined as a second SRE requiring local treatment. Clinical, oncological, and prognostic features were compared between single SREs and subsequent SREs using Mann-Whitney U test, Fisher’s exact test, and Kaplan–Meier curve. Results: Of the 3,814 patients with SREs, 3,159 (83%) patients had a single SRE and 655 (17%) patients developed a subsequent SRE. Patients who developed subsequent SREs generally had characteristics that favoured longer survival, such as higher BMI, higher albumin levels, fewer comorbidities, or lower neutrophil count. Once the patient got to the point of subsequent SRE, their clinical and oncological characteristics and one-year survival (28%) were not as good as those with only a single SRE (35%; p < 0.001), indicating that clinicians’ experiences when treating the initial SRE are not similar when treating a subsequent SRE. Conclusion: This study found that 17% of patients required treatments for a second, subsequent SRE, and the current clinical guideline did not provide a specific approach to this clinical condition. We observed that referencing the initial treatment, patients in the subsequent SRE group had longer six-week, 90-day, and one-year median survival than patients in the single SRE group. Once patients develop a subsequent SRE, they have a worse one-year survival rate than those who receive treatment for a single SRE. Future research should identify prognostic factors and assess the applicability of existing survival prediction models for better management of subsequent SREs. Cite this article: Bone Joint Res 2024;13(9):497–506.

AbstractThe support of the p-value corresponding to a discrete test-statistic is a finite isolated subset of the unit interval. In differential gene expression studies with RNA-sequence datasets, multiple discrete tests are performed. The objective of such studies are to identify differentially expressed genes with a control over a measure of false discoveries. We suggest to remove hypotheses corresponding to the p-values having minimum support-point greater than the threshold of that overall measure. We argue this suggestion and present methods of filtering the set of hypotheses for two useful testing scenarios. Simulation experiments show gain in power of the multiple testing procedures when applied to the filtered set of hypotheses. We also demonstrate the method with two real datasets, related to the study of HIV and mammary gland. [ABSTRACT FROM AUTHOR]

Copyright of Slovo a Slovesnost is the property of Academy of Sciences of the Czech Republic, Czech Language Institute and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

When designing a randomized clinical trial to compare two treatments, the sample size required to have desired power with a specified type 1 error depends on the hypothesis testing procedure. With a binary endpoint (e.g., response), the trial results can be displayed in a 2 × 2 table. If one does the analysis conditional on the number of positive responses, then using Fisher's exact test has an actual type 1 error less than or equal to the specified nominal type 1 error. Alternatively, one can use one of many unconditional "exact" tests that also preserve the type 1 error and are less conservative than Fisher's exact test. In particular, the unconditional test of Boschloo is always at least as powerful as Fisher's exact test, leading to smaller required sample sizes for clinical trials. However, many statisticians have argued over the years that the conditional analysis with Fisher's exact test is the only appropriate procedure. Since having smaller clinical trials is an extremely important consideration, we review the general arguments given for the conditional analysis of a 2 × 2 table in the context of a randomized clinical trial. We find the arguments not relevant in this context, or, if relevant, not completely convincing, suggesting the sample‐size advantage of the unconditional tests should lead to their recommended use. We also briefly suggest that since designers of clinical trials practically always have target null and alternative response rates, there is the possibility of using this information to improve the power of the unconditional tests. [ABSTRACT FROM AUTHOR]

Objective: The objective of this retrospective cross-sectional research was to examine the musculoskeletal problems associated with Juvenile Idiopathic Arthritis (JIA) at a tertiary care hospital located in Peshawar, Pakistan, during the period spanning from March 2022 to March 2023 Methods: The study included the collection and analysis of data from patients with Juvenile Idiopathic Arthritis (JIA) who were undergoing treatment at the hospital. Descriptive statistics, subgroup analyses, and Fisher’s Exact test were used to investigate potential connections between JIA and musculoskeletal problems. . Results: The analysis revealed a range of demographic features, with a significant proportion of pa- tients (52.9) falling between the age range of 11-15 years. The most common subtype of JIA was Polyarticular RF Negative, accounting for 44.1 of cases. This subtype was characterized by high lev- els of Erythrocyte Sedimentation Rate (ESR) (64.7) and C-reactive protein (CRP) (47.1), which are indicative of inflammation. The study revealed statistically significant correlations between substantial joint involvement, swelling, and discomfort in individuals with musculoskeletal conditions (p 0.05). Nevertheless, the health evaluations conducted by patients and parents did not reveal any significant association with musculoskeletal issues. Significant correlations were seen between a positive fam- ily history of JIA or other RMDS and musculoskeletal disorders (p 0.05). Conclusion: The present research emphasizes the need to conduct a thorough medical history and physical tests for diagnosing Juvenile Idiopathic Arthritis (JIA), with a special focus on children who have distinct symptoms. Providing healthcare personnel with knowledge about musculoskeletal com- plaints may assist in promptly identifying and treating them, therefore enhancing patient results.

Storey's estimator for the proportion of true null hypotheses, originally proposed under the continuous framework, has been modified in this work under the discrete framework. The modification results in improved estimation of the parameter of interest. The proposed estimator is used to formulate an adaptive version of the Benjamini–Hochberg procedure. Control over the false discovery rate by the proposed adaptive procedure has been proved analytically. The proposed estimate is also used to formulate an adaptive version of the Benjamini–Hochberg–Heyse procedure. Simulation experiments establish the conservative nature of this new adaptive procedure. Substantial amount of gain in power is observed for the new adaptive procedures over the standard procedures. For demonstration of the proposed method, two important real life gene expression data sets, one related to the study of HIV and the other related to methylation study, are used. [ABSTRACT FROM AUTHOR]

Aims: Revision total knee arthroplasty (rTKA) is a technically challenging and costly procedure. It is well-documented that primary TKA (pTKA) have better survivorship than rTKA; however, we were unable to identify any studies explicitly investigating previous rTKA as a risk factor for failure following rTKA. The purpose of this study is to compare the outcomes following rTKA between patients undergoing index rTKA and those who had been previously revised. Methods: This retrospective, observational study reviewed patients who underwent unilateral, aseptic rTKA at an academic orthopaedic speciality hospital between June 2011 and April 2020 with > one-year of follow-up. Patients were dichotomized based on whether this was their first revision procedure or not. Patient demographics, surgical factors, postoperative outcomes, and re-revision rates were compared between the groups. Results: A total of 663 cases were identified (486 index rTKAs and 177 multiply revised TKAs). There were no differences in demographics, rTKA type, or indication for revision. Multiply revised patients had significantly longer rTKA operative times (p < 0.001), and were more likely to be discharged to an acute rehabilitation centre (6.2% vs 4.5%) or skilled nursing facility (29.9% vs 17.5%; p = 0.003). Patients who had been multiply revised were also significantly more likely to have subsequent reoperation (18.1% vs 9.5%; p = 0.004) and re-revision (27.1% vs 18.1%; p = 0.013). The number of previous revisions did not correlate with the number of subsequent reoperations (r = 0.038; p = 0.670) or re-revisions (r = −0.102; p = 0.251). Conclusion: Multiply revised TKA had worse outcomes, with higher rates of facility discharge, longer operative times, and greater reoperation and re-revision rates compared to index rTKA. Cite this article: Bone Jt Open 2023;4(5):393–398.

Fisher's exact test and Pearson's chi-squared test are frequently used for testing associations of two binary variables in 2-by-2 contingency tables. In the single test setting, many studies have shown that the asymptotic Pearson's chi-squared test cannot preserve the test size for small samples and Fisher Exact test tends to be overly conservative. Multiple unconditional exact tests were proposed for small samples as they perform better than the commonly used chi-square and Fisher's exact test. No comparison of these approaches have been done in the multiple testing setting.This study examines the performances of two unconditional tests (Boschloo and Z-pooled test statistics are used) with Fisher's exact test as well as asymptotic Pearson's chi-squared test in a small sample multiple testing scenario via a simulation study. When testing simultaneously many null hypotheses, Benjamini-Hochberg (BH) procedure is typically applied to control the false discovery rate (FDR). The results show that in terms of sensitivity rate, the performances of Z-pooled and Boschloo Statistic are close to each other; Asymptotic chi-squared test is slightly better than the unconditional exact tests; Fisher's exact test is the least powerful in all different settings. Boschloo's test is more computation intensive. Z-pooled test is preferred if running time is a concern. [ABSTRACT FROM AUTHOR]

We report the molecular characterization of an ethyl methanesulfonate (EMS)-induced mutation that causes albinism and lethality at the seedling stage in Arabidopsis thaliana. We identified the mutation using a mapping-by-sequencing approach that uses Fisher's exact tests to detect changes in allele frequencies among the seedlings of an F2 mapping population, which had been pooled according to their phenotypes (wild-type or mutant). After purifying genomic DNA from the plants of both pools, the two samples were sequenced using the Illumina HiSeq 2500 next-generation sequencing platform. The bioinformatic analysis allowed us to identify a point mutation that damages a conserved residue at the acceptor site of an intron of the At2g04030 gene, which encodes the chloroplast-localized AtHsp90.5 protein, a member of the HSP90 family of heat shock proteins. Our RNA-seq analysis demonstrates that the new allele alters the splicing of At2g04030 transcripts in multiple ways, leading to massive deregulation of genes encoding plastid-localized proteins. A search for protein–protein interactions using the yeast two-hybrid method allowed us to identify two members of the GrpE superfamily as potential interactors of AtHsp90.5, as has previously been reported for green algae. [ABSTRACT FROM AUTHOR]

This study investigates 11 agricultural management practices (AMPs) and their effects on seven visual soil quality indicators and soil aggregate stability. The survey carried out across eight pedoclimatic zones in Europe and China was based on visual soil assessments (New Zealand VSA method) performed on soils subject to different soil management practices and nearby similar soils, under similar farming features, without the distinctive soil management practice (control). Fisher's exact test was used to test if the management treatment was independent of the score of each visual soil quality indicator and to test if the management treatment produced a higher frequency of the score 'good'. The results showed a statistically significant (α <.05) higher frequency of the score 'good' for 'soil structure and consistency' and/or 'soil porosity' for six AMPs. For no‐till AMP, the null hypothesis can also be rejected for 'susceptibility to erosion' and 'soil stability' and for 'mulching + permanent soil cover' AMP, for the 'presence of tillage pan' and 'soil colour'. The hypothesis that the management treatment was independent of the score of each indicator was rejected for 'soil structure and consistency' of three AMPs, for 'soil porosity' of three AMPs, for 'soil colour' of one AMP and for the 'presence of tillage pan' of one AMP. This study demonstrates that farming systems sharing a common influential soil management practice at different locations and with different soil types significantly affect the score of some visual soil quality indicators. [ABSTRACT FROM AUTHOR]

A test of independence is commonly used to determine differences (or associations) between samples in a nominal level measurement. Fisher's exact test and Chi-square test are two of the most widely applied tests of independence used in the data analyses in different areas such as information technologies, biostatistics, psychology and health sciences. In some cases, contingency tables with null entries (also called random zeros) arise, particularly if the number of samples is small, and the variables analyzed are multilevel. This situation becomes a problem because if one or more entries in a contingency table are zero or have small values, then the tests of independence produce unreliable results. In this paper, we propose a method to address that issue. The method merges one or more levels of the variables analyzed to create contingency tables with only one degree of freedom, avoiding applying a test of independence on contingency tables with random zeros. The source code (Python) of the method is publicly available for use. The results obtained using our method give a complete panorama of the associations between the variables of a data set. To show the effectiveness of our approach to find dependencies between variables, we use four data sets publicly available on the Internet. [ABSTRACT FROM AUTHOR]

A small n, sequential, multiple assignment, randomized trial (snSMART) is a small sample, two-stage design where participants receive up to two treatments sequentially, but the second treatment depends on response to the first treatment. The parameters of interest in an snSMART are the first-stage response rates of the treatments, but outcomes from both stages can be used to obtain more information from a small sample. A novel way to incorporate the outcomes from both stages uses power prior models, in which first stage outcomes from an snSMART are regarded as the primary (internal) data and second stage outcomes are regarded as supplemental data (co-data). We apply existing power prior models to snSMART data, and we also develop new extensions of power prior models. All methods are compared to each other and to the Bayesian joint stage model (BJSM) via simulation studies. By comparing the biases and the efficiency of the response rate estimates among all proposed power prior methods, we suggest application of Fisher's Exact Test or the Bhattacharyya's overlap measure to an snSMART to estimate the response rates in an snSMART, which both have performance mostly as good or better than the BJSM. We describe the situations where each of these suggested approaches is preferred. [ABSTRACT FROM AUTHOR]

Aims: This study assessed the impact of COVID-19 on hip and distal femur fracture patient outcomes across three successive UK lockdown periods over one year. Methods: A single-centre retrospective cohort study was performed at an acute NHS Trust. Hip and distal femur fracture patients admitted within the first month from each of the three starting dates of each national lockdown were included and compared to a control group in March 2019. Data were collected as per the best practice tariff outcomes including additional outcomes as required. Data collection included COVID-19 status, time to theatre, 30-day mortality, presence of acute kidney injury (AKI) and pneumonia, and do not attempt cardiopulmonary resuscitation (DNACPR) status. Data were analyzed using an independent-samples t-test or chi-squared test with Fisher’s exact test where applicable. A p-value of < 0.05 was considered statistically significant. Results: A total of 95 patients during the pandemic were included and 20 were COVID-positive. Patients experienced a statistically significant increase in time to theatre in Lockdown 1 compared to 2019 (p = 0.039) with a decrease with successive lockdown periods by Lockdown 3. The 30-day mortality increased from 8.8% in 2019 to 10.0% to 14.8% in all lockdown periods. COVID-positive patient mortality was 30.0% (p = 0.063, odds ratio (OR) = 4.43 vs 2019). The rates of AKI and pneumonia experienced were higher for patients during the pandemic. The highest rates were experienced in COVID-positive patients, with 45.0% of patients with AKI versus 27.0% in 2019 (p = 0.38, OR = 1.80), and 50.0% of patients diagnosed with pneumonia versus 16.2% in 2019 (p = 0.0012, OR = 5.17). The percentage of patients with a DNACPR increased from 30.0% in 2019 to 60.7% by Lockdown 3 (p = 0.034, OR = 3.61). Conclusion: COVID-positive hip and distal femur fracture patients are at a higher risk of mortality due to AKI and pneumonia. Patient outcomes have improved with successive lockdowns to pre-pandemic levels. Cite this article: Bone Jt Open 2021;2(12):1017–1026.

Aims: Physician burnout and its consequences have been recognized as increasingly prevalent and important issues for both organizations and individuals involved in healthcare delivery. The purpose of this study was to describe and compare the patterns of self-reported wellness in orthopaedic surgeons and trainees from multiple nations with varying health systems. Methods: A cross-sectional survey of 774 orthopaedic surgeons and trainees in five countries (Australia, Canada, New Zealand, UK, and USA) was conducted in 2019. Respondents were asked to complete the Mayo Clinic Well-Being Index and the Stanford Professional Fulfillment Index in addition to 31 personal/demographic questions and 27 employment-related questions via an anonymous online survey. Results: A total of 684 participants from five countries (Australia (n = 74), Canada (n = 90), New Zealand (n = 69), UK (n = 105), and USA (n = 346)) completed both of the risk assessment questionnaires (Mayo and Stanford). Of these, 42.8% (n = 293) were trainees and 57.2% (n = 391) were attending surgeons. On the Mayo Clinic Well-Being Index, 58.6% of the overall sample reported feeling burned out (n = 401). Significant differences were found between nations with regards to the proportion categorized as being at risk for poor outcomes (27.5% for New Zealand (19/69) vs 54.4% for Canada (49/90) ; p = 0.001). On the Stanford Professional Fulfillment Index, 38.9% of the respondents were classified as being burned out (266/684). Prevalence of burnout ranged from 27% for Australia (20/74 up to 47.8% for Canadian respondents (43/90; p = 0.010). Younger age groups (20 to 29: RR 2.52 (95% confidence interval (CI) 1.39 to 4.58; p = 0.002); 30 to 39: RR 2.40 (95% CI 1.36 to 4.24; p = 0.003); 40 to 49: RR 2.30 (95% CI 1.35 to 3.9; p = 0.002)) and trainee status (RR 1.53 (95% CI 1.15 to 2.03 p = 0.004)) were independently associated with increased relative risk of having a ‘at-risk’ or ‘burnout’ score. Conclusions: The rate of self-reported burnout and risk for poor outcomes among orthopaedic surgeons and trainees varies between countries but remains unacceptably high throughout. Both individual and health system characteristics contribute to physician wellness and should be considered in the development of strategies to improve surgeon wellbeing. Level of Evidence: III Cite this article: Bone Jt Open 2021;2(11):932–939.

The use of statistics to derive insights from the data has provided researchers with empirical tools to describe, diagnose, predict, and prescribe actions, interventions and generate knowledge from varied data sets. Depending on the types of data (structured, semi-structured, and unstructured), different statistical models and tests can be performed to generate the said insights and new knowledge. Correctly identifying the data types (whether the data is discrete or continuous) aids researchers in identifying the applicable statistical tests. The distribution of the data also has an implication for determining the relevant statistical test. When continuous data are said to be normally distributed, the types of tests that can be used to compare groups differ to when the data are found to be not normally distributed. The same is true for discrete data, in that there are certain assumptions that need to be satisfied to identify the correct statistical tests to use in comparing the data groups. In this paper, the discussion will be focused on nine commonly used statistical tests. These common tests include the t-test, paired t-test, analysis of variance (ANOVA) test, Wilcoxon rank-sum test (WRST), Wilcoxon signed-rank test (WSRT), nonparametric ANOVA, chi-square (X2) test, Fisher's exact test, and McNemar's test. The conditions for the use of these tests will be described, and the applications thereof will be discussed. Therefore, the purpose of this paper is not to describe the mathematical theories behind different statistical tests but to introduce the tests and their applications. [ABSTRACT FROM AUTHOR]

Due to the escalating usage of cellphones, cellphone distracted driving remains one of the fastest-growing traffic safety problems. Two basic types of cellphone distractions are – talking (handheld or hands-free) and manipulating (texting, internet browsing, using apps for social networking, navigation, entertainment, etc.). To explore the association between the cellphone distraction type and characteristics of a driver, roadway, and vehicle, we used Fisher's exact test and association rule mining to analyze the data from ten different hour-long observation sessions performed both at intersections and on straight continuous segments. Among 3727 drivers observed, 22.1% were found distracted by cellphones. More drivers were involved in manipulating (12.8%) than talking on the phone (9.3%). The Fisher's exact test results show that intersections and the presence of passengers may be significantly associated with driver distraction type. This study makes a novel attempt to utilize association rule mining in cellphone distraction observation. A set of generated rules and their network visualization demonstrated how a specific group of characteristics can be related to cellphone conversation or manipulation through the measures of support, confidence, and lift. 'Peak hour', 'Absence of passengers', and 'Urban setting' are more likely to be associated with distracted driving than other characteristics. The results from association rules revealed that male drivers were found to be predominantly involved in cellphone manipulation during peak hours on urban segments than female drivers, and they were also largely involved in cellphone conversation during peak hours on the rural segment. Female drivers engaged in manipulating cellphones at the urban intersection during both peak and off-peak hours. In the rural area during peak hours, female drivers were manipulating at the intersection and were talking while driving on the continuous segment. Drivers aged '30–60 years' were found to be more associated with cellphone use compared to '60 years' age group. 'Passenger car drivers during peak hours' were more associated with manipulating cellphones than expected compared to any other collective group, whereas 'female passenger car drivers driving on continuous segment' were strongly associated with cellphone conversation. The detailed discussion of the findings from association rule mining will be useful for targeting a specific group of relevant characteristics in potential cellphone distraction reduction strategies.

Objective: The objective of this retrospective cross-sectional research was to examine the musculoskeletal problems associated with Juvenile Idiopathic Arthritis (JIA) at a tertiary care hospital located in Peshawar, Pakistan, during the period spanning from March 2022 to March 2023. Methods: The study included the collection and analysis of data from patients with Juvenile Idiopathic Arthritis (JIA) who were undergoing treatment at the hospital. Descriptive statistics, subgroup analyses, and Fisher's Exact test were used to investigate potential connections between JIA and musculoskeletal problems. Results: The analysis revealed a range of demographic features, with a significant proportion of patients (52.9%) falling between the age range of 11-15 years. The most common subtype of JIA was Polyarticular RF Negative, accounting for 44.1% of cases. This subtype was characterized by high levels of Erythrocyte Sedimentation Rate (ESR) (64.7%) and Creactive protein (CRP) (47.1%), which are indicative of inflammation. The study revealed statistically significant correlations between substantial joint involvement, swelling, and discomfort in individuals with musculoskeletal conditions (p < 0.05). Nevertheless, the health evaluations conducted by patients and parents did not reveal any significant association with musculoskeletal issues. Significant correlations were seen between a positive family history of JIA or other RMDS and musculoskeletal disorders (p < 0.05). Conclusion: The present research emphasizes the need to conduct a thorough medical history and physical tests for diagnosing Juvenile Idiopathic Arthritis (JIA), with a special focus on children who have distinct symptoms. Providing healthcare personnel with knowledge about musculoskeletal complaints may assist in promptly identifying and treating them, therefore enhancing patient results. [ABSTRACT FROM AUTHOR]

In many applied single-point Yes/No signal-detection studies, the main interest is to evaluate the observer's sensitivity, based on the observed rates of hits and false alarms. For example, Kostopoulou, Nurek, Cantarella et al. (2019, Medical Decision Making, 39, 21–31) presented general practitioners (GPs) with clinical vignettes of patients showing various cancer-related symptoms, and asked them to decide if urgent referral was required; the standard discrimination index d′ was calculated for each GP. An alternative conditional approach to statistical inference emphasizes explicitly the conditional nature of the inferences drawn, and argues on the basis of the response marginal (the number of "yes" responses) that was actually observed. It is closely related to, for example, Fisher's exact test or the Rasch model in item response theory which have long been valuable and prominent in psychology. The conditional framework applied to single-point Yes/No detection studies is based on the noncentral hypergeometric sampling distribution and permits, for samples of any size, exact inference because it eliminates nuisance (i.e., bias) parameters by conditioning. We describe in detail how the conditional approach leads to conditional maximum likelihood sample estimates of sensitivity, and to exact confidence intervals for the underlying (log) odds ratio. We relate the conditional approach to classical (logistic) detection models also leading to analyses of the odds ratio, compare its statistical power to that of the unconditional approach, and conclude by discussing some of its pros and cons. [ABSTRACT FROM AUTHOR]

This article serves as the first in a series that will offer recommendations for optimal data reporting, specifically focusing on statistical methods most frequently reported by the Cytopathology audience. Recommendations for reporting statistical results when comparing proportions is the first topic in the series since comparing proportions, particularly utilising the chi‐square test, was the most commonly reported inferential statistical test category over 2.5 years of Cytopathology articles.1 While this article will provide a summary of common tests used to compare proportions, an extensive review of each method, including test assumptions and calculations, is beyond the scope of this summary. The author recommends consulting a trained statistician prior to data collection to discuss an analytical plan, including determining the appropriate statistical test(s) to use. This article serves as the first in a series that will offer recommendations for optimal data reporting, specifically focusing on statistical methods most frequently reported by the Cytopathology audience. Recommendations for reporting statistical results when comparing proportions is the first topic in the series since comparing proportions, particularly utilizing the chi‐square test, was the most commonly reported inferential statistical test category over 2.5 years of Cytopathology articles. [ABSTRACT FROM AUTHOR]

The one‐arm, non‐randomized, one/two‐stage phase II designs have been a mainstay in oncology trials for evaluating response rates or similar variants (i.e., tests about single proportions). With the goal of screening new therapies that have the potential to move into a randomized phase III trial or a subsequent randomized phase II trial, all while maintaining a logistically feasible sample size. However, since the implementation of the Food and Drug Administration's Fast Track Designation, there has been a trend toward randomized phase II clinical trials as a source of stronger evidence for those seeking fast‐track approvals. While there are many single‐ and multi‐stage randomized designs for evaluating proportions in this phase II setting, there still exist limitations in terms of sample size (which directly impacts cost and study duration) or operating characteristics (ex. maintained type I error). In this article, we propose a new test for comparing two binomial proportions, which is a modification across existing methods (the standard z‐test and Jung's test). This approach is contrasted with existing methods via numeric evaluation and further contrasted using a real‐world oncology trial. The proposed method demonstrates improvements in efficiency and robustness against deviations from design assumptions. When applied to the existing trial, significant savings with respect to cost and time are illustrated. Our proposed test for comparing binomial proportions provides an efficient and robust alternative in the randomized phase II oncology setting, especially when the control arm has a high rate. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Computer Engineering & Applications is the property of Beijing Journal of Computer Engineering & Applications Journal Co Ltd. and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

• Analysis of offender fingerprints from evidence types in crimes against property. • Offender fingerprints are frequently seen in common entry points such as doors. • Porous and non-porous fingerprints are found to be similar in both property settings. • Offender fingerprints are generally located on the forward portion of a vehicle. • Vehicular body and glass component show equal likelihood of offender fingerprints. The Forensic Institute of the Republic of North Macedonia data set of 1,982 offender fingerprint identifications contributing to a conviction for crimes against property, was evaluated and analysed using contingency table statistical analysis techniques, chi-square test, fisher's exact test and post hoc analysis. The data set was based on the forensic and court information available from 2005 to 2015 and pertained to the location, property type and evidence type. Interpretation of the data identified glass components, doors, windows, points of entry, cardboard and other packaging to be the most likely areas for locating offender fingerprints in non-residential and residential properties. In vehicle-based crimes, the front area (both left- and right-hand side) was the most likely to yield offender fingerprints. This study reinforced the types of evidential items at property based crime scenes yielding offender fingerprints. In addition, the study seeks to provide recommendations for future data collection to enhance the data analysis and interpretation. [ABSTRACT FROM AUTHOR]

The issue of sustainability, or corporate social responsibility (CSR), has become a widely discussed topic in all industrial production sectors. The article focuses on the automobile industrial sector because it is not only the most dynamically developing industrial area but also because it is one of the driving forces of local economies in many European countries. This paper aims to reveal possible differences and diversity of understanding of priorities in the CSR activities provided by automotive suppliers in European countries. Based on the meta-analysis, 73 actions were listed, and a questionnaire survey was performed. Cluster analysis and Fisher's exact test were applied to find out whether the attitude towards sustainability differs dependent on the position in the supply chain or on the company size. [ABSTRACT FROM AUTHOR]

We present the U-statistic permutation (USP) test of independence in the context of discrete data displayed in a contingency table. Either Pearson's X²-test of independence, or the G-test, are typically used for this task, but we argue that these tests have serious deficiencies, both in terms of their inability to control the size of the test, and their power properties. By contrast, the USP test is guaranteed to control the size of the test at the nominal level for all sample sizes, has no issues with small (or zero) cell counts, and is able to detect distributions that violate independence in only a minimal way. The test statistic is derived from a U-statistic estimator of a natural population measure of dependence, and we prove that this is the unique minimum variance unbiased estimator of this population quantity. The practical utility of the USP test is demonstrated on both simulated data, where its power can be dramatically greater than those of Pearson's test, the G-test and Fisher's exact test, and on real data. The USP test is implemented in the R package USP. [ABSTRACT FROM AUTHOR]

A test of independence is commonly used to determine differences (or associations) between samples in a nominal level measurement. Fisher’s exact test and Chi-square test are two of the most widely applied tests of independence used in the data analyses in different areas such as information technologies, biostatistics, psychology and health sciences. In some cases, contingency tables with null entries (also called random zeros) arise, particularly if the number of samples is small, and the variables analyzed are multilevel. This situation becomes a problem because if one or more entries in a contingency table are zero or have small values, then the tests of independence produce unreliable results. In this paper, we propose a method to address that issue. The method merges one or more levels of the variables analyzed to create contingency tables with only one degree of freedom, avoiding applying a test of independence on contingency tables with random zeros. The source code (Python) of the method is publicly available for use. The results obtained using our method give a complete panorama of the associations between the variables of a data set. To show the effectiveness of our approach to find dependencies between variables, we use four data sets publicly available on the Internet.

Brucellosis is a zoonotic disease and a major public health problem. However, the genetic mechanism of brucellosis in sheep remains unclear. In this study, serum samples were collected from 6,358 sheep from the F2 population (Dorper sheep ♂ × Hu sheep ♀), and antibody levels were continuously measured at 14 days and 1, 2, 3, 4, 5, 6, 7, 8, 9, and 10 months after administration of brucellosis vaccine. Finally, 19 brucellosis-resistant group (BRG) sheep and 22 brucellosis-susceptible group sheep (BSG) were screened for whole-genome sequencing. Using the fixation index, Fisher’s exact test, and chi-square test, a total of 205 candidate SNP sites were identified. Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis suggested that 138 candidate genes were significantly enriched in adherens junction (CTNNA3, PARD3, and PTPRM), cell adhesion molecules (NLGN1, CNTNAP2, NCAM1, and PTPRM), salivary secretion (LOC101102109, PRKG1, and ADCY2), and hippo signaling pathway (CTNNA3, YAP1, and PARD3). These findings provide valuable molecular markers for brucellosis resistance breeding in sheep and novel insights into the genetic mechanism of brucellosis resistance.

Brucellosis is a zoonotic disease and a major public health problem. However, the genetic mechanism of brucellosis in sheep remains unclear. In this study, serum samples were collected from 6,358 sheep from the F2 population (Dorper sheep ♂ × Hu sheep ♀), and antibody levels were continuously measured at 14 days and 1, 2, 3, 4, 5, 6, 7, 8, 9, and 10 months after administration of brucellosis vaccine. Finally, 19 brucellosis-resistant group (BRG) sheep and 22 brucellosis-susceptible group sheep (BSG) were screened for whole-genome sequencing. Using the fixation index, Fisher's exact test, and chi-square test, a total of 205 candidate SNP sites were identified. Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis suggested that 138 candidate genes were significantly enriched in adherens junction (CTNNA3 , PARD3 , and PTPRM), cell adhesion molecules (NLGN1 , CNTNAP2 , NCAM1 , and PTPRM), salivary secretion (LOC101102109 , PRKG1 , and ADCY2), and hippo signaling pathway (CTNNA3 , YAP1 , and PARD3). These findings provide valuable molecular markers for brucellosis resistance breeding in sheep and novel insights into the genetic mechanism of brucellosis resistance. [ABSTRACT FROM AUTHOR]

Due to the escalating usage of cellphones, cellphone distracted driving remains one of the fastest-growing traffic safety problems. Two basic types of cellphone distractions are – talking (handheld or hands-free) and manipulating (texting, internet browsing, using apps for social networking, navigation, entertainment, etc.). To explore the association between the cellphone distraction type and characteristics of a driver, roadway, and vehicle, we used Fisher's exact test and association rule mining to analyze the data from ten different hour-long observation sessions performed both at intersections and on straight continuous segments. Among 3727 drivers observed, 22.1% were found distracted by cellphones. More drivers were involved in manipulating (12.8%) than talking on the phone (9.3%). The Fisher's exact test results show that intersections and the presence of passengers may be significantly associated with driver distraction type. This study makes a novel attempt to utilize association rule mining in cellphone distraction observation. A set of generated rules and their network visualization demonstrated how a specific group of characteristics can be related to cellphone conversation or manipulation through the measures of support, confidence, and lift. 'Peak hour', 'Absence of passengers', and 'Urban setting' are more likely to be associated with distracted driving than other characteristics. The results from association rules revealed that male drivers were found to be predominantly involved in cellphone manipulation during peak hours on urban segments than female drivers, and they were also largely involved in cellphone conversation during peak hours on the rural segment. Female drivers engaged in manipulating cellphones at the urban intersection during both peak and off-peak hours. In the rural area during peak hours, female drivers were manipulating at the intersection and were talking while driving on the continuous segment. Drivers aged '30–60 years' were found to be more associated with cellphone use compared to '<30 years' and '>60 years' age group. 'Passenger car drivers during peak hours' were more associated with manipulating cellphones than expected compared to any other collective group, whereas 'female passenger car drivers driving on continuous segment' were strongly associated with cellphone conversation. The detailed discussion of the findings from association rule mining will be useful for targeting a specific group of relevant characteristics in potential cellphone distraction reduction strategies. • Fisher's exact tests measure significance of cellphone use type with roadway, vehicle, and driver characteristics. • Fisher's test results indicate significant association of intersections and passenger presence with distraction type. • Association rule mining is utilized for presenting co-occurring collective relationship of observed characteristics. • Association rule mining reveals 'passenger car drivers during peak hours' are linked with cellphone manipulation. • Cellphone conversation is more associated with 'female passenger car drivers driving on continuous segment'. [ABSTRACT FROM AUTHOR]

In this paper operators i[j] and [j]k are defined, whose effects on an r×c contingency table X are to subtract 1 from xij and to add 1 to xkj , respectively, so that the composition i[j]k of the two operators changes the j-th column of the contingency table without altering its total. Also a loop is defined as a composition of such operators that leaves unchanged both row and column totals. This is used to characterize the r×c contingency tables of maximum probability over the fixed marginals reference set (under the hypothesis of row and column independence). Another characterization of such maximum probability tables is given using the concept of associated U tables, a U = {uij} table being defined as a table such that uij > 0, 1 ≤ i ≤ r and 1 ≤ j ≤ c, and for a given set of values rh, 1 ≤ h < r, uh+1,j = rhuhj for all j. Finally, a necessary and sufficient condition for the uniqueness of a maximum probability table in the fixed marginals reference set is provided.

Consumers' buying behavior and preferences are affected by many factors such as the product quality, price, labeling and country of origin. The objective of this paper was to examine the opinions of the Slovak consumers about the purchase and consumption of eggs and identify their preferences at egg purchase. The input data were obtained using a questionnaire survey. The method of descriptive statistics and selected methods of measuring dependence or associations were used. The existence of statistically significant relationships was verified by the Pearson chi-square test or by the Fisher's exact test. The statistical proof of relationships was evaluated based on the significance of the test characteristic (p-value). The existence of dependence between the most important factor affecting purchasing of eggs - a price of eggs, and the age of the respondent - was confirmed. Further, the relationship between the preferred place of buying eggs and the classification criterion was also proved, i.e. whether a respondent is a breeder of the egg type of hens or not. The relationship between the preferred place of buying eggs and the gender of a respondent was confirmed as well. There was determined the dependence on the gender of a respondent in the question related to eggs consumption.

Abstract Background Recent statistical methods for next generation sequencing (NGS) data have been successfully applied to identifying rare genetic variants associated with certain diseases. However, most commonly used methods (e.g., burden tests and variance-component tests) rely on large sample sizes. Notwithstanding, due to its-still high cost, NGS data is generally restricted to small sample sizes, that cannot be analyzed by most existing methods. Methods In this work, we propose a new exact association test for sequencing data that does not require a large sample approximation, which is applicable to both common and rare variants. Our method, based on the Generalized Cochran-Mantel-Haenszel (GCMH) statistic, was applied to NGS datasets from intraductal papillary mucinous neoplasm (IPMN) patients. IPMN is a unique pancreatic cancer subtype that can turn into an invasive and hard-to-treat metastatic disease. Results Application of our method to IPMN data successfully identified susceptible genes associated with progression of IPMN to pancreatic cancer. Conclusions Our method is expected to identify disease-associated genetic variants more successfully, and corresponding signal pathways, improving our understanding of specific disease’s etiology and prognosis.

The detection of protein complexes from protein-protein interaction network is a fundamental issue in bioinformatics and systems biology. To solve this problem, numerous methods have been proposed from different angles in the past decades. However, the study on detecting statistically significant protein complexes still has not received much attention. Although there are a few methods available in the literature for identifying statistically significant protein complexes, none of these methods can provide a more strict control on the error rate of a protein complex in terms of family-wise error rate (FWER). In this paper, we propose a new detection method SSF that is capable of controlling the FWER of each reported protein complex. More precisely, we first present a $p$ p -value calculation method based on Fisher's exact test to quantify the association between each protein and a given candidate protein complex. Consequently, we describe the key modules of the SSF algorithm: a seed expansion procedure for significant protein complexes search and a set cover strategy for redundancy elimination. The experimental results on five benchmark data sets show that: (1) our method can achieve the highest precision; (2) it outperforms three competing methods in terms of normalized mutual information (NMI) and F1 score in most cases. [ABSTRACT FROM AUTHOR]

Protein domains can be regarded as sections of protein sequences capable of folding independently and performing specific functions. In addition to amino-acid level changes, protein sequences can also evolve through domain shuffling events such as domain insertion, deletion, or duplication. The evolution of protein domains can be studied by tracking domain changes in a selected set of species with known phylogenetic relationships. Here, we conduct such an analysis by defining domains as "features" or "descriptors," and considering the species (target + outgroup) as instances or data-points in a data matrix. We then look for features (domains) that are significantly different between the target species and the outgroup species. We study the domain changes in 2 large, distinct groups of plant species: legumes (Fabaceae) and grasses (Poaceae), with respect to selected outgroup species. We evaluate 4 types of domain feature matrices: domain content, domain duplication, domain abundance, and domain versatility. The 4 types of domain feature matrices attempt to capture different aspects of domain changes through which the protein sequences may evolve—that is, via gain or loss of domains, increase or decrease in the copy number of domains along the sequences, expansion or contraction of domains, or through changes in the number of adjacent domain partners. All the feature matrices were analyzed using feature selection techniques and statistical tests to select protein domains that have significant different feature values in legumes and grasses. We report the biological functions of the top selected domains from the analysis of all the feature matrices. In addition, we also perform domain-centric gene ontology (dcGO) enrichment analysis on all selected domains from all 4 feature matrices to study the gene ontology terms associated with the significantly evolving domains in legumes and grasses. Domain content analysis revealed a striking loss of protein domains from the Fanconi anemia (FA) pathway, the pathway responsible for the repair of interstrand DNA crosslinks. The abundance analysis of domains found in legumes revealed an increase in glutathione synthase enzyme, an antioxidant required from nitrogen fixation, and a decrease in xanthine oxidizing enzymes, a phenomenon confirmed by previous studies. In grasses, the abundance analysis showed increases in domains related to gene silencing which could be due to polyploidy or due to enhanced response to viral infection. We provide a docker container that can be used to perform this analysis workflow on any user-defined sets of species, available at https://cloud.docker.com/u/akshayayadav/repository/docker/akshayayadav/protein-domain-evolution-project. [ABSTRACT FROM AUTHOR]

Staphylococcus haemolyticus is one of the most significant coagulase-negative staphylococci, and it often causes severe infections. Rapid strain typing of pathogenic S. haemolyticus is indispensable in modern public health infectious disease control, facilitating the identification of the origin of infections to prevent further infectious outbreak. Rapid identification enables the effective control of pathogenic infections, which is tremendously beneficial to critically ill patients. However, the existing strain typing methods, such as multi-locus sequencing, are of relatively high cost and comparatively time-consuming. A practical method for the rapid strain typing of pathogens, suitable for routine use in clinics and hospitals, is still not available. Matrix-assisted laser desorption ionization-time of flight mass spectrometry combined with machine learning approaches is a promising method to carry out rapid strain typing. In this study, we developed a statistical test-based method to determine the reference spectrum when dealing with alignment of mass spectra datasets, and constructed machine learning-based classifiers for categorizing different strains of S. haemolyticus. The area under the receiver operating characteristic curve and accuracy of multi-class predictions were 0.848 and 0.866, respectively. Additionally, we employed a variety of statistical tests and feature-selection strategies to identify the discriminative peaks that can substantially contribute to strain typing. This study not only incorporates statistical test-based methods to manage the alignment of mass spectra datasets but also provides a practical means to accomplish rapid strain typing of S. haemolyticus.