Browsing by Author "Andersson, Eva"

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A monitoring system for detecting starts and declines of influenza epidemics
(2003-12-01) Andersson, Eva
The aim is to detect an influenza outbreak as soon as possible. Data are weekly reports of number of patients showing influenza-like symptoms. At each additional observation we decide whether a change has occurred or not. The methodology of statistical surveillance is used to construct an outbreak detection system. The report also demonstrates measures that reflect timeliness, such as the probability of successful detection within a specified time and the predictive value at different time points. A new non-parametric approach is used. The cycles are estimated using only monotonicity restrictions. Also different approaches regarding the intensity of the change-process are compared. The pros and cons of using an empirical intensity are evaluated. The time to an alarm is investigated, both for false and motivated alarms. When setting the alarm limit, there is a trade-off between the false alarms and the delay of motivated alarms. In the evaluation it must be considered that the performance of the system depends on when the outbreak begins, in relation to the start of the surveillance. If the outbreak begins at the same time as the surveillance is started, then the probability of early detection is 0.04, but if the surveillance is started 12 time points before the outbreak the detection probability is 0.43. The non-parametric approach avoids miss-specifications of the base line. Even a "normal" miss-specification results in serious delay. Another drawback is that alarms at late time points have low predictive value. An empirical prior for the intensity works well when the actual outbreak time agrees with the prior. But when the outbreak occurs "earlier than expected", the alarms are seriously delayed. A non-informative prior, however, works well.
Detection of turning points in business cycles
(University of Gothenburg, 2002-06-01) Andersson, Eva; Bock, David; Frisén, Marianne
Methods for on-line monitoring of business cycles are compared with respect to the ability of early prediction of the next turn by an alarm for a turn in a leading index. Three likelihood based methods for turning point detection are compared in detail by using the theory of statistical surveillance and by simulations. One of the methods is based on a Hidden Markov Model. Another includes a non-parametric estimation procedure. Evaluations are made of several features such as knowledge of shape and parameters of the curve, types and probabilities of transitions and smoothing. Results on the expected delay time to a correct alarm and the predictive value of an alarm are discussed. The three methods are also used to analyze an actual data set of a period of the Swedish industrial production. The relative merits of evaluation of methods by one real data set or by simulations are discussed.
Effect of dependency in systems for multivariate surveillance.
(2007-11-22T11:45:15Z) Andersson, Eva
In many situations we need a system for detecting changes early. Examples are early detection of disease outbreaks, of patients at risk and of financial instability. In influenza outbreaks, for example, we want to detect an increase in the number of cases. Important indicators might be the number of cases of influenza-like illness and pharmacy sales (e.g. aspirin). By continually monitoring these indicators, we can early detect a change in the process of interest. The methodology of statistical surveillance is used. Often, the conclusions about the process(es) of interest is improved if the surveillance is based on several indicators. Here three systems for multivariate surveillance are compared. One system, called LRpar, is based on parallel likelihood ratio methods, since the likelihood ratio has been shown to have several optimality properties. In LRpar, the marginal density of each indicator is monitored and an alarm is called as soon as one of the likelihood ratios exceeds its alarm limit. The LRpar is compared to an optimal alarm system, called LRjoint, which is derived from the full likelihood ratio for the joint density. The performances of LRpar and LRjoint are compared to a system where the Hotellings T2 is monitored. The evaluation is made using the delay of a motivated alarm, as a function of the times of the changes. The effect of dependency is investigated: both dependency between the monitored processes and correlation between the time points when the changes occur. When the first change occurs immediately, the three methods work rather similarly, for independent processes and zero correlation between the change times. But when all processes change later, the T2 has much longer delay than LRjoint and LRpar. This holds both when the processes are independent and when they have a positive covariance. When we assume a positive correlation between the change times, the LRjoint yields a shorter delay than LRpar when the changes actually do occur simultaneously, whereas the opposite is true when the changes do actually occur at different time point.
Elevers datoranvändning i Montessorimiljö
(2012-03-16) Andersson, Eva; University of Gothenburg/Department of education and special education; Göteborgs universitet
Bakgrund: Maria Montessoris vision var att hennes pedagogik inte skulle bli åldrad och förlegad utan att ständigt hållas levande. Med ett växande och varierande samhälle bör IKT användas som ett naturligt arbetssätt i den förberedda miljön på Montessoriskolor inom en snar framtid. Om vi tidigt lär barnen att kritiskt granska och handskas med den nya tekniken och vad den kan användas till. Då behöver de inte växa upp till passiva tonåringar, som sitter timtals framför bildskärmen(Montessoritidningen, 2004) Syfte: Mitt syfte är att undersöka elevers förhållningssätt och deras användning av IKT inom den förberedda miljön i Montessoriskolan och på så sätt få fram en genuin bild av hur moderniteter formar elevers studerande. Metod: Undersökningen gjordes med hjälp av kvalitativa forskningsintervjuer och observationer. Jag har observerat datoranvändningen av två klasser i en årskurs 2-3:a respektive 4-5:a. Mina observationer ligger till grund för urvalet av de intervjuade eleverna. Metoden som användes var öppna intervjuer med fyra elever. Jag har också tagit del av litteratur och forskning i ämnet. Resultat: Resultatet visar att eleverna är mycket positiva till användandet av IKT och de tycker de lär sig mycket kunskapsmässigt. De är eniga att datorer skall finnas i verksamheten som ett naturligt redskap i den förberedda miljön. Utifrån min undersökning, stämde det väl överens med mina resultat. I 2-3:an användes datorn initierat av pedagog, eftersom eleverna i klassen nyttjade endast datorn som komplement utifrån sina specifika läs- och skrivsvårigheter. Betydelse för läraryrket: Att pedagoger skall få en bättre inblick hur IKT används av eleverna, som ett naturligt redskap i verksamheten . Att se pennan som ett viktigt verktyg och som ett komplement till datoranvändning. Att ge eleverna förutsättningar till att skriva en text för hand eller på datorn för att bygga upp elevens självförtroende och självkänsla. I vår läroplan står följande om svenskämnet: Att eleven ska kunna olika strategier för att skriva olika slags typer av texter med anpassning till deras typiska uppbyggnad och språkliga drag. Olika sätt att bearbeta egna texter till innehåll och form. Handstil samt att skriva, disponera och redigera texter för hand och med hjälp av dator. (Lgr-11.2010, s.224)
"En stor stark, tack!" En studie om Alkohollagens tillämpning ur ett rättssociologiskt perspektiv
(2009-08-31T12:44:03Z) Andersson, Eva; Claësson, Ulrika; Göteborg University/Department of Social Work; Göteborgs universitet/Institutionen för socialt arbete
Syfte: Uppsatsens syfte är dels att undersöka hur alkohollagen tillämpas på krogar i centrala Göteborg vad gäller legitimationskontroll vid servering till unga. Ett annat syfte är att studera domsluten för brott mot Alkohollagen vad gäller servering av alkohol till underåriga för att se om lagstiftningens intentioner efterlevs. Utifrån dessa två studier presenteras de diskurser som kan utläsas kring servering av alkohol till unga utifrån rättskällor och andra texter vi analyserat. Metod: Uppsatsen använder sig av olika metoder för de olika studierna, vilket innebär att vi genomfört 100 provköp för att undersöka i vilken utsträckning serveringspersonalen efterfrågar legitimation vid ölförsäljning till unga. Dels en studie av domar för att utläsa hur alkohollagen åberopas i domslut. Vidare analyserades diskurser fram kring servering av alkohol till unga. Uppsatsen undersöker såväl gällande rättsregler som förarbeten och domar. Teori: Uppsatsens resultat analyseras ur ett rättssociologiskt perspektiv. Rättsreglernas utgångspunkt är att skydda unga från en tidig alkoholdebut, samhället skall via exempelvis tillståndsmyndigheter och domstolar tillse att detta syfte uppnås. Normer och värderingar kring unga och alkohol är under förändring varpå rättssociologisk teori kan användas för att besvara frågan om lagens intentioner uppnås genom den tillämpning som råder idag. Resultat: Resultatet visar på att serveringspersonalen begär legitimation i låg utsträckning. De domar vi granskat har återknutit till lagstiftningen och lever upp till gällande rättsregler. Domarna är få och resultaten visar att det inte blir speciellt kännbara påföljder för serveringspersonal som serverar alkohol till unga ens vid de tillfällen då dessa lagförs. Analys: En anledning till att unga i så hög utsträckning serveras utan att de behöver uppvisa legitimation kan bero på att "risken" för att utsättas för tillsyn och att lagföras för dessa brott bedöms som ringa. Att antalet utskänkningstillstånd ökat och därmed konkurrensen mellan krogarna kan innebära att serveringspersonalen måste vara mindre laglydiga för att krogen skall överleva i konkurrensen och då alkoholen utgör en stor inkomstkälla för krogarna.
Evaluation of multivariate surveillance
(2009-05-15T14:20:56Z) Frisén, Marianne; Andersson, Eva; Schiöler, Linus
Multivariate surveillance is of interest in many areas such as industrial production, bioterrorism detection, spatial surveillance, and financial transaction strategies. Some of the suggested approaches to multivariate surveillance have been multivariate counterparts to the univariate Shewhart, EWMA, and CUSUM methods. Our emphasis is on the special challenges of evaluating multivariate surveillance methods. Some new measures are suggested and the properties of several measures are demonstrated by applications to various situations. It is demonstrated that zero-state and steady-state ARL, which are widely used in univariate surveillance, should be used with care in multivariate surveillance.
Hotelling´s T2 Method in Multivariate On-Line Surveillance. On the Delay of an Alarm
(2008-11-28T12:19:37Z) Andersson, Eva
A system for detecting changes in an on-going process is needed in many situations. On-line monitoring (surveillance) is used in early detection of disease outbreaks, of patients at risk and of financial instability. By continually monitoring one or several indicators, we can, early, detect a change in the processes of interest. There are several suggested methods for multivariate surveillance, one of which is the Hotelling’s T2. Since one aim in surveillance is quick detection of a change, it is important to use evaluation measures that reflect the timeliness of an alarm. One suggested measure is the expected delay of an alarm, in relation to the time of change () in the process. Here we investigate a delay measure for the bivariate situation. Generally, the measure depends on both change times (i.e. 1 and 2). We show that, for a bivariate situation using the T2 method, the delay only depends on 1 and 2 through the distance 1-2.
Le français au sein des institutions de l'Union européenne
(2015-02-19) Andersson, Eva; University of Gothenburg/Department of Languages and Literatures; Göteborgs universitet/Institutionen för språk och litteraturer
Ce mémoire a pour but d'analyser de plus près l'influence de l'anglais (langue source) sur le français (langue cible) au sein de la Commission européenne, ou, en d'autres termes, l'interférence linguistique de l'anglais. Le français a longtemps tenu une place privilégiée comme langue de travail et langue de rédaction au sein des institutions de l'Union européenne. Cette situation a cependant radicalement changé au cours de ces dernières années, car les élargissements successifs, surtout les adhésions des pays de l'Europe de l'Est à partir de 2004, ont confirmé la prééminence de l’anglais comme lingua franca des institutions européennes. Aujourd'hui presque tous les textes législatifs de la Commission européenne sont rédigés en anglais pour ensuite être traduits dans toutes les autres langues officielles de l'UE, notamment le français. Il est donc justifié d'examiner de plus près les effets de la traduction sur le français. Bien que le but principal soit d'établir de façon objective au moyen d'une analyse contrastive s'il y a interférence ou non au niveau de quelques aspects choisis (connecteurs, longueur de phrase, abstrait/concret par exemple) j'ai aussi cherché à attirer l'attention sur les effets de l'interférence sur la qualité linguistique. Le corpus est beaucoup trop petit pour que l'on puisse en tirer des conclusions générales. Par conséquent j’ai plutôt cherché à indiquer quels aspects méritent d'être étudiés plus en profondeur.
Likelihood based methods for detection of turning points in business cycles - A comparative study
(University of Gothenburg, 2001-05-01) Andersson, Eva; Bock, David; Frisén, Marianne
Methods for on-line monitoring of business cycles are compared with respect to the ability of early prediction of the next tum by an alarm for a tum in a leading index. Three likelihood-based methods for turning point detection are compared in detail by using the theory of statistical surveillance and by simulations. One of the methods is based on a Hidden Markov Model. Another includes a non-parametric estimation procedure. Evaluations are made of several features such as knowledge of shape and parameters of the curve, types and probabilities of transitions and smoothing. The methods are made comparable by alarm limits, which give the same median time to the first false alarm, but also other approaches for comparability are discussed. Results are given on the expected delay time to a correct alarm, the probability of detection of a turning point within a specified time and the predictive value of an alarm. The three methods are also used to analyze an actual data set of a period of the Swedish industrial production. The relative merits of evaluation of methods by one real data set or by simulations are discussed.
Modeling influenza incidence for the purpose of on-line monitoring
(2007-11-27T12:08:00Z) Andersson, Eva; Bock, David; Frisén, Marianne
We describe and discuss statistical models of Swedish influenza data, with special focus on aspects which are important in on-line monitoring. Earlier suggested statistical models are reviewed and the possibility of using them to describe the variation in influenza-like illness (ILI) and laboratory diagnoses (LDI) is discussed. Exponential functions were found to work better than earlier suggested models for describing the influenza incidence. However, the parameters of the estimated functions varied considerably between years. For monitoring purposes we need models which focus on stable indicators of the change at the outbreak and at the peak. For outbreak detection we focus on ILI data. Instead of a parametric estimate of the baseline (which could be very uncertain,), we suggest a model utilizing the monotonicity property of a rise in the incidence. For ILI data at the outbreak, Poisson distributions can be used as a first approximation. To confirm that the peak has occurred and the decline has started, we focus on LDI data. A Gaussian distribution is a reasonable approximation near the peak. In view of the variability of the shape of the peak, we suggest that a detection system use the monotonicity properties of a peak.
Monotonicity aspects on seasonal adjustment
(University of Gothenburg, 1999-03-01) Andersson, Eva
Monotonicity is an important property in time series analysis. It is often of interest to know if the seasonal adjustment method used has altered the monotonicity or changed the time of turning points in a time series that exhibits cycles. The issue of whether the monotonicity of the trend cycle component of the original non-stationary time series is preserved after the series has been adjusted is treated in this report. The time of a turning point is defined as the time when the cycle changes from recession to expansion (or vice versa). In this report seasonal adjustment with moving average methods is analysed from monotonicity aspects. The time series is assumed to consist of three additive components: a trend cycle part, a seasonal part and a stochastic error part. No parametric model is assumed for the trend cycle. The behaviour of the adjusted series is analysed for two cases: a monotonically increasing trend cycle and a trend cycle with a peak. If the trend cycle is monotonic within the entire observed section the monotonicity is preserved. Unimodality is preserved but not always the time of the turning point.
Monotonicity restrictions used in a system of early warnings applied to monthly economic data
(University of Gothenburg, 1999-04-01) Andersson, Eva
When making political decisions, the ability to make correct predictions about the behaviour of the business cycle in the future is important. The ability to forecast business cycles determines the success of, for example, governmental programmes. By business cycles we generally refer to the fluctuations over time in the total economy. A variety of techniques for predicting the business cycles have been proposed. Some of the proposed techniques aim to predict the values of the business cycle. These techniques often prove to give very bad fits near turning points. Other forecasting methods are designed to predict the time of the turning points in the cycle. Many of the turning point prediction methods are based on discovery of turning points in a leading indicator. A leading indicator represents activity, which lead business cycle turning points, thus having its turning points before the general business cycle. It is often the case that the times of the turning points of the business cycle and a lagged leading index coincide remarkably well, even though the actual values of the two time series do not. In report I a method is proposed that uses the theory of statistical surveillance and monotonicity conditions to decide if a leading indicator, X, has reached a turning point. The proposed alarm function is based on the maximum likelihood ratio. The time series X is modelled as consisting of two components, namely trend cycle and error, where the cycles in the first component are not periodic. Non-parametric regression is used to estimate the trend cycle. The only information used is the fact that the trend cycle is monotonically increasing up to a peak and thereafter monotonically decreasing. A simulation study is made in order to illustrate the proposed method. The median run length to the first false alarm and the expected delay time were considered to be relevant measures of the performance of the proposed method. The results from the simulation study indicate that when there is no turning point, the average time to the first false alarm is five years, whereas when there is a turning point the average time to the alarm is 3 months. A possible complication in the monitoring of a leading indicator X is the fact that the observations on X will be made monthly and thus they are likely to exhibit seasonal variation. The proposed method is not designed to deal with seasonality, and therefore the observations must be adjusted for seasonality, prior to surveillance. This possible complication is considered to be solved in report I, but it is treated in report II. The seasonal variation should be eliminated only in order that the turning points should be identified. Since the proposed method of surveillance uses robust regression under monotonicity restrictions the seasonal adjustment method must not change the monotonicity. Moving average techniques, used for seasonal adjustment, are investigated as to their monotonicity preserving properties. The results from this study indicate that when there is no turning point the moving average estimator does preserve the monotonicity. If there, however, is a turning point the moving average estimator does not preserve the time of the turning point, except for some special cases.
On monotonicity and early warnings with applications in economics
(University of Gothenburg, 1999-01-01) Andersson, Eva
In this report a method for monitoring time series with cycles is presented. It is a nonparametric approach for detecting the turning point of the cycles. Time series of business indicators often exhibit cycles that can not easily be modelled with a parametric function. Forecasting the turning points is important to economic and political decisions. One approach to forecasting the business cycles is to use a leading indicator. The method presented in this report uses statistical surveillance to detect the turning points of a leading indicator. Statistical surveillance is a methodology for detecting a change in the underlying process as soon as possible. Observations on the leading indicator are gathered once a month and the change in the process is a turning point. Only a part of a series that contains one turning point at most will be investigated. The time series is assumed to consist of two additive components: a trend cycle part and a stochastic error part. No parametric model is assumed for the trend cycle, estimation is instead made by robust regression under different monotonicity restrictions. The aim is to detect a turning point as soon as possible, not to predict the value of the time series at the turning point. Evaluation of this surveillance method is done by means of simulation. The number of false alarms and the delay time are analysed. The evaluation shows that if there is no turning point then the median time to the first false alarm is five years, whereas if there is a turning point after three years, the median time to an alarm is 3 months.
On seasonal filters and monotonicity
(University of Gothenburg, 2001-04-01) Andersson, Eva; Bock, David
Seasonal adjustment is important in for example economic time series where the variation can be due to both seasonal and cyclical movements. In a situation where we want to detect a turning point of a cyclical process exhibiting seasonal variation, it is very important that the seasonal adjustment does not adversely affect the ability to detect the turning points. Thus, it is important that the seasonal adjustment does not alter the monotonicity. In this report, seasonal adjustment using differentiation and moving average methods is analyzed with respect to the effect on turning points.
On Turning Point Detection in Cyclical Processes. With applications to the monitoring of business cycles
(2001) Andersson, Eva
Predictions by early indicators of the time and height of yearly influenza outbreaks in Sweden
(2007-12-13T11:28:16Z) Andersson, Eva; Kühlmann-Berenzon, Sharon; Linde, Annika; Schiöler, Linus; Rubinova, Sandra; Frisén, Marianne
Aims: Methods for prediction of the peak of the influenza from early observations are suggested. These predictions can be used for planning purposes. Methods: In this study, new robust methods are described and applied on weekly Swedish data on influenza-like illness (ILI) and weekly laboratory diagnoses of influenza (LDI). Both simple and advanced rules for how to predict the time and height of the peak of LDI are suggested. The predictions are made using covariates calculated from data in early LDI reports. The simple rules are based on the observed LDI values while the advanced ones are based on smoothing by unimodal regression. The suggested predictors were evaluated by cross-validation and by application to the observed seasons. Results: The relation between ILI and LDI was investigated and it was found that the ILI variable is not a good proxy for the LDI variable. The advanced prediction rule regarding the time of the peak of LDI had a median error of 0.9 weeks, and the advanced prediction rule for the height of the peak had a median deviation of 28%. Conclusions: The statistical methods for predictions have practical usefulness.
Semiparametric estimation of outbreak regression
(2008-07-02T10:11:11Z) Frisén, Marianne; Andersson, Eva; Pettersson, Kjell
A regression may be constant for small values of the independent variable (for example time), but then a monotonic increase starts. Such an “outbreak” regression is of interest for example in the study of the outbreak of an epidemic disease. We give the least square estimators for this outbreak regression without assumption of a parametric regression function. It is shown that the least squares estimators are also the maximum likelihood estimators for distributions in the regular exponential family such as the Gaussian or Poisson distribution. The approach is thus semiparametric. The method is applied to Swedish data on influenza, and the properties are demonstrated by a simulation study. The consistency of the estimator is proved.
Semiparametric surveillance of outbreaks
(2008-07-02T10:15:58Z) Frisén, Marianne; Andersson, Eva
The detection of a change from a constant level to a monotonically increasing (or decreasing) regression is of special interest for the detection of outbreaks of, for example, epidemics. A maximum likelihood ratio statistic for the sequential surveillance of an “outbreak” situation is derived. The method is semiparametric in the sense that the regression model is nonparametric while the distribution belongs to the regular exponential family. The method is evaluated with respect to timeliness and predicted value in a simulation study that imitates the influenza outbreaks in Sweden. To illustrate its performance, the method is applied to Swedish influenza data for six years. The advantage of this semiparametric surveillance method, which does not rely on an estimated baseline, is illustrated by a Monte Carlo study. The proposed method is successively accumulating the information. Such accumulation is not made by the commonly used approach where the current observation is compared to a baseline. The advantage of information accumulation is illustrated.
Similarities and differences between statistical surveillance and certain decision rules in finance
(2007-12-13T11:42:37Z) Bock, David; Andersson, Eva; Frisén, Marianne
Financial trading rules have the aim of continuously evaluating available information in order to make timely decisions. This is also the aim of methods for statistical surveillance. Many results are available regarding the properties of surveillance methods. We give a review of financial trading rules and use the theory of statistical surveillance to find properties of some commonly used trading rules. In addition, a nonparametric and robust surveillance method is proposed as a trading rule. Evaluation measures used in statistical surveillance are compared with those used in finance. The Hang Seng Index is used for illustration.
Skolsköterskans arbete med överviktiga elever i ett tidigt skede
(2012-06-21) Andersson, Eva; Andersson, Åsa; University of Gothenburg/Institute of Health and Care Sciences; Göteborgs universitet/Institutionen för vårdvetenskap och hälsa
Introduktion: Övervikt hos barn och ungdomar är ett växande problem. På längre sikt leder övervikt till livsstilssjukdomar och försämrad livskvalité. Tidigare forskning visar bland annat att socioekonomisk status och barnets uppväxtmiljö påverkar förekomsten av övervikt hos barn och ungdomar. Forskning visar även betydelsen av skolsköterskans samarbete med föräldrar. Idag finns forskning avseende kraftigt överviktiga barn men det saknas kunskap om hur skolsköterskan i ett tidigt skede arbetar med elever som börjar bli överviktiga. Syfte: Att beskriva hur skolsköterskor uppmärksammar och hanterar situationen då en elev börjar bli överviktig. Metod: En pilotstudie har genomförts med en kvalitativ metod där skolsköterskor intervjuats med öppna frågor. Innehållet i intervjuerna har analyserats med kvalitativ innehållsanalys. Resultat: Skolsköterskorna uppmärksammade oftare övervikt hos äldre elever. Skolsköterskorna uppmärksammade elever som började bli överviktiga främst genom viktkurvan och BMI men även genom elevens utseende och beteende. De hanterade situationen genom kontakt med föräldrar, samtal och stöd samt genom att hänvisa vidare till andra instanser inom hälso- och sjukvården. Resultatet visade även att samarbetet mellan skolsköterskan och övriga personal var betydelsefullt. Diskussion: Viktkurvan och BMI var bra verktyg för att uppmärksamma övervikt, detta styrks delvis av tidigare forskning. Betydelsen av samarbetet mellan skolsköterskan och föräldrar styrks av tidigare forskning.