Description of an approach based on maximum likelihood to adjust an excess hazard model with a random effect

Objective: To adjust an excess hazard regression model with a random effect associated with a geographical level, the Département in France, and compare its parameter estimates with those obtained using a “fixed-effect” excess hazard regression model. Methods: An excess hazard regression model with a piecewise constant baseline hazard was used and a normal distribution was assumed for the random effect. Likelihood maximization was performed using a numerical integration technique, the Quadrature of Gauss–Hermite. Results were obtained with colon-rectum and thyroid cancer data from the French network of cancer registries. Result: The results were in agreement with what was theoretically expected. We showed a greater heterogeneity of the excess hazard in thyroid cancers than in colon-rectum cancers. The hazard ratios for the covariates as estimated with the mixed-effect model were close to those obtained with the fixed-effect model. However, unlike the fixed-effect model, the mixed-effect model allowed the analysis of data with a large number of clusters. The shrinkage estimator associated with Département is an optimal measure of Département-specific excess risk of death and the variance of the random effect gave information on the within-cluster correlation. Conclusion: An excess hazard regression model with random effect can be used for estimating variation in the risk of death due to cancer between many clusters of small sizes.     

On estimation in relative survival

Estimation of relative survival has become the first and the most basic step when reporting cancer survival statistics. Standard estimators are in routine use by all cancer registries. However, it has been recently noted that these estimators do not provide information on cancer mortality that is independent of the national general population mortality. Thus they are not suitable for comparison between countries. Furthermore, the commonly used interpretation of the relative survival curve is vague and misleading. The present article attempts to remedy these basic problems. The population quantities of the traditional estimators are carefully described and their interpretation discussed. We then propose a new estimator of net survival probability that enables the desired comparability between countries. The new estimator requires no modeling and is accompanied with a straightforward variance estimate. The methods are described on real as well as simulated data.     

Detection of significant demographic differences between subpopulations of prehispanic Maya from Copan, Honduras, by survival analysis

Heterogeneity and small sample size are problems that affect many paleodemographic studies. The former can cause the overall distribution of age at death to be an amalgam that does not accurately reflect the distributions of any of the groups composing the heterogeneous population. The latter can make it difficult to separate significant from nonsignificant demographic differences between groups. Survival analysis, a methodology that involves the survival distribution function and various regression models, can be applied to distributions of age at death in order to reveal statistically significant demographic differences and to control for heterogeneity. Survival analysis was used on demographic data from a heterogeneous sample of skeletons of low status Maya who lived in and around Copan, Honduras, between A.D. 400 and 1200. Results contribute to understanding the collapse of Classic Maya civilization.     

Estimating and modeling the cure fraction in population-based cancer survival analysis

In population-based cancer studies, cure is said to occur when the mortality (hazard) rate in the diseased group of individuals returns to the same level as that expected in the general population. The cure fraction (the proportion of patients cured of disease) is of interest to patients and is a useful measure to monitor trends in survival of curable disease. There are 2 main types of cure fraction model, the mixture cure fraction model and the non-mixture cure fraction model, with most previous work concentrating on the mixture cure fraction model. In this paper, we extend the parametric non-mixture cure fraction model to incorporate background mortality, thus providing estimates of the cure fraction in population-based cancer studies. We compare the estimates of relative survival and the cure fraction between the 2 types of model and also investigate the importance of modeling the ancillary parameters in the selected parametric distribution for both types of model.     

The Accelerated Failure Time Model Under Biased Sampling

Summary Chen (2009, Biometrics) studies the semi‐parametric accelerated failure time model for data that are size biased. Chen considers only the uncensored case and uses hazard‐based estimation methods originally developed for censored observations. However, for uncensored data, a simple linear regression on the log scale is more natural and provides better estimators.     

冬小麦农田中净辐射的研究

本文对陕西泾阳地区冬小麦田净辐射进行了分段和分层模拟,取得了较好的拟合效果,相对误差在１０％以内。确定了麦田相对叶面积函数最大值的出现高度为４．５／７Ｈ,介于高粱（４／７Ｈ）和谷子（５／７Ｈ）之间。计算了不同发育期、不同层次至冠层顶部累积叶片的消光系数,结果表明,消光系数因发育期和叶片层次而异,拔节期,由旗叶向下,消光系数增大,乳熟期旗叶的消光系数最大,比拔节期大一倍,倒二叶以上两个层次叶片消光系数较小。就平均而言,冬小麦消光系数拔节期为０．５１,乳熟期为０．５６。本项成果为进一步开展麦田小气候研究提供了有意义的数据和方法。     

A semiparametric approach for the nonparametric transformation survival model with multiple covariates

The nonparametric transformation model makes no parametric assumptions on the forms of the transformation function and the error distribution. This model is appealing in its flexibility for modeling censored survival data. Current approaches for estimation of the regression parameters involve maximizing discontinuous objective functions, which are numerically infeasible to implement with multiple covariates. Based on the partial rank (PR) estimator (Khan and Tamer, 2004), we propose a smoothed PR estimator which maximizes a smooth approximation of the PR objective function. The estimator is shown to be asymptotically equivalent to the PR estimator but is much easier to compute when there are multiple covariates. We further propose using the weighted bootstrap, which is more stable than the usual sandwich technique with smoothing parameters, for estimating the standard error. The estimator is evaluated via simulation studies and illustrated with the Veterans Administration lung cancer data set.     

Structure and productivity along a tree height gradient in a Kandelia obovata mangrove forest in the Manko Wetland, Okinawa Island, Japan

Tree height (H) of Kandelia obovata trees decreased sharply from 5 m at the forest interior behind the terrestrial forest to 1.5 m at the forest edge near the river bank according to an increase in the yearly waterlogged period along a belt transect. The decreasing tree stature was attributed to a decrease in the asymptote of H in the D _0.1 (stem diameter at H/10)-H relationship toward the edge. The K. obovata trees were well classified into interior and edge types using a discriminant function based on the habitat-specific D _0.1–H relationships. Allometric equations, as a function of D _0.1² H, differed significantly between the interior and edge types in the estimation of the phytomasses of stems and leaves, and the leaf area per tree. On the other hand, common allometric equations were successfully established in the estimation of respective phytomasses of aboveground parts and branches. Biomass and leaf area index decreased toward the forest edge. The biomass allocation to stems decreased toward the edge, whereas those to branches and leaves increased. A dramatic change in stem diameter increment resulted in differences in the D _0.1–H relationship along the tree height gradient. Relative growth rate of biomass and light-saturated net photosynthesis, which paralleled net assimilation rate from the interior to the edge, showed their maximum peaks in the middle of the belt transect. This indicates that there exists an optimal environmental condition for growth of K. obovata trees. Leaf nitrogen content tended to increase to the edge with increasing waterlogged period.     

Responses of photosynthesis,leaf conductance and growth to different salinities in three coastal dune plants

The effects of soil-water salinity on growth and photosynthesis of three coastal dune plants were examined by salt-treatment in order to clarify the causal relationship between salinity and plant distribution in a dune habitat. Plants were cultivated hydroponically at three salinity levels: 0, 10 and 100 mM NaCl. With the 100 mM salt treatment,Calystegia soldanella (C₃ species) had the highest relative growth rate (RGR) (0.085 g g⁻¹ d⁻¹), followed byCarex kobomugi (C₃) (0.066), andIschaemum anthephoroides (C₄) (0.060). This order coincides with the distribution pattern of the three species on coastal dunes;Calystegia soldanella is generally distributed in more seaward areas whereasI. anthephoroides occurs further inland. The order of RGR was determined exclusively by leaf area ratio (LAR) among the three species. Due to its C₄ pathway,I. anthephoroides had higher net photosynthetic rate (Pn) and net assimilation rate (NAR) than the two C₃ plants at all NaCl concentrations, despite its low RGR. This apparent discrepancy is explainable by differences of LAR among the three species; LAR ofI. anthephoroides was lowest, and about half that ofCalystegia soldanella. These results suggest that LAR is one of the main determinants of salt tolerance based on RGR, whereas Pn or NAR may not be significant. This article is dedicated to Professor Hideo Iwaki, University of Tsukuba, in appreciation of the sincere encouragement he has given to the authors.     

WSE, a new sequence distance measure based on word frequencies

In this article, we present a new distance metric, the Weighted Sequence Entropy (WSE), based on the short word composition of biological sequences. As a revision of the classical relative entropy (RE), our metric (1) works equivalently with RE in the case of small k, (2) avoids the degeneracy when some word types are absent in one sequence but not in the other. Experiments on 25 viruses including SARS-CoVs show that our method and RE give exactly the same phylogenetic tree when word length k3. When k>3, our method still works and gets convergent phylogenetic topology but the RE gives degenerate results.     

The influence of water level on the growth and photosynthesis of Hydrocotyle ranunculoides L.fil.

Floating Pennywort (Hydrocotyle ranunculoides L.fil.), a native to North America and naturalized in Central and South America, is an invasive aquatic weed in western Europe and several other regions worldwide. H. ranunculoides settles primarily in stagnant to slow-flowing waters (e.g. ditches, canals, rivers, lakes and ponds). The species prefers sunny and nutrient-rich sites and forms dense interwoven mats, which can quickly cover the surface of infested waters. In this study, the effect of three different water levels on growth of Floating Pennywort was investigated. Plants were cultivated on high-nutrient soils under waterlogged, semi-drained and drained conditions. Highest relative growth rates (RGR) of 0.097±0.004 g g⁻¹ dw d⁻¹ were reached under waterlogged conditions. This was significantly higher than RGR of plants cultivated semi-drained and drained. Floating Pennywort showed some phenological adaptations to drained soil conditions, including significant differences in the relative amounts of leaf, petiole and shoot biomass, whilst the relative amount of root biomass was not significantly influenced by the water level. Furthermore, Floating Pennywort reached under drained conditions lower relative water contents (RWC) of leaves, petioles and shoots, a significant shorter length of internodes, a significant lower extent of shoot porosity (POR), a lower chlorophyll content and an increased Chl_a:Chl_b ratio. In addition, maximum gas exchange of drained cultivated plants is significantly lower, due to strongly decreased leaf conductance under reduced water availability. Overall, H. ranunculoides showed ability to grow under different water levels, but performed best under waterlogged conditions.     

Growth characteristics,nutrient allocation and photosynthesis ofCarex species from floating fens

Summary The purpose of this study was to investigate various growth parameters, dry matter and nitrogen, phosphorus and potassium allocation and photosynthesis ofCarex acutiformis, C. rostrata andC. diandra growing in fens with, in this order, decreasing nutrient availability and decreasing aboveground productivity. Plants were grown from cuttings at optimum nutrient conditions in a growth chamber. Growth analysis at sequential harvests revealed that the species had no inherently different relative growth rates which could explain their different productivity, but that their LAR (LWR and SLA) decreased in the orderC. acutiformis, C. rostrata, C. diandra and their NAR increased in this order. All growth parameters decreased during plant growth even under the controlled conditions of the experiment.C. acutiformis allocated relatively much dry matter to the leaves,C. rostrata to the rhizomes andC. diandra to the roots. This may, in part, explain the higher aboveground biomass production ofC. acutiformis in the field. Nitrogen, but not phosphorus and potassium, allocation patterns were different for the three species.C. diandra, the species from the nitrogen-poorest site, had the highest leaf N content of the three species and also a higher chlorophyll content. Related to this, this species had the highest photosynthetic activity of whole plants both when collected from the field and when grown in the growth chamber. The nitrogen productivity was similar for the three species and the photosynthetic nitrogen use efficiency, determined forC. acutiformis andC. diandra, was similar for these two species.C. diandra had the most finely branched root system, i.e., the highest specific root length of the three species and its root surface area to leaf surface area ratio was also the highest. All three species showed higher nitrate reductase activity in the leaves than in the roots when grown on nutrient solution. The growth ofC. diandra at a relatively nutrient-poor site and a rather open low vegetation is assumed to be adapted to its habitat by a relatively high NAR made possible by a high rate of photosynthesis concurrent with a high leaf N content. The growth ofC. acutiformis at a relatively nutrient-rich site and a more dense and higher vegetation is adapted to its habitat by a high LAR.     

Components of variation in seedling potential relative growth rate: phylogenetically independent contrasts

Variation between species in seedling potential relative growth rate (RGR) is among the most important spectra of plant adaptation. Investigations are reported into the components responsible for this variation, using phylogenetically independent contrasts (PICs). The two species for each PIC were selected to diverge in seed mass at least four-fold, seed mass being a known correlate of RGR. Consistent with previous reports, the main influence on RGR differences between species was leaf area per unit leaf mass (SLA), rather than net assimilation rate per leaf area (NAR_a). The PIC design showed that SLA differences both underpinned old RGR divergences between orders and families, and also were repeatedly responsible for more recent RGR divergences between genera and species.     

Above-ground biomass estimation based on NPP time-series − A novel approach for biomass estimation in semi-arid Kazakhstan

Biomass is a sensitive indicator of environmental change and ecological functioning. Quantification of biomass is essential to identify and monitor those areas threatened by degradation and desertification. This is especially important in arid and semi-arid environments. However, robust techniques to monitor carbon stocks over large areas and through time are still missing. The major objective of the presented study is to develop a novel approach for biomass estimation in semi-arid environments using remote-sensing based Net Primary Productivity (NPP) data.The developed methodical concept aims at derivation of above-ground grass and shrub biomass for natural environments. It is based on NPP time-series and plants’ relative growth rates. Fractional cover data provide information about grass and shrub coverage. The developed approach has been applied to three study areas in Kazakhstan, in which field data were collected for validation.Biomass maps were derived that show the spatial distribution of grass and shrub biomass. Validation revealed a moderate correlation (R = 0.68) with field data for grass biomass. For shrub biomass, a high correlation (R = 0.83) is retrieved when fractional cover information from field observations is used.The presented novel approach for biomass estimation is based on remote sensing derived NPP time-series and is thus potentially transferable in space and time. This is a great advantage compared to commonly applied empirical relationships. The presented concept can be adapted to be applied to other vegetation communities. Providing the necessary data about fractional vegetation cover is available, the method will allow for repeated and large-area biomass estimation for natural semi-arid environments as needed for observing changes in biomass and support sustainable land management.     

A Comparison Between Several Goodness of Fit Tests for Cox's Model

A comparison is made between two approaches to testing goodness of fit of Cox's regression model for survival data. The first approach is based on the inclusion of time dependent covariates, whereas the second one is based on the autocovariance of successive contributions to the derivative of the loglikelihood. It appears that the second test is most appropriate for testing in situations where the structure of the departure from proportional hazards is not known a priori. An approximate expression for the relative efficiency of the two test procedures is presented.