A Swedish radon data set, consisting of more than 8000 measurements of residential radon levels in about 50% of the Swedish municipalities were analysed using a multilevel approach.

The results were compared with those of a single-level analysis. We found that there was a significant variability between municipalities. The point estimates of the population mean radon levels were similar (geometric mean 60 Bq/m3 and arithmetic mean 106 Bq/m3).

The analysis shows the advantages of multilevel modeling compared with a single-level OLS model.

A single-level model results in too optimistic standard errors, about 25% of those of the multilevel

model which can lead to erroneous conclusions.

In a multilevel model including house type as a fixed effect (single-family house, row house, or apartment in multi-family house), the estimates of the fixed effect of house type were similar for the single-level and the multi-level models

This paper describes an alternative approach for testing for the existence of trend among time series. The test method has been constructed using wavelet analysis which has the ability of decomposing a time series into low frequencies (trend) and high-frequency (noise) components. Under the normality assumption, the test is distributed as F. However, using generated empirical critical values, the properties of the test statistic have been investigated under different conditions and different types of wavelet. The Harr wavelet has shown to exhibit the highest power among the other wavelet types. The methodology here has been applied to real temperature data in Sweden for the period 1850-1999. The results indicate a significant increasing trend which agrees with the 'global warming' hypothesis during the last 100 years.

This article introduces two different non-parametric wavelet-based panel unit-root tests in the presence of unknown structural breaks and cross-sectional dependencies in the data. These tests are compared with a previously suggested non-parametric wavelet test, the parameteric Im-Pesaran and Shin (IPS) test and a Wald type of test. The results from the Monte Carlo simulations clearly show that the new wavelet-ratio tests are superior to the traditional tests both in terms of size and power in panel unit-root tests because of its robustness to cross-section dependency and structural breaks. Based on an empirical Central American panel application, we can, in contrast to previous research (where bias due to structural breaks is simply disregarded), find strong, clear-cut support for purchasing power parity (PPP) in this developing region.

Quarterly data for the period 1960:1 to 1997:2, conventional tests, a bootstrap simulation approach and a multivariate Rao's F-test have been used to investigate if the causality between government spending and revenue in Finland was changed at the beginning of 1990 due to future plans to create the European Monetary Union (EMU). The results indicate that during the period before 1990, the government revenue Granger-caused spending, while the opposite happened after 1990, which agrees better with Barro's tax smoothing hypothesis. However, when using monthly data instead of quarterly data for almost the same sample period, totally different results have been noted. The general conclusion is that the relationship between spending and revenue in Finland is still not completely understood. The ambiguity of these results may well be due to the fact that there are several time scales involved in the relationship, and that the conventional analyses may be inadequate to separate out the time scale structured relationships between these variables. Therefore, to investigate empirically the relation between these variables we attempt to use the wavelets analysis that enables us to separate out different time scales of variation in the data. We find that time scale decomposition is important for analysing these economic variables.

Objectives: To investigate whether routinely collected data from hospital episode statistics could be used to identify the gynaecologist Rodney Ledward, who was suspended in 1966 and was the subject of the Ritchie inquiry into quality and practice within the NHS.

Design A mixed scanning approach was used to identify seven variables from hospital episode statistics that were likely to be associated with potentially poor performance. A blinded multivariate analysis was undertaken to determine the distance (known as the Mahalanobis distance) in the seven indicator multidimensional space that each consultant was from the average consultant in each year. The change in Mahalanobis distance over time was also investigated by using a mixed effects model.



Setting: NHS hospital trusts in two English regions, in the five years from 1991-2 to 1995-6.



Population: Gynaecology consultants (n = 143) and their hospital episode statistics data.



Main outcome measure Whether Ledward was a statistical outlier at the 95% level.



Results: The proportion of consultants who were outliers in any one year (at the 95% significance level) ranged from 9% to 20%. Ledward appeared as an outlier in three of the five years. Our mixed effects (multi-year) model identified nine high outlier consultants, including Ledward.



Conclusion: It was possible to identify Ledward as an outlier by using hospital episode statistics data. Although our method found other outlier consultants, we strongly caution that these outliers should not be overinterpreted as indicative of "poor" performance. Instead, a scientific search for a credible explanation should be undertaken, but this was outside the remit of our study. The set of indicators used means that cancer specialists, for example, are likely to have high values for several indicators, and the approach needs to be refined to deal with case mix variation. Even after allowing for that, the interpretation of outlier status is still as yet unclear. Further prospective evaluation of our method is warranted, but our overall approach may be potentially useful in other settings, especially where performance entails several indicator variables.

Abstract

Women constitute a clear minority in the field of information and communications technology (ICT) in higher education as well as in the job market. At the same time, this field is expected to have a shortage of qualified people in the future. Do women and men engineering graduates have the same career opportunities? This article problematizes the relationship between higher education in engineering and opportunities on the job market. The results show that men reach higher positions to a greater extent than women, and that women remain in low-qualification jobs to a greater extent than men.

Kvinnor utgör en klar minoritet inom området informations- och kommunikationsteknologi, både inom den högre utbildningen och på arbetsmarknaden. Artikeln problematiserar relationen mellan den högre tekniska utbildningen och positioner på arbetsmarknaden. Får kvinnor och män samma utbyte av sin ingenjörsexamen i arbetslivet? Resultaten visar att män i större utsträckning än kvinnor når högre positioner. Vidare ser vi att kvinnor stannar i lågkvalificerade jobb i högre utsträckning än män.

Detecting and estimating long-range dependence are important in the analysis of many environmental time series. This article proposes a periodogram roughness (PR) estimator and describes its uses for testing and estimating the dependence structure. Asymptotic critical values are generated for performing the test, and special attention is given to investigating the properties of the PR regarding size and power. The conventional short-memory models, such as the autoregressive (AR), are shown to be less parsimonious. Forecasting errors of both fractional Gaussian noise (FGN) and fractional autoregressive moving average (FARMA) are investigated by conducting simulation studies. In addition to the PR, maximum likelihood (ML) and semi-parametric (SP) estimators are used and evaluated. Our results have shown that more accurate forecasted points are obtained when using the fractional forecasting. The methods are illustrated using Swedish wind speed data