Nonparametric Covariate Adjustment for Receiver Operating Characteristic Curves

The accuracy of a diagnostic test is typically characterised using the receiver operating characteristic (ROC) curve. Summarising indexes such as the area under the ROC curve (AUC) are used to compare different tests as well as to measure the difference between two populations. Often additional information is available on some of the covariates which are known to influence the accuracy of such measures. We propose nonparametric methods for covariate adjustment of the AUC. Models with normal errors and non-normal errors are discussed and analysed separately. Nonparametric regression is used for estimating mean and variance functions in both scenarios. In the general noise case we propose a covariate-adjusted Mann-Whitney estimator for AUC estimation which effectively uses available data to construct working samples at any covariate value of interest and is computationally efficient for implementation. This provides a generalisation of the Mann-Whitney approach for comparing two populations by taking covariate effects into account. We derive asymptotic properties for the AUC estimators in both settings, including asymptotic normality, optimal strong uniform convergence rates and MSE consistency. The usefulness of the proposed methods is demonstrated through simulated and real data examples

How Much is the Whole Really More than the Sum of its Parts? 1 + 1 = 2.5: Superlinear Productivity in Collective Group Actions

In a variety of open source software projects, we document a superlinear growth of production ($R \sim c^\beta$) as a function of the number of active developers $c$, with $\beta \simeq 4/3$ with large dispersions. For a typical project in this class, doubling of the group size multiplies typically the output by a factor $2^\beta=2.5$, explaining the title. This superlinear law is found to hold for group sizes ranging from 5 to a few hundred developers. We propose two classes of mechanisms, {\it interaction-based} and {\it large deviation}, along with a cascade model of productive activity, which unifies them. In this common framework, superlinear productivity requires that the involved social groups function at or close to criticality, in the sense of a subtle balance between order and disorder. We report the first empirical test of the renormalization of the exponent of the distribution of the sizes of first generation events into the renormalized exponent of the distribution of clusters resulting from the cascade of triggering over all generation in a critical branching process in the non-meanfield regime. Finally, we document a size effect in the strength and variability of the superlinear effect, with smaller groups exhibiting widely distributed superlinear exponents, some of them characterizing highly productive teams. In contrast, large groups tend to have a smaller superlinearity and less variability.Comment: 29 pages, 8 figure

Blurred Lines: Between Formal and Substantive Transparency in Consumer Credit Contracts

This is the author accepted manuscript. The final version is available from Kluwer Law InternationalDirective 2008/48/EC aims to guarantee a high level of consumer protection and comparability of consumer credit offers, protecting consumers against over-indebtedness. In light of the ongoing review of this directive, it is important to consider whether the principle of transparency could not play a bigger role in ensuring that consumers are provided with understandable consumer credit information. The authors argue, therefore, that the assessment of the credit information’s transparency should go beyond a mere compliance check with formal aspects of transparency, i.e. whether consumers had access to the information and whether it was legible. At least an equal amount of consideration should be paid to aspects of the substantive transparency, i.e. whether consumers ultimately understood the information. Moreover, the European Commission should strengthen the consumer credit transparency toolbox by explaining the meaning and significance of various transparency requirements, and re-check the effectiveness of the standardised credit information.NWO - Netherlands Organisation for Scientific Researc

An Exploratory Study of the Impact of Formatting on Email Effectiveness and Recall

Although literally trillions of emails are sent annually, little empirical research exists about how formatting of emails impacts email effectiveness. Abundant research exists about the use of subject lines, yet little research addresses the formatting of email content. Many experts from the business communication field have offered advice on effective formatting. We conducted an experiment that controlled for formatting of email messages. The first email message was a job announcement. The second email message contained identical content yet employed what are considered best practices for formatting. We found that university students who viewed the formatted message were significantly more likely to perceive the advertised job as attractive. Furthermore, they were significantly more likely to correctly recall facts about the job. This lends credibility to existing advice from the business communication field about effective formatting. It also serves as a foundation for additional and more nuanced research about an issue that nearly all professionals face on a daily basis

The argumentational texture of transaction cost economics

Transaction Costs;Deconstruction Method;economic theory

A research review of quality assessment for software

Measures were recommended to assess the quality of software submitted to the AdaNet program. The quality factors that are important to software reuse are explored and methods of evaluating those factors are discussed. Quality factors important to software reuse are: correctness, reliability, verifiability, understandability, modifiability, and certifiability. Certifiability is included because the documentation of many factors about a software component such as its efficiency, portability, and development history, constitute a class for factors important to some users, not important at all to other, and impossible for AdaNet to distinguish between a priori. The quality factors may be assessed in different ways. There are a few quantitative measures which have been shown to indicate software quality. However, it is believed that there exists many factors that indicate quality and have not been empirically validated due to their subjective nature. These subjective factors are characterized by the way in which they support the software engineering principles of abstraction, information hiding, modularity, localization, confirmability, uniformity, and completeness

A polychotomous accountability index for integrated reporting by South African listed companies

Abstracts in English, Southern Sotho and SwahiliThe broad aim of this explanatory sequential mixed-methods study was to extend the extant literature by developing a weighted polychotomous accountability index (PAI) that, in turn, was used to measure and evaluate the extent and quality of integrated annual reports (IARs) prepared by the Johannesburg Stock Exchange (JSE) listed companies for the period 2013 to 2016. The study was motivated by a paucity of research on whether corporate accountability, through corporate reporting, has improved (extent and quality) under integrated reporting () through improved integrated reporting quality (IRQ) scores. The study was conducted in two phases. The first phase was for developing the PAI through the Delphi Inquiry method. In the same phase, through qualitative and quantitative content analysis, the PAI was used to measure and evaluate the extent and quality of IARs for the JSE Top 100 companies over the four-year period (2013–2016). The second phase, in the form of semi-structured interviews, aimed at investigating the factors that contributed to the change in IRQ scores over that period. Eight respondents (preparers of IARs), representing five companies, were interviewed. Through the Delphi Inquiry method, the PAI was developed (major contribution of the study), which has eight categories, 44 constructs, a total possible score of 152 and a total weight of 100%. Furthermore, the PAI has a six-point ordinal scoring system from 0 to 5. For the IRQ scores, mean annual IRQ scores were computed as 52.45% for 2013, 58.48% for 2014, 64.72% for 2015 and 68.29% for 2016. As for the JSE sectors, the highest IRQ scores were 66.45%, 71.05%, 75% and 81.25% for 2013, 2014, 2015 and 2016 respectively. From an industry perspective, the results showed highest IRQ scores of 66.45%, 72.37%, 70.72% and 62.42% for 2013, 2014, 2015 and 2016 respectively. The steady increase in the mean IRQ scores for 2013, 2014, 2015 and 2016 shows that there is significant improvement in the extent and quality of IARs produced by the JSE listed companies. This improvement in the IRQs is due to different reasons, which include: preparers taking seriously, teamwork, benchmarking, training, experience, addressing stakeholder needs and understanding the principles before implementing . Moreover, some companies fail to produce quality IARs due to a number of factors that include: an inadequate understanding of by some preparers of IARs; some entities not seeing value in preparing quality IARs hence they present poor quality IARs; partial buy-in, especially by the executive management; a paucity of skills and resources; outsourcing that was identified as bringing with it poor quality work and some entities preferring to chase prestigious awards at the expense of the company’s actual philosophy, hampering the quality of IARs in the process. Different conclusions were reached. It was noted that some concepts and principles should be more synchronised so that they are not in conflict with each other. Rules should be introduced so that may be a blend of principles and rules as this could minimise preparer judgement. The International Integrated Reporting Council (IIRC) must align its terminology with that of other guideline bodies, such as rating agencies, to give more meaning to . The IIRC needs to improve in order to suit companies in the service industry. Integrated reporting has to be more compatible with the digital world and not necessarily paper based. More research must be done about what users need to see in IARs to enhance the relevance of the IAR to different stakeholders. Furthermore, the IIRC must proactively educate decision-makers for an improved buy-in of . Pertaining to transformation, de facto and de jure transformation remain merely theoretical without substantial changes on the ground. Government and the JSE should consider the nature of current disincentives since these seem not to sufficiently challenge the current status quo. Finally, more training on capitals and business models should be conducted in order to improve the quality of reporting since these two constructs are perceived to be complex and hence difficult to implement, especially through quantification.Maikaelelo a a anameng a thutopatlisiso eno e e tlhalosang ya mekgwa e e tswakantsweng ya tatelano e ne e le go atolosa dikwalo tse di gona ka go dira tshupane ya maikarabelo ya polychotomous (PAI) e morago e neng ya dirisediwa go lekanyetsa le go sekaseka bogolo le boleng jwa dipegelo tsa ngwaga le ngwaga tse di golaganeng (diIAR) tse di rulaganngwang ke ditlamo tse di kwadisitsweng kwa Johannesburg Stock Exchange (JSE) mo pakeng ya 2013 go fitlha 2016. Thutopatlisiso e rotloeditswe ke tlhaelo ya dipatlisiso tse di malebana le gore a maikarabelo a ditlamo, ka dipegelo tsa ditlamo, a tokafetse (bogolo le boleng) ka fa tlase ga dipegelo tse di golaganeng () ka maduo a a tokafatseng a boleng jwa dipegelo tse di golaganeng (IRQ). Thutopatlisiso e dirilwe ka magato a le mabedi. Legato la ntlha e ne e le la go dira PAI ka mokgwa wa Delphi Inquiry. Mo legatong leo, ka tshekatsheko ya diteng go dirisiwa mokgwa o o lebelelang dipalopalo le o o lebelelang mabaka, go dirisitswe PAI go lekanyetsa le go sekaseka bogolo le boleng wa diIAR tsa ditlamo tse di kwa Godimo tse 100 tsa JSE mo pakeng ya dingwaga tse nne (2013–2016). Legato la bobedi, le le neng le le mo sebopegong sa dipotsolotso tse di batlileng di rulagana, le ne le ikaeletse go batlisisa dintlha tse di tshwaetseng mo diphetogong tsa maduo a IRQ mo pakeng eo. Go botsoloditswe batsibogi ba le robedi (barulaganyi ba diIAR), ba ba emetseng ditlamo di le tlhano. Ka mokgwa wa Delphi Inquiry, go tlhamilwe PAI (tshwaelo e kgolo ya thutopatlisiso), e e nang le dikarolo tse robedi, ka megopolo e le 44, maduo otlhe a a kgonagalang a 152 le boima jotlhe jwa 100%. Mo godimo ga moo, PAI e na le thulaganyo ya maduo ya dintlha tse thataro go tswa go 0 go ya go 5. Malebana le maduo a IRQ, palogare ya maduo a ngwaga le ngwaga a IRQ, e tlhakanyeditswe go nna 52.45% ka 2013, 58.48% ka 2014, 64.72% ka 2015 le 68.29% ka 2016. Malebana le maphata a JSE gona, maduo a a kwa godimodimo a IRQ e ne e le 66.45%, 71.05%, 75% le 81.25% ka 2013, 2014, 2015 le 2016 ka tatelano eo. Go ya ka indaseteri, dipoelo di bontshitse maduo a a kwa godimodimo a IRQ a 66.45%, 72.37%, 70.72% le 62.42% ka 2013, 2014, 2015 le 2016 ka tatelano eo. Koketsego ka iketlo ya palogare ya maduo a IRQ a 2013, 2014, 2015 le 2016 e bontsha gore go na le tokafalo e e bonalang mo bogolong le boleng jwa diIAR tse di tlhagisiwang ke ditlamo tse di kwadisitsweng mo JSE. Tokafalo eno ya diIRQ ke ka ntlha ya mabaka a a farologaneng, a a akaretsang: barulaganyi ba tsotelela thata, tirisanommogo ya setlhopha, go itshwantsha le ba bangwe, katiso, maitemogelo, go samagana le ditlhokego tsa baamegi le go tlhaloganya dintlhatheo pele ga go diragatsa . Mo godimo ga moo, ditlamo dingwe di palelwa ke go tlhagisa diIAR tsa boleng ka ntlha ya dintlha di le mmalwa tse di akaretsang: go tlhaloganya go go sa lekanang ga ke barulaganyi bangwe ba diIAR; ditheo dingwe di sa bone boleng jwa go baakanya diIAR tsa boleng mme seo se dira gore di tlhagise diIAR tsa boleng jo bo kwa tlase; tshegetso e e sa lekanang, bogolo segolo ya botsamaisikhuduthamaga; tlhaelo ya bokgoni le ditlamelo; theko ya ditirelo kwa ntle, e leng se se supilweng se tla ka boleng jo bo kwa tlase jwa tiro le ditheo dingwe di tlhopha go lelekisa dikgele tsa mabono mme di ikgatholosa filosofi ya nnete ya ya setlamo, mme ka go rialo di ama boleng jwa diIAR. Go fitlheletswe diphitlhelelo tse di farologaneng. Go lemogilwe gore megopolo mengwe le dintlhatheo tsa di tshwanetse go rulaganngwa ka tsamaisano gore di se ke tsa ganetsana. Go tshwanetse ga itsisewe melanwana gore e nne motswako wa dintlhatheo le melawana gonne seno se ka fokotsa go atlhola ga barulaganyi. Lekgotla la Boditšhabatšha la Dipegelo tse di Golaganeng (IIRC) le tshwanetse go lepalepanya mareo a lona le a ditheo tse dingwe tse di kaelang, go tshwana le ditheo tse di lekanyetsang, gore e nne le bokao jo bo oketsegileng. Lekgotla la IIRC le tshwanetse go tokafatsa gore e siamele ditlamo tse di mo indasetering ya ditirelo. Dipegelo tse di golaganeng di tshwanetse go tsamaelana le lefatshe la dijitale mme e seng fela gore e nne tse di mo dipampiring. Go tshwanetse ga dirwa dipatlisiso tse dingwe malebana le gore badirisi ba tlhoka go bona eng mo diIAR go tokafatsa bomaleba jwa IAR mo baameging ba ba farologaneng. Go feta foo, lekgotla la IIRC le tshwanetse go ruta batsayaditshwetso gore go nne le tshegetso e e tokafetseng ya . Malebana le diphetogo, diphetogo tse di gona le tsa tshwanelo e sala go nna tiori fela mme go se na diphetogo tse di bonalang. Puso le JSE ba tshwanetse go lebelela dintlha tsa ga jaana tse di kgobang marapo ka ntlha ya fa go sa bonale fa di gwetlha seemo sa ga jaana mo go lekaneng. Kwa bokhutlong, go tshwanetse ga dirwa katiso e nngwe ya letlotlo le dikao tsa kgwebo go tokafatsa boleng jwa go dira dipegelo ka ntlha ya fa megopolo eno e mebedi e lebega e le marara mme ka jalo go se bonolo go e diragatsa, bogolo segolo ka dipalo.Ndivho khulwane ya ṱhalutshedzo iyi ya ngona yo ṱanganelanaho ya thevhekano ho vha u engedza maṅwalwa a zwino nga u bveledza indekisi ya vhuḓifhinduleli yo khethekanywaho (PAI) ine ya dovha ya, shumiswa u kala na u ela vhuphara na ndeme ya mivhigo ya ṅwaha nga ṅwaha yo ṱanganelanaho (dzi IAR) yo lugiswaho nga vha khamphani dzo ṅwaliswaho kha Johannesburg Stock Exchange (JSE) lwa tshifhinga tsha vhukati ha 2013 u swika 2016. Ngudo dzo ṱuṱuwedzwa nga u shaea ha ṱhoḓisiso dza nga ha uri vhuḓifhinduleli, u mona na u vhiga ha tshiofisi ho no khwiṋisea na (vhuphara na ndeme) nga fhasi ha u vhiga ho ṱanganelanaho () nga kha zwikoro zwa ndeme ya u vhiga ho ṱanganelanaho (IRQ). Ngudo dzo itwa fhethu huvhili nga maga mavhili. Ḽiga ḽa u thoma ḽo vha ḽi ḽa u bveledza PAI nga kha ngona dza Ṱhoḓisiso dza Delphi. Kha ḽiga ḽeneḽo, nga kha musaukanyo wa vhungomu wo sedzaho ndeme na tshivhalo, PAI yo shumiswa u kala na u ela vhuphara na ndeme ya dzi IAR kha khamphani dza 100 dza nṱha dza JSE kha tshifhinga tsha miṅwaha miṋa (2013–2016). Ḽiga ḽa vhuvhili nga tshivhumbeo tsha inthaviwu dzo dzudzanywaho zwiṱuku dzi sengulusaho zwivhumbi zwi dzhenelelaho kha tshanduko ya zwikoro zwa IRQ lwa tshifhinga. Vhafhinduli vha malo (vhadzudzanyi vha dzi IAR), vho imelaho khamphani ṱhanu vho vhudziswa. Nga kha Ngona ya Ṱhoḓisiso dza Delphi, ho bveledzwa PAI (zwidzheneleli zwihulwane kha ngudo), dzi re na khethekanyo dza malo, miṱalukanyo ya 44, ṱhanganyelo dza zwikoro zwine zwa nga vha hone zwa 152 na ṱhanganyelo ya tshileme ya 100%. Zwiṅwe hafhu, PAI dzi na sisiṱeme ya zwikoro ya odinaḽa zwa phoindi dza rathi u bva kha 0 u swika kha 5. U itela zwikoro zwa IRO, zwikoro zwa vhukati zwa ṅwaha nga ṅwaha zwo rekanywa zwa vha 52.45% nga 2013, 58.48% nga 2014, 64.72% nga 2015 na 68.29% for 2016. Kha sekithara dza JSE, zwikoro zwa nṱhesa zwa IRQ zwo vha zwi 66.45%, 71.05%, 75% na 81.25% nga 2013, 2014, 2015 na 2016 nga u tevhekana. U ya nga kuvhonele kwa nḓowetshumo, mvelelo dzo sumbedza zwikoro zwa nṱhesa zwa IRQ zwa 66.45%, 72.37%, 70.72% na 62.42% nga 2013, 2014, 2015 na 2016 nga u tevhekana. U gonya zwiṱuku kha zwikoro zwa vhukati zwa IRQ zwa 2013, 2014, 2015 na 2016 zwi sumbedza uri hu na u khwiṋisea hu hulwane kha vhuphara na ndeme ya dzi IAR dzo bveledzwaho vha khamphani dzi re kha JSE. U khwiṋisea uhu ha dzi IRQ ndi nga ṅwambo wa zwiitisi, zwine zwa katela vhadzudzanyi vha dzhielaho nṱha, u shuma sa thimu, u vhambedza, vhugudisi, tshenzhelo, u livhana na ṱhoḓea dza vhadzheneleli na u pfesesa milayo phanḓa ha musi i tshi shumiswa . Nṱhani ha izwo, dziṅwe khamphani dzi a kundelwa u bveledzwa dzi IAR nga ṅwambo zwa zwiitisi zwo vhalaho , zwi katelaho u sa pfesea lwo lingaho ha nga vhaṅwe vhadzudzanyi vha dzi IAR, zwiṅwe zwiimiswa zwi sa vhoni ndeme ya u ita dzi IAR dza ndeme zwa sia vha tshi bvledza dzi IAR dza ndeme i sa takadzi, u zwi ṱanganedza hu si nga mbilu dzoṱhe nga maanḓa vha vhalanguli vhahulwane; u shaea ha zwikili na zwiko; u ṱunḓa tshumelo nnḓa zwine zwo topolwa sa zwi ḓisaho mushumo wa ndeme i sa takadzi na zwiṅwe zwiimiswa zwi tshi funa u gidimisana na pfufho dza maimo hu sa dzhielwi nṱha fiḽosofi ya vhukuma ya dza khamphani, zwine zwa thivhela ndeme ya dzi IAR kha kuitele kwa zwithu. Ho swikelelwa khunyeledzo dzo fhambanaho. Ho vhonala uri miṅwe miṱalukanyo ya na milayo i tea u dzudzanywa u itela uri i sa vhe na khuḓano. Milayo i tea u ḓivhadzwa u itela uri dzi vha ṱhanganyelo ya milayo na maitele saizwi zwi tshi nga fhungudza khaṱhulo dza vhadzudzanyi. Khoro ya Dzitshakatshaka yo Ṱanganelanaho ya u Vhiga (IIRC) i tea u dzudzanya mathemo ayo na ayo a zwiimiswa nyendedzi, zwi nga ho sa mazhendedzi a u fhima, u ṋea ṱhalutshedzo ya khwiṋe kha . Vha IIRC vha tea u khwiṋisa u itela uri dzi elane na nḓowetshumo dza tshumelo. U vhiga ho ṱanganelanaho hu tea u elana vhukuma na ḽifhasi ḽa didzhithala nahone hu sa ḓisendeke nga bammbiri. Hu tea u itwa ṱhoḓisiso nga ha zwine vhashumisi vha vhona kha dzi IAR u khwaṱhisedza u tea ha IAR dza vhashumisani vho fhambanaho. Dziṅwe hafhu, IIRC i tea u funza vhadzhii vha tsheo lwo khwaṱhaho u itela u khwiṋisa u ḓidzhenisa kha . Zwi tshi elana na tshanduko, tshanduko ya de facto na ya de jure i sokou dzula i ya thyori hu si na tshanduko dzi vhonalaho ngeno fhasi. Muvhuso na JSE vha tea dzhiela nṱha lushaka lwa sa vha hone ha zwiṱuṱuwedzi saizwi izwi zwi tshi tou nga zwi ṋekedza khaedu lwo linganaho tshiimo tsha zwithu tsha zwino. Tsha u fhedzisela, vhugudisi kha zwiedza zwa pfuma na bindu vhu tea u itwa u itela u khwiṋisa ndeme ya u vhiga saizwi izwo zwifhaṱo zwivhili zwi tshi vhonala sa zwi konḓaho nahone zwi konḓaho u shumisa, nga maanḓa nga kha u vhekanya ndemeFinancial AccountingD. Phil. (Accounting Sciences

Do Directors Have a Use-By Date? Examining the Impact of Board Tenure on Firm Performance

Corporate boards serve the dual important functions of monitoring and advising management. We examine whether corporate boards consisting of longer-serving independent directors are better able to fulfill these functions due to firm-specific knowledge accumulation, or whether director performance suffers due to declining effectiveness in monitoring managers and/or overall staleness of board capital (board value to shareholders). Using a broad sample of up to 3,800 firms over a 20-year period, our evidence suggests that board tenure is positively related to forward-looking measures of market value and stock returns, with the relationship reversing after about nine years on average. The detrimental effect of longer average board tenure on market value (after an initial period of positive effects) is stronger for high growth firms, which is consistent with the deterioration of the board members’ ability to perform their advisory function