Regularised Weights in Statistical Models

For flexible and overparameterised models like neural networks, overfitting can be a notorious problem that makes it hard to give accurate predictions in real-life usage. Overfitting is in particular likely in the presence of errors in the training data, such as misclassifications or outliers. Therefore it is essential to either carefully inspect the data or, more realistically, adapt the training algorithm to reduce variance and overfitting. To reduce the risk of overfitting, a common approach is to manipulate the loss function. Either by adding a penalty on the model\u27s flexibility, which reduces variance with a cost of an increased bias, or weight the loss contribution from different data points in order to reduce the influence of harmful data. This thesis introduces a self-maintained method to reweigh different components (observations and/or parameter regularisation) in the loss function during training. With some care with the choice of model, these weights can be solved for, leading in the end to only a modification in the loss function. Due to this, the resulting method can easily be combined with other regularisation techniques. Using the weighting technique on observations in a setting with mislabeled data produces more robust training than an unweighted model and detects mislabeled examples in data. When used on the regularisation penalty, the weights reduces bias introduces by the regularisation term while keeping some crucial attributes from the original penalty

Applied Problems and Use of Technology in Basic Courses in Probability and Statistics : A Way to Enhance Understanding and Increase Motivation

Several authors have reported problems on service courses in basic probability and statistics: students may lack motivation, find the theory difficult or boring, others see no applications for the results. To remedy these problems we have developed a learning environment where two important components are applied problems and use of technology. However, the mere existence of applied problems and technology in the course does not automatically implyincreased motivation or enhanced learning. Technology is helpful for the students if it is used to achieve learning goals, is integrated with the needs of the students and is aligned with the rest of the course. Real-life data and problems evoke interest if the students perceive they benefit from the task. We give two examples, one where active work with applied exercises and projects give a more positive attitude towards the subject, the other example shows that aligned web-based test and exercises increase the result on the final exam and also indicate a better conceptual understanding

On the Robustness of Statistical Models: Entropy-based Regularisation and Sensitivity of Boolean Deep Neural Networks

Models like deep neural networks are known to be sensitive towards many different aspects of noise. Unfortunately, due to the black-box nature of these models, it is in general not known why this is the case. Here, we analyse and attack these problems from three different perspectives. The first one (Paper I) is when noise is present in training labels. Here we introduce a regularisation scheme that accurately identifies wrongly annotated labels and sometimes trains the model as if the noise were not present. The second perspective (Paper II) studies the effect of regularisation in order to reduce variance in the estimation. Due to the bias-variance trade-off, it is a hard task to find the appropriate regularisation penalty and strength. Here we introduce a methodology to reduce bias from a general regularisation penalty to make the estimation closer to the true value. In the final perspective (Paper III), we study the sensitivity that deep neural networks tend to have with respect to noise in their inputs, in particular, how these behaviours depend on the model architecture. These behaviours are studied within the framework of noise sensitivity and noise stability of Boolean functions

Misleading Advertising for Antidepressants in Sweden: A Failure of Pharmaceutical Industry Self-Regulation

BACKGROUND: The alleged efficacy of pharmaceutical industry self-regulation has been used to repudiate increased government oversight over promotional activity. European politicians and industry have cited Sweden as an excellent example of self-regulation based on an ethical code. This paper considers antidepressant advertising in Sweden to uncover the strengths and weaknesses of self-regulation. METHODOLOGY: We analyzed all antidepressant advertisements in the Swedish Medical Journal, 1994-2003. The regulation of these advertisements was analyzed using case reports from self-regulatory bodies. The authors independently reviewed this material to investigate: (1) extent of violative advertising; (2) pattern of code breaches; (3) rate at which the system reacted to violative advertising; (4) prevalence of and oversight over claims regarding antidepressant efficacy and disease causality, and (5) costs for manufactures associated with violative advertising. PRINCIPAL FINDINGS: Self-regulatory bodies identified numerous code breaches. Nonetheless, they failed to protect doctors from unreliable information on antidepressants, since as many as 247 of 722 (34%) advertisements breached the industry code. Self-regulatory bodies repeatedly failed to challenge inflated claims of antidepressant efficacy, lending evidence of lax oversight. On average, 15 weeks elapsed between printing and censure of a wrongful claim, and in 25% of cases 47 weeks or more elapsed. Industry paid roughly €108000 in fines for violative advertising, adding an estimated additional average cost of 11% to each purchased violative advertisement, or amounting to as little as 0.009% of total antidepressant sales of around €1.2 billion. CONCLUSIONS: Lax oversight, combined with lags in the system and low fines for violations, may explain the Swedish system's failure to pressure companies into providing reliable antidepressants information. If these shortcomings prove to be consistent across self-regulatory settings, and if appropriate measures are not taken to amend shortcomings, many countries may want to reconsider the current balance between self-regulation, and legislative control with government oversight

STRENGTHENING COOPERATION WITH THIRD COUNTRIES IN THE FIELD OF HIGHER EDUCATION. 14388/01 (Presse 437-G), 29 November 2001

BACKGROUND: In many European countries, medicines promotion is governed by voluntary codes of practice administered by the pharmaceutical industry under its own system of self-regulation. Involvement of industry organizations in policing promotion has been proposed to deter illicit conduct, but few detailed studies on self-regulation have been carried out to date. The objective of this study was to examine the evidence for promotion and self-regulation in the UK and Sweden, two countries frequently cited as examples of effective self-regulation. METHODS AND FINDINGS: We performed a qualitative content analysis of documents outlining the constitutions and procedures of these two systems. We also gathered data from self-regulatory bodies on complaints, complainants, and rulings for the period 2004-2012. The qualitative analysis revealed similarities and differences between the countries. For example, self-regulatory bodies in both countries are required to actively monitor promotional items and impose sanctions on violating companies, but the range of sanctions is greater in the UK where companies may, for instance, be audited or publicly reprimanded. In total, Swedish and UK bodies ruled that 536 and 597 cases, respectively, were in breach, equating to an average of more than one case/week for each country. In Sweden, 430 (47%) complaints resulted from active monitoring, compared with only two complaints (0.2%) in the UK. In both countries, a majority of violations concerned misleading promotion. Charges incurred on companies averaged €447,000 and €765,000 per year in Sweden and the UK, respectively, equivalent to about 0.014% and 0.0051% of annual sales revenues, respectively. One hundred cases in the UK (17% of total cases in breach) and 101 (19%) in Sweden were highlighted as particularly serious. A total of 46 companies were ruled in breach of code for a serious offence at least once in the two countries combined (n = 36 in the UK; n = 27 in Sweden); seven companies were in serious violation more than ten times each. A qualitative content analysis of serious violations pertaining to diabetes drugs (UK, n = 15; Sweden, n = 6; 10% of serious violations) and urologics (UK, n = 6; Sweden, n = 13; 9%) revealed various types of violations: misleading claims (n = 23; 58%); failure to comply with undertakings (n = 9; 23%); pre-licensing (n = 7; 18%) or off-label promotion (n = 2; 5%); and promotion of prescription drugs to the public (n = 6; 15%). Violations that go undetected or unpunished by self-regulatory bodies are the main limitation of this study, since they are likely to lead to an underestimate of industry misconduct. CONCLUSIONS: The prevalence and severity of breaches testifies to a discrepancy between the ethical standard codified in industry Codes of Conduct and the actual conduct of the industry. We discuss regulatory reforms that may improve the quality of medicines information, such as pre-vetting and intensified active monitoring of promotion, along with larger fines, and giving greater publicity to rulings. But despite the importance of improving regulatory arrangements in an attempt to ensure unbiased medicines information, such efforts alone are insufficient because simply improving oversight and increasing penalties fail to address additional layers of industry bias

Record of a panel discussion on ”Euthanasia”

The basic for the discussion was the Report of the AVMA Panel on Euthanasia (Ref. 1) and the introduction given by Dr Krister Iwarsson, Huddinge, Sweden. During this introduction, reference was also given to a monograph on “animal anaesthesia” by Colin J. Green (Ref. 2) in which euthanasia is defined as “the killing of an animal with a minimum of physical and mental suffering”

On Young People’s Experience of Systems in Technology

Immersed in a technologically complex world, young people make sense of a multi-faceted set of events in everyday life. This article investigates the variation in how Swedish young people experience technological systems and is based on interviews focusing three systems concerning transport, energy and communication – contextualised in relation to bananas, electricity, and mobile phones. A phenomenographic analysis results in five qualitatively distinct categories, describing different ways of understanding technological systems: Using single components, Using the system output, Influencing the system, Interacting with the system, and Integrating thesystem. The results support that different ways of understanding technological systems implies different ways of understanding the complex nature of technology. The results also point to possible ways of developing teaching for technological citizenship

Statistical methods for twin and sibling designs

Twin and sibling studies are valuable in that they allow adjustment for potential confounding factors that are impossible or hard to measure. By measuring associations ‘within-cluster’ it is possible to adjust for many factors that are shared between individuals in the same cluster. Using Swedish national registers, it is possible to obtain information about a large number of potential confounders. While this gives medical researchers great opportunities to control for confounding, it also increases the risk of model misspecification leading to biased estimates. One strategy to reduce the risk of such bias is to use doubly robust(DR) estimation. In DR estimation two working models are combined in such a way that the resulting estimate will remain asymptotically unbiased when one of the models is misspecified. In study I, we implement existing DR estimators for parameters in linear, log-linear and logistic regression models in the R package drgee. In study II, we propose a new class of DR estimators for ‘within-cluster’ association measures in linear and log-linear regression models. In study III we propose a DR estimator for the ‘within-cluster’ log odds ratio parameter in logistic regression models. The estimators proposed in studies II and III are also implemented in the R package drgee. In study IV, we discuss what shared factors the ‘within-cluster’ association actually is adjusted for. Using the formal theory of causal diagrams we demonstrate that the standard methods for estimating ‘within-cluster’ association parameters implicitly adjust for shared confounders, shared mediators, but not shared colliders. Therefore, the estimated parameter may have a causal interpretation as a direct effect, i.e. as the part of the causal effect that is not mediated through shared factors

Associations between individual antipsychotics and the risk of arrests and convictions of violent and other crime : a nationwide within-individual study of 74925 persons

Background Individuals diagnosed with psychiatric disorders who are prescribed antipsycho-tics have lower rates of violence and crime but the differential effects of specific antipsychotics are not known. We investigated associations between 10 specific antipsychotic medications and subsequent risks for a range of criminal outcomes. Method We identified 74 925 individuals who were ever prescribed antipsychotics between 2006 and 2013 using nationwide Swedish registries. We tested for five specific first-generation antipsychotics (levomepromazine, perphenazine, haloperidol, flupentixol, and zuclo-penthixol) and five second-generation antipsychotics (clozapine, olanzapine, quetiapine, ris-peridone, and aripiprazole). The outcomes included violent, drug-related, and any criminal arrests and convictions. We conducted within-individual analyses using fixed-effects Poisson regression models that compared rates of outcomes between periods when each individual was either on or off medication to account for time-stable unmeasured confounders. All models were adjusted for age and concurrent mood stabilizer medications. Results The relative risks of all crime outcomes were substantially reduced [range of adjusted rate ratios (aRRs): 0.50-0.67] during periods when the patients were prescribed antipsychotics v. periods when they were not. We found that clozapine (aRRs: 0.28-0.44), olanzapine (aRRs: 0.46-0.72), and risperidone (aRRs: 0.53-0.64) were associated with lower arrest and conviction risks than other antipsychotics, including quetiapine (aRRs: 0.68-0.84) and haloperidol (aRRs: 0.67-0.77). Long-acting injectables as a combined medication class were associated with lower risks of the outcomes but only risperidone was associated with lower risks of all six outcomes (aRRs: 0.33-0.69). Conclusions There is heterogeneity in the associations between specific antipsychotics and subsequent arrests and convictions for any drug-related and violent crimes.Peer reviewe

Barns perspektiv i forskning om barns psykiska hälsa – förhållningssätt och utmaningar

I den här artikeln diskuteras barns perspektiv som utmaning och förhållningssätt i forskning om psykisk hälsa och ohälsa hos barn och unga. Utgångspunkten tas i frågan hur barns perspektiv i forskning skiljer sig från barns perspektiv såsom det definieras i politiska sammanhang. Mot bakgrund av de reflekterande kritiska synpunkter som mejslats fram av barn och barndomsforskare idag framträder en viktig skillnad. Den bygger på att forskare synliggör sina teoretiska och metodologiska utgångspunkter när resultat som omfattar barns perspektiv presenteras. Det blir en särskild utmaning när allt fler forskare från ämnen också utanför barn och barndomsforskning börjar utgå ifrån barns perspektiv. Ytterligare en utmaning knyter an till forskningsområdet barns psykiska hälsa och ohälsa. Med stöd av Ian Hackings teoretiska resonemang om ”the looping effects” (Hacking 1995, 1999) diskuteras ett sätt varpå barns perspektiv kan bidra till en breddning av forskning om psykisk hälsa och ohälsa