932 resultados para Multilevel linear model
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We analyze recent contributions to growth theory based on the model of expanding variety of Romer (1990). In the first part, we present different versions of the benchmark linear model with imperfect competition. These include the labequipment model, labor-for-intermediates and directed technical change . We review applications of the expanding variety framework to the analysis of international technology diffusion, trade, cross-country productivity differences, financial development and fluctuations. In many such applications, a key role is played by complementarities in the process of innovation.
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Dipteran larvae were collected from rabbit (Oryctolagus cunniculus L.) carcasses during the four seasons in 2005 in the southernmost state of Rio Grande do Sul, Brazil. The larvae were fed ground beef at ambient temperatures following collection from carcasses. The development of each species under these conditions was estimated. The most abundant species in the carcasses were Lucilia eximia (Wiedemann) and Chrysomya albiceps (Wiedemann) (Calliphoridae), and they were found in all seasons. The data were fitted to a linear model that describes the relationship between temperature and linear developmental rating. These two species are primary forensic indicators in southern Brazil. Other species such as Hemilucilia semidiaphana (Rondani) (Calliphoridae), Synthesiomyia nudiseta (Wulp), Muscina stabulans (Fallen) (Muscidae), and Fannia pusio (Wiedemann) (Fanniidae) were forensically less important because they only occurred in high frequency in certain seasons and during the first days of carcass decomposition.
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Se trabajó utilizando una metodología basada en Modelos Lineales Generalizados (MLG). La CPUE fue expresada en toneladas por duración de viaje. Las variables explicativas utilizadas fueron el año, mes, capacidad de bodega, latitud, inercia espacial y distancia a la costa. El modelo tuvo un coeficiente de determinación de 0,485, explicando casi la mitad de la variabilidad de la CPUE observada. La variable con mayor influencia en el modelo fue la capacidad de bodega (49% de la varianza explicada), debido posiblemente a que la flota anchovetera posee una capacidad elevada de captura y que los recursos pelágicos tienden a hiper-agregarse, incluso cuando están siendo fuertemente explotados. La correlación entre la CPUE estandarizada y biomasa estimada por un modelo de captura a la edad (r=0,74) indica que el método basado en MLG es recomendable para la estandarización de la CPUE. Se propone a esta CPUE como una alternativa para monitorear la biomasa de la anchoveta.
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The n-octanol/water partition coefficient (log Po/w) is a key physicochemical parameter for drug discovery, design, and development. Here, we present a physics-based approach that shows a strong linear correlation between the computed solvation free energy in implicit solvents and the experimental log Po/w on a cleansed data set of more than 17,500 molecules. After internal validation by five-fold cross-validation and data randomization, the predictive power of the most interesting multiple linear model, based on two GB/SA parameters solely, was tested on two different external sets of molecules. On the Martel druglike test set, the predictive power of the best model (N = 706, r = 0.64, MAE = 1.18, and RMSE = 1.40) is similar to six well-established empirical methods. On the 17-drug test set, our model outperformed all compared empirical methodologies (N = 17, r = 0.94, MAE = 0.38, and RMSE = 0.52). The physical basis of our original GB/SA approach together with its predictive capacity, computational efficiency (1 to 2 s per molecule), and tridimensional molecular graphics capability lay the foundations for a promising predictor, the implicit log P method (iLOGP), to complement the portfolio of drug design tools developed and provided by the SIB Swiss Institute of Bioinformatics.
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[spa] La mayoría de siniestros con daños corporales se liquidan mediante negociación, llegando a juicio menos del 5% de los casos. Una estrategia de negociación bien definida es, por tanto, fundamental para las compañías aseguradoras. En este artículo asumimos que la compensación monetaria concedida en juicio es la máxima cuantía que debería ser ofrecida por el asegurador en el proceso de negociación. Usando una base de datos real, implementamos un modelo log-lineal para estimar la máxima oferta de negociación. Perturbaciones no-esféricas son detectadas. Correlación ocurre cuando más de una siniestro se liquida en la misma sentencia judicial. Heterocedasticidad por grupos se debe a la influencia de la valoración del forense en la indemnización final.
Resumo:
La regressió basada en distàncies és un mètode de predicció que consisteix en dos passos: a partir de les distàncies entre observacions obtenim les variables latents, les quals passen a ser els regressors en un model lineal de mínims quadrats ordinaris. Les distàncies les calculem a partir dels predictors originals fent us d'una funció de dissimilaritats adequada. Donat que, en general, els regressors estan relacionats de manera no lineal amb la resposta, la seva selecció amb el test F usual no és possible. En aquest treball proposem una solució a aquest problema de selecció de predictors definint tests estadístics generalitzats i adaptant un mètode de bootstrap no paramètric per a l'estimació dels p-valors. Incluim un exemple numèric amb dades de l'assegurança d'automòbils.
Resumo:
[spa] La mayoría de siniestros con daños corporales se liquidan mediante negociación, llegando a juicio menos del 5% de los casos. Una estrategia de negociación bien definida es, por tanto, fundamental para las compañías aseguradoras. En este artículo asumimos que la compensación monetaria concedida en juicio es la máxima cuantía que debería ser ofrecida por el asegurador en el proceso de negociación. Usando una base de datos real, implementamos un modelo log-lineal para estimar la máxima oferta de negociación. Perturbaciones no-esféricas son detectadas. Correlación ocurre cuando más de una siniestro se liquida en la misma sentencia judicial. Heterocedasticidad por grupos se debe a la influencia de la valoración del forense en la indemnización final.
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1. Identifying those areas suitable for recolonization by threatened species is essential to support efficient conservation policies. Habitat suitability models (HSM) predict species' potential distributions, but the quality of their predictions should be carefully assessed when the species-environment equilibrium assumption is violated.2. We studied the Eurasian otter Lutra lutra, whose numbers are recovering in southern Italy. To produce widely applicable results, we chose standard HSM procedures and looked for the models' capacities in predicting the suitability of a recolonization area. We used two fieldwork datasets: presence-only data, used in the Ecological Niche Factor Analyses (ENFA), and presence-absence data, used in a Generalized Linear Model (GLM). In addition to cross-validation, we independently evaluated the models with data from a recolonization event, providing presences on a previously unoccupied river.3. Three of the models successfully predicted the suitability of the recolonization area, but the GLM built with data before the recolonization disagreed with these predictions, missing the recolonized river's suitability and badly describing the otter's niche. Our results highlighted three points of relevance to modelling practices: (1) absences may prevent the models from correctly identifying areas suitable for a species spread; (2) the selection of variables may lead to randomness in the predictions; and (3) the Area Under Curve (AUC), a commonly used validation index, was not well suited to the evaluation of model quality, whereas the Boyce Index (CBI), based on presence data only, better highlighted the models' fit to the recolonization observations.4. For species with unstable spatial distributions, presence-only models may work better than presence-absence methods in making reliable predictions of suitable areas for expansion. An iterative modelling process, using new occurrences from each step of the species spread, may also help in progressively reducing errors.5. Synthesis and applications. Conservation plans depend on reliable models of the species' suitable habitats. In non-equilibrium situations, such as the case for threatened or invasive species, models could be affected negatively by the inclusion of absence data when predicting the areas of potential expansion. Presence-only methods will here provide a better basis for productive conservation management practices.
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Peroxisome proliferator-activated receptors (PPARs) are a potential target for neuroprotection in focal ischemic stroke. These nuclear receptors have major effects in lipid metabolism, but they are also involved in inflammatory processes. Three PPAR isotypes have been identified: alpha, beta (or delta) and gamma. The development of PPAR transgenic mice offers a promising tool for prospective therapeutic studies. This study used MRI to assess the role of PPARalpha and PPARbeta in the development of stroke. Permanent middle cerebral artery occlusion induced focal ischemia in wild-type, PPARalpha-null mice and PPARbeta-null mice. T(2)-weighted MRI was performed with a 7 T MRI scan on day 0, 1, 3, 7 and 14 to monitor lesion growth in the various genotypes. General Linear Model statistical analysis found a significant difference in lesion volume between wild-type and PPAR-null mice for both alpha and beta isotypes. These data validate high-resolution MRI for monitoring cerebral ischemic lesions, and confirm the neuroprotective role of PPARalpha and PPARbeta in the brain.
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Aims: To assess the potential distribution of an obligate seeder and active pyrophyte, Cistus salviifolius, a vulnerable species in the Swiss Red List; to derive scenarios by changing the fire return interval; and to discuss the results from a conservation perspective. A more general aim is to assess the impact of fire as a natural factor influencing the vegetation of the southern slopes of the Alps. Locations: Alps, southern Switzerland. Methods: Presence-absence data to fit the model were obtained from the most recent field mapping of C. salviifolius. The quantitative environmental predictors used in this study include topographic, climatic and disturbance (fire) predictors. Models were fitted by logistic regression and evaluated by jackknife and bootstrap approaches. Changes in fire regime were simulated by increasing the time-return interval of fire (simulating longer periods without fire). Two scenarios were considered: no fire in the past 15 years; or in the past 35 years. Results: Rock cover, slope, topographic position, potential evapotranspiration and time elapsed since the last fire were selected in the final model. The Nagelkerke R-2 of the model for C. salviifolius was 0.57 and the Jackknife area under the curve evaluation was 0.89. The bootstrap evaluation revealed model robustness. By increasing the return interval of fire by either up to 15 years, or 35 years, the modelled C. salviifolius population declined by 30-40%, respectively. Main conclusions: Although fire plays a significant role, topography and rock cover appear to be the most important predictors, suggesting that the distribution of C. salviifolius in the southern Swiss Alps is closely related to the availability of supposedly competition-free sites, such as emerging bedrock, ridge locations or steep slopes. Fire is more likely to play a secondary role in allowing C. salviifolius to extend its occurrence temporarily, by increasing germination rates and reducing the competition from surrounding vegetation. To maintain a viable dormant seed bank for C. salviifolius, conservation managers should consider carrying out vegetation clearing and managing wild fire propagation to reduce competition and ensure sufficient recruitment for this species.
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La regressió basada en distàncies és un mètode de predicció que consisteix en dos passos: a partir de les distàncies entre observacions obtenim les variables latents, les quals passen a ser els regressors en un model lineal de mínims quadrats ordinaris. Les distàncies les calculem a partir dels predictors originals fent us d'una funció de dissimilaritats adequada. Donat que, en general, els regressors estan relacionats de manera no lineal amb la resposta, la seva selecció amb el test F usual no és possible. En aquest treball proposem una solució a aquest problema de selecció de predictors definint tests estadístics generalitzats i adaptant un mètode de bootstrap no paramètric per a l'estimació dels p-valors. Incluim un exemple numèric amb dades de l'assegurança d'automòbils.
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Introduction: Prior clozapine studies indicated no effects, mild inhibition or induction of valproic acid (VPA) on clozapine metabolism. The hypotheses that (i) VPA is a net inducer of clozapine metabolism, and (ii) smoking modifies this inductive effect were tested in a therapeutic drug monitoring study. Methods: After excluding strong inhibitors and inducers, 353 steady-state total clozapine (clozapine plus norclozapine) concentrations provided by 151 patients were analyzed using a random intercept linear model. Results: VPA appeared to be an inducer of clozapine metabolism since total plasma clozapine concentrations in subjects taking VPA were significantly lower (27% lower; 95% confidence interval, 14-39%) after controlling for confounding variables including smoking (35% lower, 28-56%). Discussion: Prospective studies are needed to definitively establish that VPA may (i) be an inducer of clozapine metabolism when induction prevails over competitive inhibition, and (ii) be an inducer even in smokers who are under the influence of smoking inductive effects on clozapine metabolism.
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Many studies have investigated the impacts that climate change could potentially have on the distribution of plant species, but few have attempted to constrain projections through plant dispersal limitations. Instead, most studies published so far have been using the simplification of considering dispersal as either unlimited or null. However, depending on a species' dispersal capacity, landscape fragmentation, and the rate of climatic change, these assumptions can lead to serious over- or underestimation of a species' future distribution. To quantify the discrepancies between unlimited, realistic, and no dispersal scenarios, we carried out projections of future distribution over the 21st century for 287 mountain plant species in a study area of the Western Swiss Alps. For each species, simulations were run for four dispersal scenarios (unlimited dispersal, no dispersal, realistic dispersal and realistic dispersal with long-distance dispersal events) and under four climate change scenarios. Although simulations accounting for realistic dispersal limitations did significantly differ from those considering dispersal as unlimited or null in terms of projected future distribution, using the unlimited dispersal simplification nevertheless provided good approximations for species extinctions under more moderate climate change scenarios. Overall, simulations accounting for dispersal limitations produced, for our mountainous study area, results that were significantly closer to unlimited dispersal than to no dispersal. Finally, analyzing the temporal pattern of species extinctions over the entire 21st century showed that, due to the possibility of a large number of species shifting their distribution to higher elevation, important species extinctions for our study area might not occur before the 2080-2100 time periods.
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The method of instrumental variable (referred to as Mendelian randomization when the instrument is a genetic variant) has been initially developed to infer on a causal effect of a risk factor on some outcome of interest in a linear model. Adapting this method to nonlinear models, however, is known to be problematic. In this paper, we consider the simple case when the genetic instrument, the risk factor, and the outcome are all binary. We compare via simulations the usual two-stages estimate of a causal odds-ratio and its adjusted version with a recently proposed estimate in the context of a clinical trial with noncompliance. In contrast to the former two, we confirm that the latter is (under some conditions) a valid estimate of a causal odds-ratio defined in the subpopulation of compliers, and we propose its use in the context of Mendelian randomization. By analogy with a clinical trial with noncompliance, compliers are those individuals for whom the presence/absence of the risk factor X is determined by the presence/absence of the genetic variant Z (i.e., for whom we would observe X = Z whatever the alleles randomly received at conception). We also recall and illustrate the huge variability of instrumental variable estimates when the instrument is weak (i.e., with a low percentage of compliers, as is typically the case with genetic instruments for which this proportion is frequently smaller than 10%) where the inter-quartile range of our simulated estimates was up to 18 times higher compared to a conventional (e.g., intention-to-treat) approach. We thus conclude that the need to find stronger instruments is probably as important as the need to develop a methodology allowing to consistently estimate a causal odds-ratio.
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PURPOSE: The objective of this study was to investigate the effects of weather, rank, and home advantage on international football match results and scores in the Gulf Cooperation Council (GCC) region. METHODS: Football matches (n = 2008) in six GCC countries were analyzed. To determine the weather influence on the likelihood of favorable outcome and goal difference, generalized linear model with a logit link function and multiple regression analysis were performed. RESULTS: In the GCC region, home teams tend to have greater likelihood of a favorable outcome (P < 0.001) and higher goal difference (P < 0.001). Temperature difference was identified as a significant explanatory variable when used independently (P < 0.001) or after adjustment for home advantage and team ranking (P < 0.001). The likelihood of favorable outcome for GCC teams increases by 3% for every 1-unit increase in temperature difference. After inclusion of interaction with opposition, this advantage remains significant only when playing against non-GCC opponents. While home advantage increased the odds of favorable outcome (P < 0.001) and goal difference (P < 0.001) after inclusion of interaction term, the likelihood of favorable outcome for a GCC team decreased (P < 0.001) when playing against a stronger opponent. Finally, the temperature and wet bulb globe temperature approximation were found as better indicators of the effect of environmental conditions than absolute and relative humidity or heat index on match outcomes. CONCLUSIONS: In GCC region, higher temperature increased the likelihood of a favorable outcome when playing against non-GCC teams. However, international ranking should be considered because an opponent with a higher rank reduced, but did not eliminate, the likelihood of a favorable outcome.