Test Of Statistical Independence Research Articles

An empirical study on web API usability: The consumer-developer perspective

The ease with which web APIs facilitate access to diverse resources and services has led to their widespread adoption, consequently giving rise to a new business paradigm: the “API economy”. Given this, usability has become a pivotal attribute for API adoption, and within a competitive market, it merits detailed investigation. This exploratory study presents the findings of a survey targeting both consumers and developers of web APIs. The primary objectives of this survey were (1) to ascertain how respondents perceive various usability factors and (2) to identify potential correlations between specific characteristics of participant profiles and their expressed opinions. To fulfill these objectives, descriptive statistical parameters and independence tests were employed. Results indicate that documentation is regarded as the most influential factor on usability, while the quantity of consecutive parameters of the same type is perceived as the least influential. Furthermore, the findings reveal that expert opinions do not deviate significantly from those of non-experts, and that a respondent's experience as a software developer and with web APIs can influence their perceptions regarding certain factors.

Tourism efficiency and quality of life in Chinese cities

PurposeThis paper aims to investigate the relationship between tourism efficiency at the city level and the quality of life (QOL) of residents. It focuses on assessing whether more efficient tourism cities in China, from an economic standpoint, also offer a higher quality of life for their residents.Design/methodology/approachA sample of 40 Chinese cities from 2010 to 2019 is analyzed. The study first employs Data Envelopment Analysis to construct a production technology and estimate the technical tourism efficiency of each city. Subsequently, a nonparametric statistical test of independence is applied yearly to explore potential relationships between the cities’ tourism efficiency rankings and their residents’ QOL. This latter is measured by constructing an index for each city following the OECD framework.FindingsThe findings of the study are mixed, revealing no clear relationship between tourism efficiency and residents’ quality of life within the analyzed period. This suggests a complex interplay between economic efficiency in tourism and the broader social and environmental factors contributing to QOL.Originality/valueThis study enhances the literature on tourism efficiency by investigating the relationship between tourism efficiency and QOL, an aspect frequently overlooked in efficiency evaluations. Our approach offers a comprehensive understanding of the interplay between economic performance in the tourism sector and the social well-being of city populations. To the best of the authors’ knowledge, this is the first instance where such a relationship has been explored at the city level within the Chinese context.

Nursing diagnoses in patients undergoing prostatectomy at the central hospital of Nampula, 1st semester of 2019

Introduction: The nursing diagnosis is a clinical assessment of a human response to health conditions/life processes, or a vulnerability to that response, by an individual, family, group or community. The research aims to describe the main nursing diagnoses in patients undergoing prostatectomy admitted to Surgery II at the Hospital Central de Nampula. Objectives: This is a descriptive study with a quantitative approach, involving patients admitted to surgery II undergoing prostatectomy. All patients with the medical diagnosis of benign prostatic hyperplasia or prostate cancer who underwent prostate surgery were included, thus all patients who underwent prostate surgery but who had other chronic diseases were excluded. Data were analyzed with SPSS statistical package to obtain descriptive analysis, percentage and use of the following Q-square statistical test of independence. Results: the study involved 33 patients undergoing prostatectomy, 54.5% of these patients had primary schooling and the most predominant age group was 66-75 years old (39.4%). A total of 461 nursing diagnoses were found, and the most frequent were: Impaired walking 5.4%, Constipation 4.8, Risk of infection 6.9, Risk of vascular trauma 7.4%, Acute pain 5.4% and Deficit in self-care for bathing 6.7%. The following diagnoses were associated with the nursing diagnosis: impaired walking p value 0.000, dentition p value 0.006, constipation (p value 0.001), risk of electrolyte imbalance p value 0.000) and risk of falls (p value 0.000). Conclusion: the use of the nursing process by nurses facilitates the survey of health problems in sick patients in order to intervene in care using real nursing diagnoses, risk and health promotion.

Kernel-based joint independence tests for multivariate stationary and non-stationary time series.

Multivariate time-series data that capture the temporal evolution of interconnected systems are ubiquitous in diverse areas. Understanding the complex relationships and potential dependencies among co-observed variables is crucial for the accurate statistical modelling and analysis of such systems. Here, we introduce kernel-based statistical tests of joint independence in multivariate time series by extending the d-variable Hilbert-Schmidt independence criterion to encompass both stationary and non-stationary processes, thus allowing broader real-world applications. By leveraging resampling techniques tailored for both single- and multiple-realization time series, we show how the method robustly uncovers significant higher-order dependencies in synthetic examples, including frequency mixing data and logic gates, as well as real-world climate, neuroscience and socio-economic data. Our method adds to the mathematical toolbox for the analysis of multivariate time series and can aid in uncovering high-order interactions in data.

Accreditation Outcomes: Does Program Director Experience Matter?

The program director (PD) is responsible for providing effective leadership and possessing knowledge of accreditation. The aim of this study was to evaluate whether a PD's experience in higher education affects the accreditation outcome. This cross-sectional study includes Physician Assistant (PA) programs that underwent an accreditation visit between January 2012 and January 2022. Data analysis was primarily descriptive, stratified by demographic variables, and outcomes of accreditation standards. Inferential analysis included chi-squared tests of statistical independence. The chi-squared analysis test of statistical independence of PD's experience and accreditation decision identified a statistically significant association between the PD's experience as a PD and the accreditation outcome for continuing reviews. However, a minimum of 3 years of experience in higher education and the accreditation outcome were statistically independent for provisional and continuing reviews. Few PDs are hired with more than 3 years of PD experience, but they tend to have more higher education or PA program educational experience. A PD's years of higher education experience was not associated with accreditation outcome, which may suggest that other supports are more critical for achieving and maintaining accreditation.

Accurate detection of shared genetic architecture from GWAS summary statistics in the small-sample context.

Assessment of the genetic similarity between two phenotypes can provide insight into a common genetic aetiology and inform the use of pleiotropy-informed, cross-phenotype analytical methods to identify novel genetic associations. The genetic correlation is a well-known means of quantifying and testing for genetic similarity between traits, but its estimates are subject to comparatively large sampling error. This makes it unsuitable for use in a small-sample context. We discuss the use of a previously published nonparametric test of genetic similarity for application to GWAS summary statistics. We establish that the null distribution of the test statistic is modelled better by an extreme value distribution than a transformation of the standard exponential distribution. We show with simulation studies and real data from GWAS of 18 phenotypes from the UK Biobank that the test is to be preferred for use with small sample sizes, particularly when genetic effects are few and large, outperforming the genetic correlation and another nonparametric statistical test of independence. We find the test suitable for the detection of genetic similarity in the rare disease context.

Factors associated with Australian preconception and pregnant women's nutrition and nutrient supplement knowledge

AbstractAimTo describe factors associated with women's knowledge of nutrition, knowledge of nutrient supplements and use of supplements that are routinely recommended during preconception and pregnancy.MethodsParticipants (women 18–45 years, pregnant or planning pregnancy) were recruited from a consumer survey panel and completed an online, custom‐built questionnaire. Responses were used to calculate individual scores for nutrition knowledge (range 0–30) and supplements knowledge (range 0–10), where higher scores indicated better knowledge, and determine use of routinely recommended supplements (yes/no). Statistical tests of independence were used to explore associations between these outcomes and 68 variables derived from the survey.ResultsOf 2289 respondents, 776 were eligible and 624 (80.4%) completed the survey. Among pregnant women (N = 144) and those planning a pregnancy (N = 480), nutrition knowledge and supplements knowledge was limited, and daily use of routinely recommended supplements was low (63.5% pregnant, 40.1% planners). The odds of appropriate supplement use was strongly associated with health literacy adequacy. There was a low positive correlation between supplements beliefs and nutrition/supplements knowledge. Nutrition and supplements knowledge was associated with information provided by a wider number of health and allied health services during preconception than during pregnancy.ConclusionHealthcare providers are central to preconception and pregnancy dietary and nutrient supplement advice. Our data reinforce the role of adequate health literacy in applying this advice and suggest that an understanding of women's beliefs about supplements and targeting the source of the information to women at different stages (preconception or pregnant), could be used to better tailor these communications.

The Investments in Human Capital within the Human Capital Management and the Impact on the Enterprise’s Performance

Human capital (HC) is a key factor for enterprises’ performance and competitiveness. The aim of this study was to identify how enterprises in Slovakia perceive the impact of the investments in HC on business performance within the context of the implementation of human capital management (HCM). The content analysis was applied to analyze the different authors’ opinions on the substance of HC. These opinions were compared, and the knowledge obtained was synthesized. The article’s originality stems from the evaluation of the results from a unique questionnaire survey conducted with a specific focus on IT companies. This follows the presumption that these companies approach the application of HCM in an exemplary way, while being considered knowledge intensive. To collect the primary data, a questionnaire survey was performed in 113 Slovak IT enterprises and its results were analyzed using statistical tests of independence. The main findings include the corroboration of a positive effect of investments in the employees’ education and the implementation of HCM on the enterprises’ performance. Despite this, more than a third of the enterprises did not evaluate the effectiveness of investment in HC, and more than half of enterprises did not have the HCM concept implemented. Several solutions are recommended with respect to the HR managers’ training.

Reasons referred by individuals who were not on kidney transplantation waiting lists.

To describe the reasons reported by individuals in hemodialysis that were not registered on kidney transplantation waiting lists. Cross-sectional study conducted in six renal replacement therapy services in Rio Grande do Sul, Brazil with 214 individuals undergoing hemodialysis who reported the reasons for not being registered on kidney transplantation waiting lists. The data collection was carried out through a questionnaire from March 2016 to March 2017. The Stata software was used to the statistical analysis and independence test. The main reasons reported by the 214 individuals who were not registered on kidney transplantation waiting lists were due to the lack of information of the individuals, not wanting to be on list, due to morbidities and age. The lack of information was associated with the variables low education, male, ≤ 5 years of time since diagnosis and ≤ 5 years in renal replacement therapy. The reason for not wanting to be on the list was associated with the variables illiteracy and age.

Trajectory Clustering for Air Traffic Categorisation

Availability of different types of data and advances in data-driven techniques open the path to more detailed analyses of various phenomena. Here, we examine the insights that can be gained through the analysis of historical flight trajectories, using data mining techniques. The goal is to learn about usual (or nominal) choices airlines make in terms of routing, and their relation with aircraft types and operational flight costs. The clustering is applied to intra-European trajectories during one entire summer season, and a statistical test of independence is used to evaluate the relations between the variables of interest. Even though about half of all flights are less than 1000 km long, and mostly operated by one airline, along one trajectory, the analysis shows that, for longer flights, there exists a clear relation between the trajectory clusters and the operating airlines (in about 49% of city pairs) and/or the aircraft types (30%), and/or the flight costs (45%).

A population level study into health vulnerabilities of mothers and fathers involved in public law care proceedings in Wales, UK between 2011 and 2019

IntroductionUnder section 31 of the Children Act 1989, public law care proceedings can be issued if there is concern a child is subject to, or at risk of significant harm, which can lead to removal of a child from parents. Appropriate and effective health and social support are required to potentially prevent some of the need for these proceedings. More comprehensive evidence of the health needs and vulnerabilities of parents will enable enhanced response from family courts and integrated other services. ObjectiveTo examine health vulnerabilities of parents involved in care proceedings in the two-year period prior to involvement. MethodsFamily court data provided by Cafcass Cymru were linked to population-based health records held within the Secure Anonymised Information Linkage Databank. Linked data were available for 8,821 parents of children involved in care proceedings between 2011 and 2019. Findings were benchmarked with reference to a comparison group of parents matched on sex, age, and deprivation (n = 32,006), not subject to care proceedings. Demographic characteristics, overall health service use, and health profiles of parents were examined. Descriptive and statistical tests of independence were used. ResultsNearly half of cohort parents (47.6%) resided in the most deprived quintile. They had higher levels of healthcare use compared to the comparison group across multiple healthcare settings, with the most pronounced differences for emergency department attendances (59.3% vs 37.0%). Health conditions with the largest variation between groups were related to mental health (43.6% vs 16.0%), substance use (19.4% vs 1.6%) and injuries (41.5% vs 23.6%). ConclusionThis study highlights the heightened socioeconomic and health vulnerabilities of parents who experience care proceedings concerning a child. Better understanding of the needs and vulnerabilities of this population may provide opportunities to improve a range of support and preventative interventions that respond to crises in the community.

Analyzing Markov Boundary Discovery Algorithms in Ideal Conditions Using the d-Separation Criterion

This article proposes the usage of the d-separation criterion in Markov Boundary Discovery algorithms, instead of or alongside the statistical tests of conditional independence these algorithms usually rely on. This is a methodological improvement applicable when designing, studying or improving such algorithms, but it is not applicable for productive use, because computing the d-separation criterion requires complete knowledge of a Bayesian network. Yet Bayesian networks can be made available to the algorithms when studied in controlled conditions. This approach has the effect of removing sources of suboptimal behavior, allowing the algorithms to perform at their theoretical best and providing insights about their properties. The article also discusses an extension of this approach, namely to use d-separation as a complement to the usual statistical tests performed on synthetic datasets in order to ascertain the overall accuracy of the tests chosen by the algorithms, for further insights into their behavior. To exemplify these two approaches, two Markov Boundary Discovery algorithms were used, namely the Incremental Association Markov Blanket algorithm and the Iterative Parent–Child-Based Search of Markov Blanket algorithm. Firstly, these algorithms were configured to use d-separation alone as their conditional independence test, computed on known Bayesian networks. Subsequently, the algorithms were configured to use the statistical G-test complemented by d-separation to evaluate their behavior on synthetic data.

A local method for identifying causal relations under Markov equivalence

Causality is important for designing interpretable and robust methods in artificial intelligence research. We propose a local approach to identify whether a variable is a cause of a given target under the framework of causal graphical models of directed acyclic graphs (DAGs). In general, the causal relation between two variables may not be identifiable from observational data as many causal DAGs encoding different causal relations are Markov equivalent. In this paper, we first introduce a sufficient and necessary graphical condition to check the existence of a causal path from a variable to a target in every Markov equivalent DAG. Next, we provide local criteria for identifying whether a variable is a cause/non-cause of a target based only on the local structure instead of the entire graph. Finally, we propose a local learning algorithm for this causal query via learning the local structure of the variable and some additional statistical independence tests related to the target. Simulation studies show that our local algorithm is efficient and effective, compared with other state-of-art methods.

E-BANKING SECURITY DILEMMAS OF USERS LIVING IN RURAL AREAS – THE CASE OF KONIN COUNTY IN WIELKOPOLSKA

The aim of the study was to identify selected threats to e-banking security in the opinion of rural residents, on the case of Konin County. Available e-banking services were analysed against the background of cybercrime threats. The research was conducted in the year 2019. In the spatial scope, it concerned Wielkopolska and the territory of the Konin County, which consists of 14 municipalities, including 5 urban-rural municipalities and 9 rural municipalities. Using the method of diagnostic survey, on a sample of almost 400 people invited to the study, the results were collected. The majority of respondents were rural residents. The survey questionnaire consisted of 22 closed questions and information data. Suggested answers were programmed according to a five-point Likert scale. The study used Pearson’s chi-square statistical test of independence, comparative and descriptive analysis. Calculations were performed in MS Excel. As a result, a relatively high level of interest in e-banking among the residents of Konin county was indicated. More than 90% of respondents, primarily rural residents, use online banking. This is especially applicable to retail payments, as well as successive control of the household budget. E-banking’s usability is mostly determined by: time saving, a widespread availability of services and convenience. Despite the awareness of risks, the level of security of online banking inspires confidence among respondents. Therefore, social and legal responsibility of the banking sector for electronic transaction security is recommended. This is justified by the majority of respondent opinions that traditional banking will be eliminated in the future by e-commerce tools, including e-banking.

Online Streaming Features Selection via Markov Blanket

Streaming feature selection has always been an excellent method for selecting the relevant subset of features from high-dimensional data and overcoming learning complexity. However, little attention is paid to online feature selection through the Markov Blanket (MB). Several studies based on traditional MB learning presented low prediction accuracy and used fewer datasets as the number of conditional independence tests is high and consumes more time. This paper presents a novel algorithm called Online Feature Selection Via Markov Blanket (OFSVMB) based on a statistical conditional independence test offering high accuracy and less computation time. It reduces the number of conditional independence tests and incorporates the online relevance and redundant analysis to check the relevancy between the upcoming feature and target variable T, discard the redundant features from Parents-Child (PC) and Spouses (SP) online, and find PC and SP simultaneously. The performance OFSVMB is compared with traditional MB learning algorithms including IAMB, STMB, HITON-MB, BAMB, and EEMB, and Streaming feature selection algorithms including OSFS, Alpha-investing, and SAOLA on 9 benchmark Bayesian Network (BN) datasets and 14 real-world datasets. For the performance evaluation, F1, precision, and recall measures are used with a significant level of 0.01 and 0.05 on benchmark BN and real-world datasets, including 12 classifiers keeping a significant level of 0.01. On benchmark BN datasets with 500 and 5000 sample sizes, OFSVMB achieved significant accuracy than IAMB, STMB, HITON-MB, BAMB, and EEMB in terms of F1, precision, recall, and running faster. It finds more accurate MB regardless of the size of the features set. In contrast, OFSVMB offers substantial improvements based on mean prediction accuracy regarding 12 classifiers with small and large sample sizes on real-world datasets than OSFS, Alpha-investing, and SAOLA but slower than OSFS, Alpha-investing, and SAOLA because these algorithms only find the PC set but not SP. Furthermore, the sensitivity analysis shows that OFSVMB is more accurate in selecting the optimal features.

The pitfalls of inferring virus-virus interactions from co-detection prevalence data: application to influenza and SARS-CoV-2.

There is growing experimental evidence that many respiratory viruses—including influenza and SARS-CoV-2—can interact, such that their epidemiological dynamics may not be independent. To assess these interactions, standard statistical tests of independence suggest that the prevalence ratio—defined as the ratio of co-infection prevalence to the product of single-infection prevalences—should equal unity for non-interacting pathogens. As a result, earlier epidemiological studies aimed to estimate the prevalence ratio from co-detection prevalence data, under the assumption that deviations from unity implied interaction. To examine the validity of this assumption, we designed a simulation study that built on a broadly applicable epidemiological model of co-circulation of two emerging or seasonal respiratory viruses. By focusing on the pair influenza–SARS-CoV-2, we first demonstrate that the prevalence ratio systematically underestimates the strength of interaction, and can even misclassify antagonistic or synergistic interactions that persist after clearance of infection. In a global sensitivity analysis, we further identify properties of viral infection—such as a high reproduction number or a short infectious period—that blur the interaction inferred from the prevalence ratio. Altogether, our results suggest that ecological or epidemiological studies based on co-detection prevalence data provide a poor guide to assess interactions among respiratory viruses.

A population level study into health vulnerabilities of mothers and fathers involved in public law care proceedings in Wales, UK between 2011 and 2019

IntroductionUnder section 31 of the Children Act 1989, public law care proceedings can be issued if there is concern a child is subject to, or at risk of significant harm, which can lead to removal of a child from parents. Appropriate and effective health and social support are required to potentially prevent some of the need for these proceedings. More comprehensive evidence of the health needs and vulnerabilities of parents will enable enhanced response from family courts and integrated other services.ObjectiveTo examine health vulnerabilities of parents involved in care proceedings in the two-year period prior to involvement.MethodsFamily court data provided by Cafcass Cymru were linked to population-based health records held within the Secure Anonymised Information Linkage Databank. Linked data were available for 8,821 parents of children involved in care proceedings between 2011 and 2019. Findings were benchmarked with reference to a comparison group of parents matched on sex, age, and deprivation (n = 32,006), not subject to care proceedings. Demographic characteristics, overall health service use, and health profiles of parents were examined. Descriptive and statistical tests of independence were used.ResultsNearly half of cohort parents (47.6%) resided in the most deprived quintile. They had higher levels of healthcare use compared to the comparison group across multiple healthcare settings, with the most pronounced differences for emergency department attendances (59.3% vs 37.0%). Health conditions with the largest variation between groups were related to mental health (43.6% vs 16.0%), substance use (19.4% vs 1.6%) and injuries (41.5% vs 23.6%).ConclusionThis study highlights the heightened socioeconomic and health vulnerabilities of parents who experience care proceedings concerning a child. Better understanding of the needs and vulnerabilities of this population may provide opportunities to improve a range of support and preventative interventions that respond to crises in the community.

Export as a Factor Boosts SMEs Internationalization

RESEARCH OBJECTIVE: The aim of the article is to examine the role and importance of factors: (1) company size on the value of generated exports, (2) the aspect of the country of origin of enterprise on the value of generated exports and also (3) to define relations between these two factors.
 THE RESEARCH PROBLEM AND METHODS: SMEs are of particular importance for all micro and macroeconomic indicators. Their specificity and peculiarity, manifested in the possibility of fast adaptation to a turbulent economic environment, which affects their effectiveness on foreign markets. The issue was considered on the basis of the analysis of the relevant literature and the results of own research with the use of two-factor analysis of variance and χ2 test.
 THE PROCESS OF ARGUMENTATION: Based on the relevant literature and the organisation theory, groups of factors determining the internationalisation processes of SMEs are described and then export results for selected EU countries are presented. To obtain the presented research results, tools of mathematical analysis and statistical tests of independence were applied.
 RESEARCH RESULTS: The obtained causal relations and theoretical-empirical conclusions point to export as a factor stimulating SMEs internationalisation, which is directly correlated with the examined factors due to the lack of sufficient evidence to reject the adopted research hypotheses regarding the independence of the examined correlations.
 CONCLUSION, INNOVATIONS, AND RECOMENDATIONS: It has been proved that the size of enterprises and the country they come from influence the value of exports generated by them, and a direct relationship between these factors has been proven to exist. It is important to determine the so-called country barriers, the elimination of which through the creation of conditions conducive to SME development on both the national and top-down EU policy level may favour the development of internationalisation of this sector.

Perception of cosmetics quality in China – comparison between young and older consumers

PurposeThe aim of the paper is to explore how Chinese consumers perceive the quality of cosmetics products and if the Chinese youth differs in the perception from older generations. The paper fills the current research gap in revealing which intrinsic and extrinsic parameters are the most and least associated with cosmetic products’ quality by young and older Chinese consumers. It also inquiries about how other selected factors (e.g. type of store, store’s trade name, the use of influencers, etc.) contribute to the perceived quality of cosmetic products.Design/methodology/approachPrimary data were collected from 423 Chinese respondents by an online questionnaire in their native language. Statistical tests of independence, correlation and cluster analysis were applied to reveal the relationships between variables.FindingsThe highest number of statistically significant dependencies of meritorious variables was associated with age groups of young and older consumers, thus suggesting greater differences in quality perception between younger and older Chinese generations. The paper also confirms that intrinsic cues prevail over extrinsic when consumers evaluate the quality of cosmetic products.Practical implicationsThe results deepen the understanding of the current preferences of Chinese consumers of cosmetic products when assessing the quality of cosmetics and represent a solid basis for further research. Moreover, they may help companies from the cosmetics industry better comprehend how different categories of people determine cosmetic products’ quality.Originality/valueThe paper uses a large convenience sample of respondents from different Chinese regions and points to several differences between younger and older generations of Chinese consumers of cosmetics.

On the Exponential Approximation of Type II Error Probability of Distributed Test of Independence

This paper studies distributed binary test of statistical independence under communication (information bits) constraints. While testing independence is very relevant in various applications, distributed independence test is particularly useful for event detection in sensor networks where data correlation often occurs among observations of devices in the presence of a signal of interest. By focusing on the case of two devices because of their tractability, we begin by investigating conditions on Type I error probability restrictions under which the minimum Type II error admits an exponential behavior with the sample size. Then, we study the finite sample-size regime of this problem. We derive new upper and lower bounds for the gap between the minimum Type II error and its exponential approximation under different setups, including restrictions imposed on the vanishing Type I error probability. Our theoretical results shed light on the sample-size regimes at which approximations of the Type II error probability via error exponents became informative enough in the sense of predicting well the actual error probability. We finally discuss an application of our results where the gap is evaluated numerically, and we show that exponential approximations are not only tractable but also a valuable proxy for the Type II probability of error in the finite-length regime.