69 resultados para Test reproducibility


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This paper tests the internal consistency of time trade-off utilities.We find significant violations of consistency in the direction predictedby loss aversion. The violations disappear for higher gauge durations.We show that loss aversion can also explain that for short gaugedurations time trade-off utilities exceed standard gamble utilities. Ourresults suggest that time trade-off measurements that use relativelyshort gauge durations, like the widely used EuroQol algorithm(Dolan 1997), are affected by loss aversion and lead to utilities thatare too high.

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This paper presents a test of the predictive validity of various classes ofQALY models (i.e., linear, power and exponential models). We first estimatedTTO utilities for 43 EQ-5D chronic health states and next these states wereembedded in health profiles. The chronic TTO utilities were then used topredict the responses to TTO questions with health profiles. We find that thepower QALY model clearly outperforms linear and exponential QALY models.Optimal power coefficient is 0.65. Our results suggest that TTO-based QALYcalculations may be biased. This bias can be avoided using a power QALY model.

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A family of scaling corrections aimed to improve the chi-square approximation of goodness-of-fit test statistics in small samples, large models, and nonnormal data was proposed in Satorra and Bentler (1994). For structural equations models, Satorra-Bentler's (SB) scaling corrections are available in standard computer software. Often, however, the interest is not on the overall fit of a model, but on a test of the restrictions that a null model say ${\cal M}_0$ implies on a less restricted one ${\cal M}_1$. If $T_0$ and $T_1$ denote the goodness-of-fit test statistics associated to ${\cal M}_0$ and ${\cal M}_1$, respectively, then typically the difference $T_d = T_0 - T_1$ is used as a chi-square test statistic with degrees of freedom equal to the difference on the number of independent parameters estimated under the models ${\cal M}_0$ and ${\cal M}_1$. As in the case of the goodness-of-fit test, it is of interest to scale the statistic $T_d$ in order to improve its chi-square approximation in realistic, i.e., nonasymptotic and nonnormal, applications. In a recent paper, Satorra (1999) shows that the difference between two Satorra-Bentler scaled test statistics for overall model fit does not yield the correct SB scaled difference test statistic. Satorra developed an expression that permits scaling the difference test statistic, but his formula has some practical limitations, since it requires heavy computations that are notavailable in standard computer software. The purpose of the present paper is to provide an easy way to compute the scaled difference chi-square statistic from the scaled goodness-of-fit test statistics of models ${\cal M}_0$ and ${\cal M}_1$. A Monte Carlo study is provided to illustrate the performance of the competing statistics.

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Although it is commonly accepted that most macroeconomic variables are nonstationary, it is often difficult to identify the source of the non-stationarity. In particular, it is well-known that integrated and short memory models containing trending components that may display sudden changes in their parameters share some statistical properties that make their identification a hard task. The goal of this paper is to extend the classical testing framework for I(1) versus I(0)+ breaks by considering a a more general class of models under the null hypothesis: non-stationary fractionally integrated (FI) processes. A similar identification problem holds in this broader setting which is shown to be a relevant issue from both a statistical and an economic perspective. The proposed test is developed in the time domain and is very simple to compute. The asymptotic properties of the new technique are derived and it is shown by simulation that it is very well-behaved in finite samples. To illustrate the usefulness of the proposed technique, an application using inflation data is also provided.

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This paper proposes a nonparametric test in order to establish the level of accuracy of theforeign trade statistics of 17 Latin American countries when contrasted with the trade statistics of the main partners in 1925. The Wilcoxon Matched-Pairs Ranks test is used to determine whether the differences between the data registered by exporters and importers are meaningful, and if so, whether the differences are systematic in any direction. The paper tests for the reliability of the data registered for two homogeneous products, petroleum and coal, both in volume and value. The conclusion of the several exercises performed is that we cannot accept the existence of statistically significant differences between the data provided by the exporters and the registered by the importing countries in most cases. The qualitative historiography of Latin American describes its foreign trade statistics as mostly unusable. Our quantitative results contest this view.

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This paper proposes a new time-domain test of a process being I(d), 0 < d = 1, under the null, against the alternative of being I(0) with deterministic components subject to structural breaks at known or unknown dates, with the goal of disentangling the existing identification issue between long-memory and structural breaks. Denoting by AB(t) the different types of structural breaks in the deterministic components of a time series considered by Perron (1989), the test statistic proposed here is based on the t-ratio (or the infimum of a sequence of t-ratios) of the estimated coefficient on yt-1 in an OLS regression of ?dyt on a simple transformation of the above-mentioned deterministic components and yt-1, possibly augmented by a suitable number of lags of ?dyt to account for serial correlation in the error terms. The case where d = 1 coincides with the Perron (1989) or the Zivot and Andrews (1992) approaches if the break date is known or unknown, respectively. The statistic is labelled as the SB-FDF (Structural Break-Fractional Dickey- Fuller) test, since it is based on the same principles as the well-known Dickey-Fuller unit root test. Both its asymptotic behavior and finite sample properties are analyzed, and two empirical applications are provided.

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When the behaviour of a specific hypothesis test statistic is studied by aMonte Carlo experiment, the usual way to describe its quality is by givingthe empirical level of the test. As an alternative to this procedure, we usethe empirical distribution of the obtained \emph{p-}values and exploit itsinformation both graphically and numerically.

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We have reported in a variety of mammalian cells the reversible formation of a filamentous actin (F-actin)-enriched aggresome generated by the actin toxin jasplakinolide (Lázaro-Diéguez et al., J Cell Sci 2008; 121:1415-25). Notably, this F-actin aggresome (FAG) resembles in many aspects the pathological Hirano body, which frequently appears in some diseases such as Alzheimer's and alcoholism. Using selective inhibitors, we examined the molecular and subcellular mechanisms that participate in the clearance of the FAG. Chaperones, microtubules, proteasomes and autophagosomes all actively participate to eliminate the FAG. Here we compile and compare these results and discuss the involvement of each process. Because of its simplicity and high reproducibility, our cellular model could help to test pharmacological agents designed to interfere with the mechanisms involved in the clearance of intracellular bodies and, in particular, of those enriched in F-actin.

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Several unit root tests in panel data have recently been proposed. The test developed by Harris and Tzavalis (1999 JoE) performs particularly well when the time dimension is moderate in relation to the cross-section dimension. However, in common with the traditional tests designed for the unidimensional case, it was found to perform poorly when there is a structural break in the time series under the alternative. Here we derive the asymptotic distribution of the test allowing for a shift in the mean, and assess the small sample performance. We apply this new test to show how the hypothesis of (perfect) hysteresis in Spanish unemployment is rejected in favour of the alternative of the natural unemployment rate, when the possibility of a change in the latter is considered.

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Several unit root tests in panel data have recently been proposed. The test developed by Harris and Tzavalis (1999 JoE) performs particularly well when the time dimension is moderate in relation to the cross-section dimension. However, in common with the traditional tests designed for the unidimensional case, it was found to perform poorly when there is a structural break in the time series under the alternative. Here we derive the asymptotic distribution of the test allowing for a shift in the mean, and assess the small sample performance. We apply this new test to show how the hypothesis of (perfect) hysteresis in Spanish unemployment is rejected in favour of the alternative of the natural unemployment rate, when the possibility of a change in the latter is considered.

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We derive a simple closed analytical expression for the total entropy production along a single stochastic trajectory of a Brownian particle diffusing on a periodic potential under an external constant force. By numerical simulations we compute the probability distribution functions of the entropy and satisfactorily test many of the predictions based on Seiferts integral fluctuation theorem. The results presented for this simple model clearly illustrate the practical features and implications derived from such a result of nonequilibrium statistical mechanics.

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A modified magnesium hydrogen breath test, using end expiratory breath sampling, is described to investigate achlorhydria. The efficacy of this test in the diagnostic investigation of pernicious anaemia was compared with that of serum pepsinogen I. Twenty one patients with pernicious anaemia--that is, patients with achlorhydria--and 22 with healed duodenal ulcer and normal chlorhydria were studied. Magnesium hydrogen breath test, serum pepsinogen I, serum gastrin, and standard gastric acid secretory tests were performed in all subjects. The mean (SEM) hydrogen peak value was lower in patients with pernicious anaemia than in the duodenal ulcer group (21.7 (1.9) v 71.3 (5.2) ppm; p = 0.00005). The hydrogen peak value had a 95.2% sensitivity and a 100% specificity to detect pentagastrin resistant achlorhydria. Mean serum pepsinogen I concentrations were also significantly lower in patients with pernicious anaemia than in the duodenal ulcer group (10.7 (2.7) v 123.6 (11.8) micrograms/l p = 0.00005). Sensitivity and specificity to detect pernicious anaemia were both 100% for pepsinogen I. It is concluded that this modified magnesium hydrogen breath test is a simple, noninvasive, cost effective, and accurate method to assess achlorhydria and may be useful in the diagnostic investigation of patients with suspected pernicious anaemia.

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The paper analyses and compares infrasonic and seismic data from snow avalanches monitored at the Vallée de la Sionne test site in Switzerland from 2009 to 2010. Using a combination of seismic and infrasound sensors, it is possible not only to detect a snow avalanche but also to distinguish between the different flow regimes and to analyse duration, average speed (for sections of the avalanche path) and avalanche size. Different sensitiveness of the seismic and infrasound sensors to the avalanche regimes is shown. Furthermore, the high amplitudes observed in the infrasound signal for one avalanche were modelled assuming that the suspension layer of the avalanche acts as a moving turbulent sound source. Our results show reproducibility for similar avalanches on the same avalanche path.

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Podeu consultar la Setena trobada de professorat de Ciències de la Salut completa a: http://hdl.handle.net/2445/43352

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Podeu consultar la Setena trobada de professorat de Ciències de la Salut completa a: http://hdl.handle.net/2445/43352