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Identifying factors that associate with more cited or higher quality research may be useful to improve science or to support research evaluation. This article reviews evidence for the existence of such factors in article text and metadata. It also reviews studies attempting to estimate article quality or predict long‐term citation counts using statistical regression or machine learning for journal articles or conference papers. Although the primary focus is on document‐level evidence, the related task of estimating the average quality scores of entire departments from bibliometric information is also considered. The review lists a huge range of factors that associate with higher quality or more cited research in some contexts (fields, years, journals) but the strength and direction of association often depends on the set of papers examined, with little systematic pattern and rarely any cause‐and‐effect evidence. The strongest patterns found include the near universal usefulness of journal citation rates, author numbers, reference properties, and international collaboration in predicting (or associating with) higher citation counts, and the greater usefulness of citation‐related information for predicting article quality in the medical, health and physical sciences than in engineering, social sciences, arts, and humanities. [ABSTRACT FROM AUTHOR]

This paper explores the effect of publishing a data paper in the Open Access journal Data in Brief (DIB) on the citation counts of the related research paper. Using regression analysis, citation content analysis and a survey method, we investigate whether research papers with a related data paper have higher citation counts and the potential reasons. After controlling variables that correlate with the citation counts, research papers with a related data paper were found to have higher citation counts than those published in the same issue of the same journal. Next, we explored the causal relationship between the two variables by surveying the corresponding authors of 618 papers who shared datasets in DIB from 2014 to 2021. The results show that the authors acknowledge the benefits of sharing data in DIB, including citation increase and career reputation enhancement. We further explored how the data papers in DIB increase the citations of the related research papers by using citation content analysis. We found that scientists co‐cite the data papers and their related research papers for the purpose of reusing the underlying data or portraying a better understanding of the underlying data and related research articles. [ABSTRACT FROM AUTHOR]

This article explores the factors influencing the future citations of conference papers. We concentrated on the explanatory power of early attention on conference papers for citations collected from Google Scholar and Scopus. The early attention data includes users' online activities in a conference support system: CN3. Bookmarks from the bibliographic management system, Citeulike, were used as a collateral source of early attention. To examine the chronological contributions of 13 factors on citations, a multiple sequential regression analysis was conducted for three timepoints of the publication cycle—paper submission, time of conferences, and months after conferences. Our results illustrate that online readers' early attention of Citeulike bookmarks were found to have the most influence on the future impact of the conference papers. The early attention records from CN3 made noteworthy improvements to explaining both the Google and Scopus citations as well. We also found that the type of papers the number of papers presented at a conference, and the best article award records were significant factors influencing future citations. However, the magnitude of the effects made by online readers' early attention from both sources appears to be larger than these three traditional factors. [ABSTRACT FROM AUTHOR]

Near Infrared Spectroscopy (NIRS), as one of analysis technologies, has shown promisingly industrial applications for significant properties for recent decades such as fast response, preciseness, non-intrusion etc. Here, the authors employed NIRS coupled with a series of physical and chemical tests to assess the ageing condition of oil-paper insulation, which is responsible for the main insulation type of high-voltage power transformer. Among these procedures, the data analytic algorithms are of utmost importance to determine the evaluation precision. After plenty of trial-and-error, Savitzky-Golay (S-G) convolution was finally utilised to de-noise samples and improve the spectral data quality. The competitive adaptive reweighted sampling (CARS) was used to select the optimal wavelength combination of NIRS, which is found able to fully extract the effectively spectral information and reduce dimensions of spectral data. Based on the above-mentioned techniques, the quantitative analysis model of NIRS was established by partial least squares (PLS), which could synthetically process the spectral data and the degree of polymerisation (DP) of paper samples. The results indicated that compared with the traditional detection methods, the NIRS analysis is a powerful and informative tool to characterise the condition of oil-paper insulation without intrusion or damage to transformers. [ABSTRACT FROM AUTHOR]

Compared to previous studies that generally detect scientific breakthroughs based on citation patterns, this article proposes a knowledge entity‐based disruption indicator by quantifying the change of knowledge directly created and inspired by scientific breakthroughs to their evolutionary trajectories. Two groups of analytic units, including MeSH terms and their co‐occurrences, are employed independently by the indicator to measure the change of knowledge. The effectiveness of the proposed indicators was evaluated against the four datasets of scientific breakthroughs derived from four recognition trials. In terms of identifying scientific breakthroughs, the proposed disruption indicator based on MeSH co‐occurrences outperforms that based on MeSH terms and three earlier citation‐based disruption indicators. It is also shown that in our indicator, measuring the change of knowledge inspired by the focal paper in its evolutionary trajectory is a larger contributor than measuring the change created by the focal paper. Our study not only offers empirical insights into conceptual understanding of scientific breakthroughs but also provides practical disruption indicator for scientists and science management agencies searching for valuable research. [ABSTRACT FROM AUTHOR]

Abstract: Introduction: The cohort of students enrolled in the discipline‐specific bioscience paper reflects a structural diversity in that it includes students of multiple ethnicities, varied age groups, differing scholastic and life experiences. These divergent identities of students are known to influence academic performance. The purpose of this retrospective quantitative study was to determine the ability of a set of variables such as age, gender, ethnicity, level of prior education, the place from which prior education was obtained, work experience and prior academic achievement to predict academic performance in the discipline‐specific bioscience paper. Method: The sample for this study was a purposive sample of all oral health students who had enrolled in the paper at the Auckland University of Technology from 2011 to 2014. The desensitised empirical data of 116 students from the University's database were subject to multivariable regression analysis. Pearson's correlation coefficients were calculated. Results: Prior academic achievement was a statistically significant predictor variable (P < 0.001) for the academic performance in the discipline‐specific bioscience paper and was also positively correlated (r = 0.641, P < 0.001) to the grades in the discipline‐specific bioscience paper. Conclusion: Prior academic achievement was the only variable that was demonstrated to be correlated to and predictive of the academic performance in the discipline‐specific bioscience paper. [ABSTRACT FROM AUTHOR]

The treatment of bleaching-effluent from pulp and paper industry was investigated in a batch electrocoagulation (EC) reactor using aluminium as sacrificial electrodes. The response surface methodology (RSM) was employed to evaluate the individual and interactive effects of four independent parameters viz., current density (j: 5-25 mA/cm2), initial pH (pHo: 5-9), electrolyte (NaCl) concentration (c: 0-2 g/L) and electrolysis time (t: 10-30 min) on Colour, COD and BOD removal efficiency. The results were analyzed using Pareto analysis of variance (ANOVA). Based on RSM analysis, a second-order polynomial regression model was developed and found to be good fit with experimental results. © 2011 American Institute of Chemical Engineers Environ Prog, 2011 [ABSTRACT FROM AUTHOR]

In recent years, the relationship of collaboration among scientists and the citation impact of papers have been frequently investigated. Most of the studies show that the two variables are closely related: An increasing collaboration activity (measured in terms of number of authors, number of affiliations, and number of countries) is associated with an increased citation impact. However, it is not clear whether the increased citation impact is based on the higher quality of papers that profit from more than one scientist giving expert input or other (citation-specific) factors. Thus, the current study addresses this question by using two comprehensive data sets with publications (in the biomedical area) including quality assessments by experts (F1000Prime member scores) and citation data for the publications. The study is based on more than 15,000 papers. Robust regression models are used to investigate the relationship between number of authors, number of affiliations, and number of countries, respectively, and citation impact-controlling for the papers' quality (measured by F1000Prime expert ratings). The results point out that the effect of collaboration activities on impact is largely independent of the papers' quality. The citation advantage is apparently not quality related; citation-specific factors (e.g., self-citations) seem to be important here. [ABSTRACT FROM AUTHOR]

Background Paper food and gastrointestinal ( GI) symptom journals are used to help irritable bowel syndrome ( IBS) patients determine potential trigger foods. The primary aim of this study was to evaluate the feasibility, usability, and clinical utility of such journals as a data collection tool. A secondary aim was to explore a method for analyzing journal data to describe patterns of diet and symptoms. Methods Participants (N=17) were asked to log three sets of 3-day food and symptom journals over a 15-day period. Feasibility was evaluated by journal completion rates, symptom logging compliance, and logging fatigability. The feasibility, usability, and clinical utility of journaling were also assessed by a customized evaluation and exit interview. For each journal, regression analyses were conducted to examine relationships between key meal nutrients and subsequent symptoms. Key Results Most participants were young (mean age 35±12) Caucasian (N=13) women (N=14). Journal completion rates were 100% for all participants with no logging fatigability. Over half perceived paper journaling of food and symptoms as feasible, usable, and clinically useful. Thirteen participants demonstrated a strong association with at least one symptom and meal nutrient. Patterns of associations differed among participants. Conclusions and Inferences Paper journaling of food and GI symptoms for 9 days over a 15-day period appeared to be a feasible and usable data collection tool for IBS patients. Over half perceived journaling as at least somewhat clinically useful. Findings from this study support the anecdote that food trigger(s) and associated symptom(s) vary for each individual. [ABSTRACT FROM AUTHOR]

Scientific novelty drives the efforts to invent new vaccines and solutions during the pandemic. First‐time collaboration and international collaboration are two pivotal channels to expand teams' search activities for a broader scope of resources required to address the global challenge, which might facilitate the generation of novel ideas. Our analysis of 98,981 coronavirus papers suggests that scientific novelty measured by the BioBERT model that is pretrained on 29 million PubMed articles, and first‐time collaboration increased after the outbreak of COVID‐19, and international collaboration witnessed a sudden decrease. During COVID‐19, papers with more first‐time collaboration were found to be more novel and international collaboration did not hamper novelty as it had done in the normal periods. The findings suggest the necessity of reaching out for distant resources and the importance of maintaining a collaborative scientific community beyond nationalism during a pandemic. [ABSTRACT FROM AUTHOR]

Machine learning, a branch of artificial intelligence, is increasingly used in health research, including nursing and maternal outcomes research. Machine learning algorithms are complex and involve statistics and terminology that are not common in health research. The purpose of this methods paper is to describe three machine learning algorithms in detail and provide an example of their use in maternal outcomes research. The three algorithms, classification and regression trees, least absolute shrinkage and selection operator, and random forest, may be used to understand risk groups, select variables for a model, and rank variables' contribution to an outcome, respectively. While machine learning has plenty to contribute to health research, it also has some drawbacks, and these are discussed as well. To provide an example of the different algorithms' function, they were used on a completed cross‐sectional study examining the association of oxytocin total dose exposure with primary cesarean section. The results of the algorithms are compared to what was done or found using more traditional methods. [ABSTRACT FROM AUTHOR]

Objective: Only a minority of suicide decedents leave a suicide note. Typically, the notes are handwritten on paper; however, electronic suicide notes have been reported with increasing frequency. This emerging phenomenon remains generally under-researched. The aim of this study was to compare the psychosocial and clinical antecedents of suicide decedents who left E-notes with those who left paper notes or no notes.Method: The study was embedded in the Southwestern Ontario Suicide Study (SOSS). The SOSS was a three-year case series of consecutive deaths by suicide that occurred in the region between 2012 and 2014. Data on psychosocial and clinical antecedents were collected with a modified version of the Manchester questionnaire used in the UK.Results: Of the 476 suicides files reviewed, 45.8% contained a suicide note. A total of 383 separate suicide notes were left: 74.3% were paper notes and 25.7% were E-notes. The results of the multivariate regression analyses indicate that the likelihood of leaving a suicide note was negatively associated with a history of admissions to a mental health unit, while the likelihood of leaving an E-note was negatively associated with age, positively associated with presence of a mental disorder, and negatively associated with history of hospital admissions.Conclusions: Future studies with larger samples need to consider the timing of the text messages, and appraise whether there was the intent of seeking help or rescue in the text messages. [ABSTRACT FROM AUTHOR]

Often it is assumed that electronic recording by observers necessarily provides better quality data than pen-and-paper methods. Fifteen novice observers recorded rates of responding from 10 role-played video samples using one of three continuous recording input formats: keyboard (laptop), touchscreen (personal digital assistants), or pen-and-paper. We evaluated the quality of the observers' data compared with criterion records using calibration and interobserver agreement algorithms. Results of the calibration analysis revealed that observers in the touchscreen group produced the most consistently accurate and precise data, the keyboard group observers showed wide variation in precision and accuracy, and the pen-and-paper group observers were significantly less precise than the touchscreen group. We conclude that although electronic recording has the potential to be as accurate as, and more precise than, pen-and-paper methods, this is far from guaranteed. Analyses of observers' errors advise recommendations for improving data accuracy and precision when using each method. Copyright © 2014 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

Many English Examination Boards will make some use of the differentiated paper method of assessment in the new scheme of 16+ examining, but it is not clear whether problems of comparability have been adequately solved. This article presents an analysis based on well-defined assumptions incorporated into a measurement model and utilising regression. Marks on the paper not taken by a group are estimated from their joint marks on the common paper and the paper specific to their group. The marks are then weighted using the measurement model and combined to produce a rank order over both the groups. In an appendix, the weighting method used is related to the more usual method of weighting adopted when combining scores. [ABSTRACT FROM AUTHOR]

Two new methods have been proposed to determine unexpected sum scores on subtests (testlets) both for paper-and-pencil tests and computer adaptive tests. A method based on a conservative bound using the hypergeometric distribution, denoted ρ, was compared with a method where the probability for each score combination was calculated using a highest density region (HDR). Furthermore, these methods were compared with the standardized log-likelihood statistic with and without a correction for the estimated latent trait value (denoted as l*z and lz respectively). Data were simulated on the basis of the one-parameter logistic model, and both parametric and non-parametric logistic regression was used to obtain estimates of the latent trait Results showed that it is important to take the trait level into account when comparing subtest scores. In a nonparametric item response theory (IRT) context, on adapted version of the HDR method was a powerful alterative to ρ. In a parametric IRT context, results showed that l*z had the highest power when the data were simulated conditionally on the estimated latent trait level. [ABSTRACT FROM AUTHOR]

Citation data for institutes are generally provided as numbers of citations or as relative citation rates (as, for example, in the Leiden Ranking). These numbers can then be compared between the institutes. This study aims to present a new approach for the evaluation of citation data at the institutional level, based on regression models. As example data, the study includes all articles and reviews from the Web of Science for the publication year 2003 ( n = 886,416 papers). The study is based on an in-house database of the Max Planck Society. The study investigates how much the expected number of citations for a publication changes if it contains the address of an institute. The calculation of the expected values allows, on the one hand, investigating how the citation impact of the papers of an institute appears in comparison with the total of all papers. On the other hand, the expected values for several institutes can be compared with one another or with a set of randomly selected publications. Besides the institutes, the regression models include factors which can be assumed to have a general influence on citation counts (e.g., the number of authors). [ABSTRACT FROM AUTHOR]

Summary This paper discusses visualization methods for discriminant analysis. It does not address numerical methods for classification per se, but rather focuses on graphical methods that can be viewed as pre-processors, aiding the analyst's understanding of the data and the choice of a final classifier. The methods are adaptations of recent results in dimension reduction for regression, including sliced inverse regression and sliced average variance estimation. A permutation test is suggested as a means of determining dimension, and examples are given throughout the discussion. [ABSTRACT FROM AUTHOR]

Considering two-sided HT ht -values would not solve the problem, any departure of the goodness-of-fit test statistics from its median would be then interpreted as negative evidence of some level. As Sander Greenland points out, these should not be confused with the HT ht -values of realized goodness of-fit-test statistics. [Extracted from the article]

This article investigates empirically the comovements of the conditional mean and volatility of stock returns. It extends the results in the literature by demonstrating the role of the commercial paper-Treasury yield spread in predicting time variation in volatility. The conditional mean and volatility exhibit an asymmetric relation, which contrasts with the contemporaneous relation that has been tested previously. The volatility leads the expected return, and this time series relation is documented using offset correlations, short-horizon contemporaneous correlations, and a vector autoregression. These results bring into question the value of modeling expected returns as a constant function of conditional volatility. [ABSTRACT FROM AUTHOR]

This paper presents a quantitative comparison of peer versus bibliometric procedures for rating the quality of U.S. universities. The peer ratings used are the Roose-Andersen rating of the quality of graduate faculty in 10 scientific fields. The bibliometric ratings used are (1) the number of university papers in each field; (2) the average "quality" of the papers based on their citation rates, expressed as influence per paper in each field; and (3) total influence, the product of number of papers and influence per paper. The bibliometric ratings are based on 127,000 university papers, from 450 journals in 10 fields for 1965 to 1973. Roose-Andersen ranks and scores are found to correlate most highly with the total influence of the university's papers, followed closely by correlations with the total number of papers, and much less closely with the average influence per paper. A partial correlation and regression analysis indicate that the Roose-Andersen scores have two additive components: bibliometric size and bibliometric quality. Further analysis explores the extent to which a university's prestige in one department correlates with the assessment of other departments within that university, and the extent to which the university's overall bibliometric size correlates with the assessment of departments within that university. It is shown that the ratings of departments with- in a university are not independent, and that these dependencies are associated with the bibliometric size of the university. University ranks and scores in different fields are shown to be much more highly correlated when based on peer assessment than when based on bibliometric measures. [ABSTRACT FROM AUTHOR]

The consistent finding that internationally coauthored papers are more heavily cited has led to a tacit agreement among politicians and scientists that international collaboration in scientific research should be particularly promoted. However, existing studies of research collaboration suffer from a major weakness in that the Thomson Reuters Web of Science until recently did not link author names with affiliation addresses. The general approach has been to hierarchically code papers into international paper, national paper, or local paper based on the address information. This hierarchical coding scheme severely understates the level and contribution of local or national collaboration on an internationally coauthored paper. In this research, I code collaboration variables by hand checking each paper in the sample, use two measures of a paper's impact, and try several regression models. I find that both international collaboration and local collaboration are positively and significantly associated with a paper's impact, but international collaboration does not have more epistemic authority than local collaboration. This result suggests that previous findings based on hierarchical coding might be misleading. [ABSTRACT FROM AUTHOR]

Small mammal species richness and relative abundance vary along elevational gradients, but there are different patterns that exist. This study reports the patterns of distribution and abundance of small mammals along the broader elevational gradient of Mt. Qilian range. The study was conducted in the Mt. Qilian range, north-western China, from June to August 2001. Removal trapping was conducted using a standardized technique at 7 sites ranging between 1600 and 3900 m elevation within three transects. Correlation, regression and graphical analyses were used to evaluate the diversity patterns along this elevational gradient. In total, 586 individuals representing 18 nonvolant small mammal species were collected during 20 160 trap nights. Species composition was different among the three transects with 6 (33%) of the species found only within one transect. Elevational distribution and relative abundance of small rodents showed substantial spatial variation, with only 2 species showing nonsignificant capture frequencies across elevations. Despite these variations, some general patterns of elevational distribution emerged: humped-shape relationships between species diversity and elevation were noted in all three transects with diversity peaks at middle elevations. In addition, relative abundance was negatively correlated with elevation. Results indicate that maximum richness and diversity of nonvolant small mammals occurred at mid-elevations where several types of plants reached their maximum diversity and primary productivity, and where rainfall and humidity reached a maximum. It is demonstrated that the mid-elevation bulge is a general feature of at least a large portion of the biota on the Mt. Qilian range. [ABSTRACT FROM AUTHOR]

Objective In a study comparing eight sessions of fortnightly guided self-change (GSC) with 16 sessions of weekly cognitive behaviour therapy (CBT) in bulimia nervosa (BN) we examined pre-treatment predictors of outcome. Method Stepwise regression analyses were performed. Results In the GSC group, a lower pre-treatment binge frequency predicted better outcome at the end of treatment and at follow-up. In the CBT group, previous psychiatric disorder, absence of baseline depression and comorbidity predicted better outcome at the end of therapy and there was a trend for depression at baseline to predict a worse outcome at follow-up. Conclusion Those with more frequent bingeing may require a more intensive intervention than guided self-care. Copyright © 2000 John Wiley & Sons, Ltd and Eating Disorders Association. [ABSTRACT FROM AUTHOR]

This study investigated the extent to which seven papers on mechanical weed control have been cited, understood and utilised in subsequent publications. Web of Science was used to identify the citing publications, and citation content analysis was conducted to investigate the cognitive links between the citing and cited publications. Cognition involves acquiring, understanding, and using knowledge. Citation of the seven publications in 305 publications was classified, and it was found that perfunctory citations (those that were routinely referenced, with little effort to understand or use content) accounted for 53% of all citations and 16% of the citing articles included citations that were not supported by the references. The most striking finding was that key content was rarely used in articles, despite being referenced in 42% of the published articles. It is recommended that more time be allocated by authors to understanding literature, as this would appear to be a matter of diminishing concern for the scientific community. For those who assume their research area has a better citation practice than found in this study, it is recommended that authors conduct a citation content analysis within their own research area to increase the focus on good literature practices. [ABSTRACT FROM AUTHOR]

Are computer science papers extended after they are published? We have surveyed 200 computer science publications, 100 journal articles, and 100 conference papers, using self-citations to identify potential and actual continuations. We are interested in determining the proportion of papers that do indeed continue, how and when the continuation takes place, and whether any distinctions are found between the journal and conference populations. Despite the implicit assumption of a research line behind each paper, manifest in the ubiquitous 'future research' notes that close many of them, we find that more than 70% of the papers are never continued. [ABSTRACT FROM AUTHOR]

The article examines the relation between traditional and paper-and-pencil formal operations tasks in the U.S. The aim of the study was to provide information based on high school students' performance on both the Tomlinson-Keasey and Campbell measure and a set of traditional, individually administered tasks. The subjects used were 27 children from 9th- and 10th grade. The results of the study indicates that Pearson correlations between the traditional formal operations tasks and their paper-and-pencil analogs were generally low and nonsignificant.

In this paper, Gaussian Process Regression (GPR)‐based models which use the Bayesian approach to regression analysis problem such as load forecasting (LF) are proposed. The GPR is a non‐parametric kernel‐based learning method having the ability to provide correct predictions with uncertainty in measurements. The proposed model provides an hourly and monthly load forecast for an Australian city and four Indian cities in the Maharashtra state. Twelve GPR models are trained with historical datasets including hourly load and environmental data. To evaluate the trained model, the actual and predicted load demand curve is plotted and mean average percentage error (MAPE) is calculated corresponding to different kernel functions of the GPR model. To the best of the author's knowledge, the prediction of load demand using GPR for Indian cities of Maharashtra state has been made for the first time. The calculated MAPE in LF is 0.15% for Australia and 0.002%, 0.209%, 0.077%, and 0.140% for Indian cities viz. Nasik, Bhusawal, Kolhapur, and Aurangabad, respectively. The test results illustrate that minimum MAPE in load prediction is obtained using the proposed model that is GPR with 'Exponential' kernel functions. Furthermore, the comparative analysis with the existing approaches confirms the dominance of the proposed model. [ABSTRACT FROM AUTHOR]

In our 2011 survey of the literature in the Journal of Economic Surveys on the effect of government size on economic growth in wealthy countries we find a relatively consistent pattern: An increase in government size by 10 percentage points is associated with a 0.5-1 percentage point lower annual growth rate. This conclusion is questioned by Colombier. In this rejoinder we present a rebuttal of Colombier's argument based on a detailed scrutiny of his own statistical evidence and regression results. Furthermore, we note that several new papers that have appeared since our original paper was published give support to our main conclusion. [ABSTRACT FROM AUTHOR]

Solar photovoltaic energy is a vital renewable resource because it is clean, endless, and pollution‐free. Due to the fast growth of the semiconductor and power electronics sectors, photovoltaic (PV) technologies are climbing significant attention in modern electrical power applications. Operating PV energy conversion systems at the maximum power point is essential for getting the maximum power output and raising efficiency. This paper proposes a regression‐based Perturb and Observe method to quickly find a global maximum power point, avoiding being stuck in local maxima, likewise analytical and metaheuristic methods. The improved control focuses on the narrowed search areas by linear and non‐linear regression analyses using the generated PV model on a flexible Python environment. Furthermore, the method's accuracy is validated in real time under variable temperatures, irradiations, and loads. This method was proven with a hardware implementation. The proposed method is more than 98% accurate and can withstand long‐term modelling. The suggested regression‐based perturbation and observation method provided a short learning time and easy implementation. Additionally, the dynamic recorded results can be visualized for researchers to utilize efficiently. [ABSTRACT FROM AUTHOR]

UK top income shares have varied hugely over the past two centuries, ranging from more than 30% to less than 7% of pre‐tax national income allocated to the top 1 percentile. We build a congruent dynamic linear regression model of the top 1% income share allowing for economic, political and social factors. Saturation estimation is used to model outliers and trend breaks, proxying underlying structural changes driving income inequality in the UK. We use the model to forecast the top 1% income share over the last 15 years, and compare to a range of forecast devices. Despite a well‐specified constant parameter model conditioning on significant explanatory variables, the best performing forecasts are obtained from a random walk and a smoothed random walk. These results are explained by the presence of shifts in the income share over the forecast period, resulting in forecasts from equilibrium correction models converging to the wrong equilibrium. Our best prediction for 2026 based on the most recent data from 2021 (a 5‐year ahead projection) is that the pre‐tax top 1% income share will remain at the most recent realized value of 12.7%, but there is a large degree of uncertainty, with a 95% confidence band ranging from 10% to 15.7%. This paper is part of the Economica 100 Series. Economica, the LSE "house journal" is now 100 years old. To commemorate this achievement, we are publishing 100 papers by former students, as well as current and former faculty. David Forbes Hendry received his MSc and PhD from the LSE. [ABSTRACT FROM AUTHOR]

Under reasonable assumptions a formula is derived to project the number of citations the usual type of scientific research paper will receive. This projection, the paper's lifetime- citation rate, is based on the paper's past citations and the regularity of citation patterns. Hypothesis tests of equality of expected lifetime-citation rates per paper and multiple comparisons are also derived. With appropriate precautions comparisons may then be made of the work of scientists in similar fields who have been publishing for different lengths of time. The method is applied to the publications of members of a university department and validated in two ways. [ABSTRACT FROM AUTHOR]

As a common technology product in life, display screen has been deeply embedded in various fields, and the display performance is the key indicator to determine the quality of display products. The evaluation of screen flicker is one of the key control parameters to evaluate the optical performance of the screen. As the paper introduced, commonly there are two methods of testing flicker: FMA method and JEITA method. This paper makes a research about the above two evaluation methods in time and frequency domain. Particularly, by using nonlinear regression of the mathematical statistics, this paper deduces the mathematical relationship of the two methods for the evaluating in the normal data field. Also, this paper gives accurate conversion formula and the precision analysis. By using the empirical formula, the complexity of existing test equipment can be simplified, the cost and test time can be saved greatly. [ABSTRACT FROM AUTHOR]

Analytic methods development, like many other disciplines, relies on experimentation and data analysis. Determining the contribution of a paper or report on a study incorporating data analysis is typically left to the reviewer's experience and good sense, without reliance on structured guidelines. This is amplified by the growing role of machine learning driven analysis, where results are based on computer intensive algorithm applications. The evaluation of a predictive model where cross validation was used to fit its parameters adds challenges to the evaluation of regression models, where the estimates can be easily reproduced. This lack of structure to support reviews increases uncertainty and variability in reviews. In this paper, aspects of statistical assessment are considered. We provide checklists for reviewers of applied statistics work with a focus on analytic method development. The checklist covers six aspects relevant to a review of statistical analysis, namely: (1) study design, (2) algorithmic and inferential methods in frequentism analysis, (3) Bayesian methods in Bayesian analysis (if relevant), (4) selective inference aspects, (5) severe testing properties and (6) presentation of findings. We provide a brief overview of these elements providing references for a more elaborate treatment. The robustness analysis of an analytical method is used to illustrate how an improvement can be achieved in response to questions in the checklist. The paper is aimed at both engineers and seasoned researchers. [ABSTRACT FROM AUTHOR]

An introduction is presented in which the editors discuss various reports published within the issue on topics including the contour regression framework, the single-tree algorithm for exact max-kernel, and the multiple source of transfer learning.

Digital technology and artificial intelligence technology have built an open sharing environment of intellectualization. For start‐ups, which are restricted by their own limited resources, it is wise to take inbound open innovation as a strategy to get external advanced technical information quickly. However, how to match technology resources obtained from outside with the organisation's demand is still a problem for entrepreneurial teams and entrepreneurial researchers. Based on the literature review of existing research and considering entrepreneurial teams' demand to deal with the challenges, this paper firstly analyses the relationship between entrepreneurial teams' inbound open innovation strategy and the innovative use of information technology by individuals in teams of start‐ups and based on the Identity Theory to explore the mechanism of IT identity on the relationship mentioned above. Lastly, the paper further analyses two types of team authorisation (structural empowerment and psychological empowerment) that play different moderating roles in the relationship of inbound open innovation, IT identity and the innovative use of information technology by individuals in teams. Using 238 survey data from entrepreneurial teams with linear regression analysis, we found that IT identity moderates the relationship between inbound open innovation and individual new IT technology exploration positively, and team psychological empowerment has further moderated the relationship between inbound open innovation and the innovative use of information technology by individuals in teams positively, while team structure empowerment plays an inverted U‐shaped moderation. This study has certain guiding significance for entrepreneurial teams to take advantage of digitalised opportunities, and it also has important value for innovation and digitalisation research. [ABSTRACT FROM AUTHOR]

COVID‐19 has emerged as a major research hotspot and trending topic in recent years, leading to increased publications and citations of related papers. While concerns exist about the potential citation boost in journals publishing these papers, the specifics are not fully understood. This study uses a generalized difference‐in‐differences approach to examine the impact of publishing COVID‐19 papers on journal citation metrics in the Health Sciences fields. Findings indicate that journals publishing COVID‐19 papers in 2020 received significantly higher citation premiums due to COVID‐19 in 2020 and continued to benefit from the premium in 2021 in certain fields. In contrast, journals that began publishing COVID‐19 papers in 2021 experienced weaker citation premiums. The citation premiums exhibit some negative spillover effect: Although the publication volume of non‐COVID‐19 papers also surged, these papers experienced insignificant or negative citation gains, even when published in the same journals as COVID‐19 papers. COVID‐19 papers published in high‐impact journals brought higher citation premiums than those in low‐impact journals in most fields, indicating a potential Matthew effect. These citation premiums can affect various citation‐based journal metrics, such as our simulated impact factor and SCImago Journal Rank, to different degrees. Compared to the simulated impact factor, other normalized journal metrics are less influenced by citation premiums. The results highlight a "gold rush" pattern in which early entrants establish their citation advantage in research hotspots and caution against using citation‐based metrics for research assessment. [ABSTRACT FROM AUTHOR]

This paper examines the mediating effect of R&D alliance network dynamics on the relationship between technology convergence and firm innovation quality, it further investigates the moderating effect of degree assortativity in the inventor network. An empirical analysis is conducted based on a panel negative binomial regression model with data of Chinese high‐tech firms listed on the Shanghai and Shenzhen Stock from 2000 to 2018. The results show that novel technology convergence not only contributes to innovation quality directly but also indirectly through ego‐network expansion. The relationship between reinforced technology convergence and innovation quality is inverted U‐shaped, partially mediated by ego‐network stability. In addition, degree assortativity suppresses the effects of novel technology convergence on ego‐network expansion and innovation quality and steepens the inverted U‐shaped relationships of reinforced technology convergence with ego‐network stability and innovation quality. This paper contributes to the relevant literature by revealing the links between technology convergence, ego‐network dynamics, and innovation quality, and emphasizing the importance of inventor collaboration ties formation mechanism in knowledge searching and convergent innovation. Furthermore, the conclusion provides managerial suggestions for high‐tech firms to coordinate internal and external resources to improve technical impacts. [ABSTRACT FROM AUTHOR]

The aim of this paper is to identify the main factors responsible for the 2007–2008 crisis development and transmission across the 10 developed European Union (EU) countries. In order to achieve this objective, trade and financial linkages, crisis contagion from the United States and EU countries and countries' internal and external economic vulnerabilities are examined. The results of logistic regression model covering the period from 2002 to 2012 presented in this paper indicate that the transmission of the crisis occurred through contagion from the United States but also from other EU countries. Additionally, the empirical results confirm that high inflation, a decrease in the exchange rate, and a decrease in the US long‐term interest rates increased the probability of the 2007–2008 financial crisis. [ABSTRACT FROM AUTHOR]

Abstract: This study reviews the empirical literature on banking efficiency by conducting a meta‐regression analysis. The meta‐dataset consists of 1661 observations retrieved from 120 papers published over the period 2000–2014. While the role of study design and method‐specific characteristics of primary studies is evaluated, the focus concerns regulation in banking. The results are fourfold. First, parametric methods always yield lower levels of banking efficiency than non‐parametric studies. Second, banking efficiency is higher in studies using the value‐added approach rather than the intermediation method. Third, efficiency scores also depend on the journal's ranking and on the number of observations and variables used in the primary papers. Finally, regulation matters: primary papers focusing on countries with a liberalized banking industry provide higher values for efficiency scores. [ABSTRACT FROM AUTHOR]

The effects of direct payments on rice income variability in Japan are analysed based on a balanced panel dataset of Japanese rice farms for 2012–2016. Firstly, the contribution of income components to rice income variability and the effects of a direct payment reduction are discussed by applying variance decomposition. Secondly, robust regression techniques are used to measure the correlation between direct payments and rice income variability. The originality of this paper is that it disaggregates the effects of payments using a regression analysis of the effects of direct payments on income variability for Japan. This contrasts with the existing literature on this topic, which has largely focused on European Union countries. This paper discusses to what degree the reduction in direct payments increases income variability. The results reveal that direct payments decrease Japanese rice income variability. Indeed, after controlling for various farm characteristics, we find a negative relationship between the amount of direct payments linked to rice production and rice income variability. Finally, the results suggest that reducing direct payments when the rice price is falling would increase rice income variability. [ABSTRACT FROM AUTHOR]

The linear power flow (LPF) model is widely used in the optimization, operation, and control of distribution networks. These applications require the LPF model to be accurate, fast, and simple in order to simplify calculations as well as to efficiently perform operations and scheduling. In addition, it is difficult to realize the online update of parameters in the existing LPF models. The model retraining brings serious data burden and inefficiency. To serve these applications and comply with requirements, a brand new LPF model is proposed in this paper. A quadratic power flow model is trained by regression learning first, and then the proposed LPF model is derived by Taylor expansion. After only one initial regression learning, the proposed LPF model no longer needs retraining when updated. The refreshed parameter is simply updated online according to the real‐time measurement data, which improves the generalization ability. In conclusion, the proposed LPF model is accurate, generalizable, and greatly minimizes the data consumption and running time. Performance analysis verifies these superiorities. [ABSTRACT FROM AUTHOR]

Systematic reviews and maps are considered a reliable form of research evidence, but often neglect non-English-language literature, which can be a source of important evidence. To understand the barriers that might limit authors' ability or intent to find and include non-English-language literature, we assessed factors that may predict the inclusion of non-English-language literature in ecological systematic reviews and maps, as well as the review authors' perspectives. We assessed systematic reviews and maps published in Environmental Evidence (n = 72). We also surveyed authors from each paper (n = 32 responses), gathering information on the barriers to the inclusion of non-English language literature. 44% of the reviewed papers (32/72) excluded non-English literature from their searches and inclusions. Commonly cited reasons included constraints related to resources and time. Regression analysis revealed that reviews with larger author teams, authors from diverse countries, especially those with non-English primary languages, and teams with multilingual capabilities searched in a significantly greater number of non-English languages. Our survey exposed limited language diversity within the review teams and inadequate funding as the principal barriers to incorporating non-English language literature. To improve language inclusion and reduce bias in systematic reviews and maps, our study suggests increasing language diversity within review teams. Combining machine translation with language skills can alleviate the financial and resource burdens of translation. Funding applications could also include translation costs. Additionally, establishing language exchange systems would enable access to information in more languages. Further studies investigating language inclusion in other journals would strengthen these conclusions. [ABSTRACT FROM AUTHOR]

Objectives: This paper aims to comprehensively analyze trends in gynecological cancers among elderly women in the United States from 1975 to 2020. Methods: Surveillance, Epidemiology, and End Results (SEER) population data were utilized for the analysis. Annual Percentage Change (APC) and Average APC were estimated using join‐point regression to assess trends in mortality rates. Results: The study reveals an increasing pattern of incidence and mortality in all gynaecological cancer sites except cervical cancer among elderly. The incidence of cervical cancer decreased from 1975 to 2007 and then increased, whereas cancer‐specific mortality decreased from 1977 to 2020, indicating positive advancements in detection and treatment. Conclusions: Despite progress in managing certain gynecological cancers, challenges persist, particularly evidenced by increasing mortality rates for cancers in other female genital organs. This underscores the necessity for sustained research efforts and targeted interventions to address these ongoing challenges effectively. [ABSTRACT FROM AUTHOR]

Considering the behavior anomaly under both rising and falling market conditions, this paper aims to address whether the investor trading behavior is sensitive to a different quantile of stock return dispersions by using quantile regression model. Results show that investor trading behavior has significant impacts on different quantiles of stock return dispersions, and reveal the smile slope of investor trading behavior effect which is stronger at the extreme quantile distributions than the median distribution. Moreover, results evidence that the investor trading behavior effect with optimistic investor sentiment should be stronger than the investor trading behavior effect with pessimistic investor sentiment. Finally, this paper sheds light on the anchoring effect of investor trading behavior, and demonstrates that the anchor of investor trading behavior has a positive and significant impact on stock returns. These patterns hold when accounting for stock specific characteristics, various factors and market conditions. [ABSTRACT FROM AUTHOR]

Background: When parents bring their child to appointments and then adhere to agreed speech and language therapy (SLT) recommendations, there is the potential to increase the intensity of the intervention, support generalization and improve outcomes. In SLT, however, little is known about factors that may promote attendance or adherence. Studies in other clinical areas such in medicine, psychology and physiotherapy have identified risk factors for non‐attendance or non‐adherence that are multifactorial and variable dependent on, for example, population and intervention. Aims: To identify rates of non‐attendance and non‐adherence, and to identify parent or child factors associated with parent involvement in intervention for children under 5 years of age receiving SLT. Methods: Parents completed questionnaires at two time points assessing the domains of parents' beliefs (problem perceptions, self‐efficacy), personal circumstances (socio‐demographics, family functioning), treatment experience and child factors. Predictors of parent attendance and adherence were identified through multiple regression analyses. Non‐attendance rates were identified via local health records and non‐adherence ascertained using a specific parent‐reported measure within the treatment experience domain. Results: Participants (N = 199) were predominantly mothers, and were ethnically and socio‐economically diverse, speaking a wide range of languages. Their children presented with a range of speech, language communication needs (SLCN). The rate of non‐attendance was 25% and the main predictors of non‐attendance were maternal age, education level and two factors within the parent beliefs domain. This model explained 40% of the variance in attendance. The rate of non‐adherence in this cohort was 26% with parental rating of the importance of a recommendation and self‐efficacy beliefs predicting adherence; this explained 56% of the variance in adherence to SLT recommendations at home. Conclusions & Implications: Our research has provided preliminary evidence of the influence of parents' beliefs, personal circumstances and treatment experiences on their involvement in their child's therapy. Speech and language therapists should consider factors impacting attendance and adherence to treatment and explore parental perceptions of their child's SLCN before embarking on an intervention, a foundation for collaborative practice. A possible limitation of this study is that the levels of attrition in our sample led to generally high measured rates of participation, which should be considered in future studies. Future research should explore adherence in treatments with varying doses, with different types of SLCN or interventions and in different settings. WHAT THIS PAPER ADDS: What is already known on the subject: It is acknowledged that parent involvement in their child's therapy, such as attending and adhering to recommendations, is important but little is known about the rates of involvement and what factors may be associated with attendance and adherence in SLT. Qualitative research has explored parental involvement suggesting that beliefs about an intervention may be pertinent. Extensive research in other clinical areas suggest multiple and varied factors are influential and further exploration of particular populations and interventions is necessary. What this paper adds to the existing knowledge: This study identified rates of parental non‐attendance and non‐adherence in a cohort of predominantly mothers of children under the age of 5 years. It is the first study to measure parent adherence in SLT and identify factors that are associated parental adherence to SLT recommendations. It adds to the small body of SLT specific research in understanding risk factors for non‐attendance. What are the potential or actual clinical implications of this work?: This study highlights the need for a speech and language therapist to consider and explore parents' perspectives of their child's SLCN as a part of achieving collaboration with a parent in order to achieve the best outcomes. It provides a foundation for further systematic research into parent involvement with the ultimate aim of enhancing outcomes for children with SLCN. [ABSTRACT FROM AUTHOR]

Objectives: For older employees, a mismatch between work and nonwork roles can lead to work–family conflict (WFC) and stress. This paper examines whether the availability of social support from outside the workplace can assist these employees in coping with the stress‐related consequences of WFC. Methods: This study used data from Waves 16 (Time 1) and 17 (Time 2) of the Household, Income and Labour Dynamics in Australia (HILDA) survey (N = 2867). Sociodemographic characteristics were measured using age, sex and employment tenure. A moderated regression model was applied to the older employees in this sample using stress, WFC with external social support as the moderator. Analysis was additionally undertaken for the different aged employee cohorts, younger than 30 years and middle‐aged (30–50). Results: We found that external social support dampened the effect of WFC on employee stress for older employees. This effect was more powerful for older employees than for younger employees. Interestingly, older employees reported the same levels of external social support as employees between 30 and 50, but less than that of employees younger than 30 years. Conclusions: Following our hypothesised relationships based on conservation of resources (COR), selection, optimisation with compensation (SOC) and socio‐emotional selectivity theories (SST), this paper demonstrates that older employees benefit significantly from external social support. As external social support increased among older employees, the negative effect of WFC on stress decreased. However, this effect was only significant for employees up to the 68th percentile. Overall, this effect was less powerful for both groups of younger employees. Consistent with SOC and SST, older employees possessed different social motives (less reported external social support). Employer and government strategies assisting employees to develop social networks outside the workplace may provide significant benefits to organisations in addition to employees. [ABSTRACT FROM AUTHOR]