Statistical Inference Methods for Two Crossing Survival Curves: A Comparison of Methods

A common problem that is encountered in medical applications is the overall homogeneity of survival distributions when two survival curves cross each other. A survey demonstrated that under this condition, which was an obvious violation of the assumption of proportional hazard rates, the log-rank test was still used in 70% of studies. Several statistical methods have been proposed to solve this problem. However, in many applications, it is difficult to specify the types of survival differences and choose an appropriate method prior to analysis. Thus, we conducted an extensive series of Monte Carlo simulations to investigate the power and type I error rate of these procedures under various patterns of crossing survival curves with different censoring rates and distribution parameters. Our objective was to evaluate the strengths and weaknesses of tests in different situations and for various censoring rates and to recommend an appropriate test that will not fail for a wide range of applications. Simulation studies demonstrated that adaptive Neyman’s smooth tests and the two-stage procedure offer higher power and greater stability than other methods when the survival distributions cross at early, middle or late times. Even for proportional hazards, both methods maintain acceptable power compared with the log-rank test. In terms of the type I error rate, Renyi and Cramér—von Mises tests are relatively conservative, whereas the statistics of the Lin-Xu test exhibit apparent inflation as the censoring rate increases. Other tests produce results close to the nominal 0.05 level. In conclusion, adaptive Neyman’s smooth tests and the two-stage procedure are found to be the most stable and feasible approaches for a variety of situations and censoring rates. Therefore, they are applicable to a wider spectrum of alternatives compared with other tests.     

A Comparison of Statistical Methods for Identifying Out-of-Date Systematic Reviews

Background

Systematic reviews (SRs) can provide accurate and reliable evidence, typically about the effectiveness of health interventions. Evidence is dynamic, and if SRs are out-of-date this information may not be useful; it may even be harmful. This study aimed to compare five statistical methods to identify out-of-date SRs.

Methods

A retrospective cohort of SRs registered in the Cochrane Pregnancy and Childbirth Group (CPCG), published between 2008 and 2010, were considered for inclusion. For each eligible CPCG review, data were extracted and “3-years previous” meta-analyses were assessed for the need to update, given the data from the most recent 3 years. Each of the five statistical methods was used, with random effects analyses throughout the study.

Results

Eighty reviews were included in this study; most were in the area of induction of labour. The numbers of reviews identified as being out-of-date using the Ottawa, recursive cumulative meta-analysis (CMA), and Barrowman methods were 34, 7, and 7 respectively. No reviews were identified as being out-of-date using the simulation-based power method, or the CMA for sufficiency and stability method. The overall agreement among the three discriminating statistical methods was slight (Kappa = 0.14; 95% CI 0.05 to 0.23). The recursive cumulative meta-analysis, Ottawa, and Barrowman methods were practical according to the study criteria.

Conclusion

Our study shows that three practical statistical methods could be applied to examine the need to update SRs.     

A Statistical Method for Comparison of Two Structures and Its Biological Applications

Some experimental methods applied to biological investigations allow to find a number q of homogeneous discrete components that determine a structure of the object in the study and the to establish the presence of some components from these q in compositions of other n objects. Such data form a nXq incidence matrix. In this paper a statistical approach is suggested for revealing the associated components in two different structures of the object. The procedure is based on joint consideration of two sampling incidence matrices. An application of this method is demonstrated by analysis of relationships between antigens and proteins of one strain of cyanobacteria. The method may be useful in different scientific areas, e.g. psychology, when direct experimental comparison of components from two structures is difficult.     

Statistical Analysis of Individual Participant Data Meta-Analyses: A Comparison of Methods and Recommendations for Practice

Background

Individual participant data (IPD) meta-analyses that obtain “raw” data from studies rather than summary data typically adopt a “two-stage” approach to analysis whereby IPD within trials generate summary measures, which are combined using standard meta-analytical methods. Recently, a range of “one-stage” approaches which combine all individual participant data in a single meta-analysis have been suggested as providing a more powerful and flexible approach. However, they are more complex to implement and require statistical support. This study uses a dataset to compare “two-stage” and “one-stage” models of varying complexity, to ascertain whether results obtained from the approaches differ in a clinically meaningful way.

Methods and Findings

We included data from 24 randomised controlled trials, evaluating antiplatelet agents, for the prevention of pre-eclampsia in pregnancy. We performed two-stage and one-stage IPD meta-analyses to estimate overall treatment effect and to explore potential treatment interactions whereby particular types of women and their babies might benefit differentially from receiving antiplatelets. Two-stage and one-stage approaches gave similar results, showing a benefit of using anti-platelets (Relative risk 0.90, 95% CI 0.84 to 0.97). Neither approach suggested that any particular type of women benefited more or less from antiplatelets. There were no material differences in results between different types of one-stage model.

Conclusions

For these data, two-stage and one-stage approaches to analysis produce similar results. Although one-stage models offer a flexible environment for exploring model structure and are useful where across study patterns relating to types of participant, intervention and outcome mask similar relationships within trials, the additional insights provided by their usage may not outweigh the costs of statistical support for routine application in syntheses of randomised controlled trials. Researchers considering undertaking an IPD meta-analysis should not necessarily be deterred by a perceived need for sophisticated statistical methods when combining information from large randomised trials.     

MitoLSDB: A Comprehensive Resource to Study Genotype to Phenotype Correlations in Human Mitochondrial DNA Variations

Human mitochondrial DNA (mtDNA) encodes a set of 37 genes which are essential structural and functional components of the electron transport chain. Variations in these genes have been implicated in a broad spectrum of diseases and are extensively reported in literature and various databases. In this study, we describe MitoLSDB, an integrated platform to catalogue disease association studies on mtDNA (http://mitolsdb.igib.res.in). The main goal of MitoLSDB is to provide a central platform for direct submissions of novel variants that can be curated by the Mitochondrial Research Community. MitoLSDB provides access to standardized and annotated data from literature and databases encompassing information from 5231 individuals, 675 populations and 27 phenotypes. This platform is developed using the Leiden Open (source) Variation Database (LOVD) software. MitoLSDB houses information on all 37 genes in each population amounting to 132397 variants, 5147 unique variants. For each variant its genomic location as per the Revised Cambridge Reference Sequence, codon and amino acid change for variations in protein-coding regions, frequency, disease/phenotype, population, reference and remarks are also listed. MitoLSDB curators have also reported errors documented in literature which includes 94 phantom mutations, 10 NUMTs, six documentation errors and one artefactual recombination. MitoLSDB is the largest repository of mtDNA variants systematically standardized and presented using the LOVD platform. We believe that this is a good starting resource to curate mtDNA variants and will facilitate direct submissions enhancing data coverage, annotation in context of pathogenesis and quality control by ensuring non-redundancy in reporting novel disease associated variants.     

Evaluating the Evidence for Hormesis: A Statistical Perspective

It is possible to account for hormesis under current regulatory guidelines by invoking criteria for departure from default risk assessment procedures. However, past experience suggests that it will be difficult to amass enough evidence for hormesis in an individual case to permit departure from default procedures. Accordingly, hormesis is likely to be important in agency risk assessments only if guidelines are modified to incorporate hormesis as a default assumption. This could be appropriate if hormesis is determined to be a universal or near-universal phenomenon. Although there is ample evidence that hormesis occurs in many specific situations, the overall prevalence of hormesis is very difficult to evaluate based on currently available data. The lack of a valid statistical test for hormesis is a major limitation when evaluating evidence for hormesis. The attempts at estimating the prevalence of hormesis reviewed herein did not adequately control for false positives and/or may have had inadequate power to detect hormesis. Some suggestions are made for constructing a database and analyzing the data therein that would provide more readily interpretable information on the prevalence of hormesis.     

A Palynological Method for Stratigraphical Correlations

A method for the stratigraphical correlation and dating of Lower Cretaceous deposits from south-eastern France and north-eastern Spain is proposed, on the basis of a morphological analysis of pollen grains belonging to the form-genus Classopollis (Pflug) Pocock & Jansonius. This method has made possible correlations between microfloristic assemblages from various regions and it solves the problem of the age of the Wealden and Utrillas facies in the region studied. The correlation between these facies and the levels associated with bauxite suggests that a biostratigraphical interpretation would be possible by further application of the method described.     

The Balance-Scale Task Revisited: A Comparison of Statistical Models for Rule-Based and Information-Integration Theories of Proportional Reasoning

We propose and test three statistical models for the analysis of children’s responses to the balance scale task, a seminal task to study proportional reasoning. We use a latent class modelling approach to formulate a rule-based latent class model (RB LCM) following from a rule-based perspective on proportional reasoning and a new statistical model, the Weighted Sum Model, following from an information-integration approach. Moreover, a hybrid LCM using item covariates is proposed, combining aspects of both a rule-based and information-integration perspective. These models are applied to two different datasets, a standard paper-and-pencil test dataset (N = 779), and a dataset collected within an online learning environment that included direct feedback, time-pressure, and a reward system (N = 808). For the paper-and-pencil dataset the RB LCM resulted in the best fit, whereas for the online dataset the hybrid LCM provided the best fit. The standard paper-and-pencil dataset yielded more evidence for distinct solution rules than the online data set in which quantitative item characteristics are more prominent in determining responses. These results shed new light on the discussion on sequential rule-based and information-integration perspectives of cognitive development.     

Antler and Body Weight Allometry in Red Deer: A Comparison of Statistical Estimators

In allometric expressions, both variables are measured with error. Such structural relationships require specific statistical techniques for precise and valid estimation of equation parameters. The relative growth pattern for antler weight and body weight was examined for 1700 red deer (Cervus elaphus L.) stags from the Harz mountain district in West Germany. Coefficients for the allometric equation were determined using several statistical estimation procedures and the results were compared and evaluated. There is evidence that the magnitude of the exponent in the allometric expression increases with the onset of sexual maturity.     

Comparison of Statistical Models for Analyzing Wheat Yield Time Series

The world''s population is predicted to exceed nine billion by 2050 and there is increasing concern about the capability of agriculture to feed such a large population. Foresight studies on food security are frequently based on crop yield trends estimated from yield time series provided by national and regional statistical agencies. Various types of statistical models have been proposed for the analysis of yield time series, but the predictive performances of these models have not yet been evaluated in detail. In this study, we present eight statistical models for analyzing yield time series and compare their ability to predict wheat yield at the national and regional scales, using data provided by the Food and Agriculture Organization of the United Nations and by the French Ministry of Agriculture. The Holt-Winters and dynamic linear models performed equally well, giving the most accurate predictions of wheat yield. However, dynamic linear models have two advantages over Holt-Winters models: they can be used to reconstruct past yield trends retrospectively and to analyze uncertainty. The results obtained with dynamic linear models indicated a stagnation of wheat yields in many countries, but the estimated rate of increase of wheat yield remained above 0.06 t ha⁻¹ year⁻¹ in several countries in Europe, Asia, Africa and America, and the estimated values were highly uncertain for several major wheat producing countries. The rate of yield increase differed considerably between French regions, suggesting that efforts to identify the main causes of yield stagnation should focus on a subnational scale.     

The Relationship Between Two Statistical Tests for the Comparison of Two Exponential Distributions

To compare two exponential distributions with or without censoring, two different statistics are often used; one is the F test proposed by COX (1953) and the other is based on the efficient score procedure. In this paper, the relationship between these tests is investigated and it is shown that the efficient score test is a large-sample approximation of the F test.     

对应用几种统计模型评价甘蔗品种稳定性的初步比较

利用广东省2009年甘蔗品种区域试验产量数据,对线性回归模型、AMMI模型和LR-PCA模型在评价甘蔗品种稳定性方面的应用进行了初步比较,结果发现,回归法计算简便、直观,AMMI模型和LR-PCA模型的分析结果则更全面、深入,而这两种模型之间仍存在着一定差异.实际操作中,在根据不同的数据资料选择相适宜的分析方法的同时,也可以采用不同的方法进行分析,通过比较选择较为合理的结果.     

锡林河流域两类植物群落土壤呼吸特征的比较

采用碱液吸收法对锡林河流域一个半干旱典型草原群落的土壤呼吸进行了5个月的野外测定,并对其与气候因子和生物量之间的关系进行了分析。另选择了锡林河岸边的一个沼泽化草甸群落作为对比来研究土壤湿度和植被类型对土壤呼吸的影响。主要结果包括:1)两个群落土壤呼吸的季节动态基本一致,均出现了两个峰值,其中草原群落和草甸群落土壤呼吸速率的变化范围分别为312.8～1 738.9 mg C·m-2·d-1 和354.6～2 235.6 mg C·m-2·d-1。草甸群落的土壤呼吸速率明显高于草原群落,它们的日平均土壤呼吸速率分别为1 349.6 mg C·m-2·d-1和785.9mg C·m-2·d-1; 2)在草原群落中,土壤呼吸速率与土壤湿度的相关性比其与温度的关系更加显著,而在草甸群落正好相反,反映出这两种气候因子在不同生境中起着不同的作用。根据土壤呼吸与气温之间的回归关系外推出2001年生长季草原群落和草甸群落的土壤呼吸量分别为142.4 g C/m2 和 236.1 g C/m2;3)在草甸群落中,地上总生物量与土壤呼吸速率之间没有显著的相关关系,而地上部活体生物量与土壤呼吸速率之间则存有很显著的幂函数关系。在草原群落中,土壤呼吸速率与地上活体生物量或地上总生物量的相关性均很弱。     

Comparison of Statistical Tests for Association between Rare Variants and Binary Traits

Genome-wide association studies have found thousands of common genetic variants associated with a wide variety of diseases and other complex traits. However, a large portion of the predicted genetic contribution to many traits remains unknown. One plausible explanation is that some of the missing variation is due to the effects of rare variants. Nonetheless, the statistical analysis of rare variants is challenging. A commonly used method is to contrast, within the same region (gene), the frequency of minor alleles at rare variants between cases and controls. However, this strategy is most useful under the assumption that the tested variants have similar effects. We previously proposed a method that can accommodate heterogeneous effects in the analysis of quantitative traits. Here we extend this method to include binary traits that can accommodate covariates. We use simulations for a variety of causal and covariate impact scenarios to compare the performance of the proposed method to standard logistic regression, C-alpha, SKAT, and EREC. We found that i) logistic regression methods perform well when the heterogeneity of the effects is not extreme and ii) SKAT and EREC have good performance under all tested scenarios but they can be computationally intensive. Consequently, it would be more computationally desirable to use a two-step strategy by (i) selecting promising genes by faster methods and ii) analyzing selected genes using SKAT/EREC. To select promising genes one can use (1) regression methods when effect heterogeneity is assumed to be low and the covariates explain a non-negligible part of trait variability, (2) C-alpha when heterogeneity is assumed to be large and covariates explain a small fraction of trait's variability and (3) the proposed trend and heterogeneity test when the heterogeneity is assumed to be non-trivial and the covariates explain a large fraction of trait variability.     

Correlations in Multi-Locus Genetic Systems: A Mathematical Model

A spin model with parallels to a multi-locus genetic model is presented which makes it possible to calculate the correlation between allelic states at any two loci in a population at equilibrium. The main features are: (1) The decay of correlation with distance may be expressed essentially as a linear combination of two exponentials, one of which dominates when the two loci are sufficiently far apart. (2) The correlation between two loci a specified distance apart is increased as the number of loci in the entire system increases. The results are compared with those of other theoretical models and discussed in the light of available experimental data. Possible ways of generalizing the model are outlined. However, additional experimental data is clearly needed to indicate the genetic relevance of work of this nature.