Improved estimates of cancer site-specific risks for A-bomb survivors

Pawel, D. J., Preston, D. L., Pierce, D. A. and Cologne, J. B. Improved Estimates of Cancer Site-Specific Risks for A-Bomb Survivors. Radiat. Res. 169, 87-98 (2008). Simple methods are investigated for improving summary site-specific radiogenic risk estimates. Estimates in this report are derived from cancer incidence data from the Life Span Study (LSS) cohort of A-bomb survivors that are followed up by the Radiation Effects Research Foundation (RERF). Estimates from the LSS of excess relative risk (ERR) for solid cancer sites have typically been derived separately for each site. Even though the data for this are extensive, the statistical imprecision in site-specific (organ-specific) risk estimates is substantial, and it is clear that a large portion of the site-specific variation in estimates is due to this imprecision. Empirical Bayes (EB) estimates offer a reasonable approach for moderating this variation. The simple version of EB estimates that we applied to the LSS data are weighted averages of a pooled overall estimate of ERR and separately derived site-specific estimates, with weights determined by the data. Results indicate that the EB estimates are most useful for sites such as esophageal or bladder cancer, for which the separately derived ERR estimates are less precise than for other sites.     

Estimating the educational consequences of teenage childbearing: Identification,heterogeneous effects and the value of biological relationship information

Understanding the contribution of childbearing to social disadvantages of teenage mothers requires estimates that control for unobservables and generalize to teenage mothers. Sibling-differences and Instrumental Variables (IV) are common approaches to this end. Using the “Add Health” data, which oversampled siblings, and building on IV specifications from a widely-cited study, we compare various estimates of the consequences of teenage childbearing for schooling attainment. These IV-based estimates suggest moderate to large adverse impacts of teenage births (point estimates of −0.7 years of schooling or larger). However, the IV estimates are highly sensitive to choice of instrument and model specification. Estimates based on sibling and twin differences are consistently near zero—e.g., an estimated difference of −0.1 years between a teen mother and her biological full sister who did not have a teen birth—and are estimated with sufficient precision to exclude effects larger than −0.5 years. We review concerns about sibling methods and conclude that, despite their limitations, sibling estimates should be admitted along with other evidence on the consequences of teenage childbearing. Appreciation of the sensitivity of IV estimates and their other limitations would reinforce this conclusion.     

A Penalized Multinomial Approach to Smoothed Estimation of Disease Incidence

Raw estimates of disease rates over a geographical region are frequently quite variable, even though one may reasonably expect adjacent communities to have similar true rates. Smoother estimates are obtained by incorporating a penalty into a multinomial likelihood estimation procedure. For each pair of locations, this penalty increases with the difference between the rates and decreases with the distance between the two sites. The resulting estimates have smaller mean squared error than the raw estimates. Expansions are developed which demonstrate the contributions of the smoothing constant, spatial configuration, risk population and raw estimates to the amount of smoothing. Simulations and an example involving gastric cancer data illustrate the proposed method.     

A note on the estimation of allele frequencies

A new method of obtaining allele frequency estimates is described. The method may prove useful when maximum likelihood estimates are not available. No assumptions regarding the absence of alleles are required. Errors of estimates have not been obtained, but the process seems to converge to maximum likelihood.     

Estimation of the amount of inbreeding due to subdivision of a population

In a large population which is subdivided into isolated or partially isolated subpopulations polymorphic for a gene locus, there is an excess of homozygotes due to the subdivision. This excess increases with the variance of the gene frequency. The excess can be measured by the “coefficient of inbreeding.” The aim of this paper is to estimate this coefficient, which is a function of various population parameters. We suggest several different estimates, which are the same functional form of unbiased estimates of the population parameters. These estimates are shown to be consistent. They have been compared by numerical methods among themselves and with two other estimates suggested previously.     

Maximum likelihood vs. minimum chi-square--a general comparison with applications to the estimation of recombination fractions in two-point linkage analysis.

Some relationships between the estimates of recombination fraction in two-point linkage analysis obtained by maximum likelihood, minimum chi-square, and general least squares are derived. These theoretical results are based on an approximation for the multinomial distribution. Applications (theoretical and experimental) with RFLP (restriction fragment length polymorphism) markers for a segregating F2 population are given. The minimum chi-square estimate is slightly larger than the maximum likelihood estimate. For applications, however, both estimates must be considered to be approximately equal. The least squares estimates are slightly different (larger or smaller) from these estimates.     

Bias Reduction and a Solution for Separation of Logistic Regression with Missing Covariates

Summary Logistic regression is an important statistical procedure used in many disciplines. The standard software packages for data analysis are generally equipped with this procedure where the maximum likelihood estimates of the regression coefficients are obtained iteratively. It is well known that the estimates from the analyses of small‐ or medium‐sized samples are biased. Also, in finding such estimates, often a separation is encountered in which the likelihood converges but at least one of the parameter estimates diverges to infinity. Standard approaches of finding such estimates do not take care of these problems. Moreover, the missingness in the covariates adds an extra layer of complexity to the whole process. In this article, we address these three practical issues—bias, separation, and missing covariates by means of simple adjustments. We have applied the proposed technique using real and simulated data. The proposed method always finds a solution and the estimates are less biased. A SAS macro that implements the proposed method can be obtained from the authors.     

Precision and accuracy of divergence time estimates from STR and SNPSTR variation

Inference of intraspecific population divergence patterns typically requires genetic data for molecular markers with relatively high mutation rates. Microsatellites, or short tandem repeat (STR) polymorphisms, have proven informative in many such investigations. These markers are characterized, however, by high levels of homoplasy and varying mutational properties, often leading to inaccurate inference of population divergence. A SNPSTR is a genetic system that consists of an STR polymorphism closely linked (typically < 500 bp) to one or more single-nucleotide polymorphisms (SNPs). SNPSTR systems are characterized by lower levels of homoplasy than are STR loci. Divergence time estimates based on STR variation (on the derived SNP allele background) should, therefore, be more accurate and precise. We use coalescent-based simulations in the context of several models of demographic history to compare divergence time estimates based on SNPSTR haplotype frequencies and STR allele frequencies. We demonstrate that estimates of divergence time based on STR variation on the background of a derived SNP allele are more accurate (3% to 7% bias for SNPSTR versus 11% to 20% bias for STR) and more precise than STR-based estimates, conditional on a recent SNP mutation. These results hold even for models involving complex demographic scenarios with gene flow, population expansion, and population bottlenecks. Varying the timing of the mutation event generating the SNP revealed that estimates of divergence time are sensitive to SNP age, with more recent SNPs giving more accurate and precise estimates of divergence time. However, varying both mutational properties of STR loci and SNP age demonstrated that multiple independent SNPSTR systems provide less biased estimates of divergence time. Furthermore, the combination of estimates based separately on STR and SNPSTR variation provides insight into the age of the derived SNP alleles. In light of our simulations, we interpret estimates from data for human populations.     

Nonparametric Estimates of the Asymptotic Covariance Matrix Associated with BICKEL's Estimate for Multivariate Shift Parameters

Nonparametric estimates are proposed for the asymptotic covariance matrix associated with the vector of medians of averages of pairs when estimating the shift parameter in the multivariate one sample problem. These estimates are based on density estimation and are competitors to the “natural” estimate proposed by BICKEL (1965). Weak and strong consistency of the estimates as well as asymptotic normality are presented.     

Effective population size of natural populations of Drosophila buzzatii, with a comparative evaluation of nine methods of estimation

Allozyme and microsatellite data from numerous populations of Drosophila buzzatii have been used (i) to determine to what degree N(e) varies among generations within populations, and among populations, and (ii) to evaluate the congruence of four temporal and five single-sample estimators of N(e) . Effective size of different populations varied over two orders of magnitude, most populations are not temporally stable in genetic composition, and N(e) showed large variation over generations in some populations. Short-term N(e) estimates from the temporal methods were highly correlated, but the smallest estimates were the most precise for all four methods, and the most consistent across methods. Except for one population, N(e) estimates were lower when assuming gene flow than when assuming populations that were closed. However, attempts to jointly estimate N(e) and immigration rate were of little value because the source of migrants was unknown. Correlations among the estimates from the single-sample methods generally were not significant although, as for the temporal methods, estimates were most consistent when they were small. These single-sample estimates of current N(e) are generally smaller than the short-term temporal estimates. Nevertheless, population genetic variation is not being depleted, presumably because of past or ongoing migration. A clearer picture of current and short-term effective population sizes will only follow with better knowledge of migration rates between populations. Different methods are not necessarily estimating the same N(e) , they are subject to different bias, and the biology, demography and history of the population(s) may affect different estimators differently.     

Intertribal gene flow between the Ye'cuana and Yanomama: genetic analysis of an admixed village

Genetic exchange with a neighboring village of Ye'cuana Indians had introduced two alleles, Dia and ACPa, into the Yanomama Indian Village of Borabuk. After several generations, these alleles had reached frequencies of 0.08 and 0.10, respectively. These frequencies are puzzling because they are higher in Borabuk than in the Ye'cuana village from which they were derived. Single allele estimates of ancestral proportions obtained from either of these traits are biologically unrealistic and suggest that admixture is not a good explanation for genetic variation in Borabuk. Nevertheless, multiallelic admixture models are seen to produce credible estimates of ancestral proportions and to explain a large amount of allele frequency variation in Borabuk. When these results are compared with expectations derived froma formal pedigree analysis, good agreement is seen. Comparison of single allele estimates of ancestral proportions obtained from alleles at 11 loci, with multiallelic estimates obtained from the same 11 loci and with the pedigree-derived estimates, demonstrates the superiority of the multiallelic approach.     

Angiosperm divergence times: the effect of genes, codon positions, and time constraints

An understanding of the evolution of modern terrestrial ecosystems requires an understanding of the dynamics associated with angiosperm evolution, including the timing of their origin and diversification into their extraordinary present-day diversity. Molecular estimates of angiosperm age have varied widely, and many substantially predate the Early Cretaceous fossil appearance of the group. In this study, the effect of different genes, codon positions, and chronological constraints on node ages are examined on divergence time estimates across seed plants, with a special focus on angiosperms. Penalized likelihood was used to estimate divergence times on a phylogenetic hypothesis for seed plants derived from Bayesian analysis, with branch lengths estimated with maximum likelihood. The plastid genes atpB, psaA, psbB, and rbcL were used individually and in combination, using first and second, third, and the three codon positions, including and excluding age constraints on 20 nodes derived from a critical examination of the land-plant fossil record. The optimal level of rate smoothing according to each unconstrained and constrained dataset was obtained with penalized likelihood. Tests for a molecular clock revealed significantly unclocklike rates in all datasets. Addition of fossil constraints resulted in even greater departures from constancy. Consistently with significant deviations from a clock, estimated optimal smoothing values were low, but a strict correlation between rate heterogeneity and optimal smoothing value was not found. Age estimates for nodes across the phylogeny varied, sometimes substantially, with gene and codon position. Nevertheless, estimates based on the four concatenated genes are very similar to the mean of the four individual gene estimates. For any given node, unconstrained age estimates are more variable than constrained estimates and are frequently younger than well-substantiated fossil members of the clade. Constrained estimates of ages of clades are older than unconstrained estimates and oldest fossil representatives, sometimes substantially so. Angiosperm age estimates decreased as rate smoothing increased. Whereas the range of unconstrained angiosperm age estimates spans the fossil age of the clade, the range of constrained estimates is narrower (and older) than the earliest angiosperm fossils. Results unambiguously indicate the relevance of constraints in reducing the variability of ages derived from different partitions of the data and diminishing the effect of the smoothing parameter. Constrained optimizations of divergence times and substitution rates across the phylogeny suggest appreciably different evolutionary dynamics for angiosperms and for gymnosperms. Whereas the gymnosperm crown group originated shortly after the origin of seed plants, a long time elapsed before the origin of crown group angiosperms. Although absolute age estimates of angiosperms and angiosperm clades are older than their earliest fossils, the estimated pace of phylogenetic diversification largely agrees with the rapid appearance of angiosperm lineages in stratigraphic sequences.     

Estimating age of harbor seals (Phoca vitulina) with incisor teeth and morphometrics

We compared annuli counts from sets of canine, postcanine, and incisor teeth from 450 subsistence-harvested harbor seals, submitted blind to a laboratory. Postcanine and incisor ages were highly correlated with canine age estimates ( r = 0.985 and r = 0.984, respectively), as were postcanine and incisor teeth ( r = 0.984). Age estimates from teeth of 23 known-aged seals were highly correlated; canine teeth r = 0.987; postcanine r = 0.996; incisor r = 0.992, although age for all tooth-types was underestimated for a 29-yr-old seal. Incisor estimates were variable; comparison of age estimates from two incisors/individual ( n = 42) was r = 0.992 if only high-quality age estimates were used and r = 0.705 if lower-quality estimates were used. Morphometrics and incisor-based ages of 164 live-captured seals were explored to derive a method of estimating ages of harbor seals when age estimates are needed immediately; 39 seals were of known age. Curvilinear length, mass, and axial girth were most predictive of age for females, and curvilinear length and mass for males (equations for morphometrically calculating ages are given). Morphometric-based age estimates were highly correlated with known ages ( r = 0.896) and incisor-based estimates ( r = 0.904) and discrepancies between known and morphometric-based ages were small for younger seals. Morphometric-based age estimates also accurately distinguished between young and mature individuals.     

Correcting for bias in estimation of quantitative trait loci effects

Estimates of quantitative trait loci (QTL) effects derived from complete genome scans are biased, if no assumptions are made about the distribution of QTL effects. Bias should be reduced if estimates are derived by maximum likelihood, with the QTL effects sampled from a known distribution. The parameters of the distributions of QTL effects for nine economic traits in dairy cattle were estimated from a daughter design analysis of the Israeli Holstein population including 490 marker-by-sire contrasts. A separate gamma distribution was derived for each trait. Estimates for both the α and β parameters and their SE decreased as a function of heritability. The maximum likelihood estimates derived for the individual QTL effects using the gamma distributions for each trait were regressed relative to the least squares estimates, but the regression factor decreased as a function of the least squares estimate. On simulated data, the mean of least squares estimates for effects with nominal 1% significance was more than twice the simulated values, while the mean of the maximum likelihood estimates was slightly lower than the mean of the simulated values. The coefficient of determination for the maximum likelihood estimates was five-fold the corresponding value for the least squares estimates.     

Quantitative genetic tools for insecticide resistance risk assessment: estimating the heritability of resistance

Quantitative genetic studies of resistance can provide estimates of genetic parameters not available with other types of genetic analyses. Three methods are discussed for estimating the amount of additive genetic variation in resistance to individual insecticides and subsequent estimation of the heritability (h2) of resistance. Sibling analysis and offspring-parent regression permit direct estimates of h2 by comparing the resistance phenotypes of individuals of known relatedness. Threshold trait analyses, performed on data from selection experiments, provide estimates of realized heritability. Procedures are outlined for predicting changes in resistance to insecticides based on h2 estimates. Quantitative genetic theory is examined as it relates to resistance and resistance as a quantitative trait; quantitative genetic methods also are unique in providing estimates of genetic correlations between traits. Comments are included on estimates of genetic correlation between resistance and phenotypic traits (e.g., development time) and how they may be used to predict changes in the genetic aspects of phenology that result from insecticide applications (i.e., to predict how the reproductive capacity of future generations will differ from that of the treated generation).     

Cranial variables as predictors of hominine body mass

Body mass is a key variable in investigating the evolutionary biology of the hominines (Australopithecus, Paranthropus, and Homo). It is not only closely related to life-history parameters but also provides a necessary baseline for studies of encephalization or megadonty. Body mass estimates are normally based on the postcranial skeleton. However, the majority of hominid fossils are cranio-dental remains that are unassociated with postcranial material. Only rarely can postcranial material be linked with craniodentally defined hominid taxa. This study responds to this problem by evaluating body mass estimates based on 15 cranial variables to determine whether they compare in reliability with estimates determined from postcranial variables. Results establish that some cranial variables, and particularly orbital area, orbital height, and biporionic breadth, are nearly as good mass predictors for hominoids as are some of the best postcranial predictors. For the hominines in particular, orbital height is the cranial variable which produces body mass estimates that are most in line with postcranially generated estimates. Both orbital area and biporionic breadth scale differently in the hominines than they do in the other hominoids. This difference in scaling results in unusually large estimates of body mass based on these variables for the larger-sized hominines, although the three cranial variables produce equivalent predicted masses for the smaller-bodied hominines. © 1994 Wiley-Liss, Inc.     

Comparison of three vegetation monitoring methods: Their relative utility for ecological assessment and monitoring

Vegetation cover and composition are two indicators commonly used to monitor terrestrial ecosystems. These indicators are currently quantified with a number of different methods. The interchangeability and relative benefits of different methods have been widely discussed in the literature, but there are few published comparisons that address multiple criteria across a broad range of grass- and shrub-dominated communities, while keeping sampling effort (time) approximately constant. This study compared the utility of three field sampling methods for ecological assessment and monitoring: line-point intercept, grid-point intercept, and ocular estimates. The criteria used include: (1) interchangeability of data, (2) precision, (3) cost, and (4) value of each method based on its potential to generate multiple indicators. Foliar cover by species was measured for each method in five plant communities in the Chihuahuan Desert. Line- and grid-point intercept provide similar estimates of species richness which were lower than those based on ocular estimates. There were no differences in the precision of the number of species detected. Estimates of foliar cover with line- and grid-point intercept were similar and significantly higher than those based on ocular estimates. Precision of cover estimates with line-point intercept was higher than for ocular estimates. Time requirements for the three methods were similar, despite the fact that the point-based methods included cover estimates for all canopy layers and the soil surface, while the ocular estimates included only the top canopy layer. Results suggest that point-based methods provide interchangeable data with higher precision than ocular estimates. Moreover these methods can be used to generate a much greater number of indicators that are more directly applicable to a variety of monitoring objectives, including soil erosion and wildlife habitat.     

Demography of the Pacific walrus (Odobenus rosmarus divergens): 1974–2006

Global climate change may fundamentally alter population dynamics of many species for which baseline population parameter estimates are imprecise or lacking. Historically, the Pacific walrus is thought to have been limited by harvest, but it may become limited by global warming‐induced reductions in sea ice. Loss of sea ice, on which walruses rest between foraging bouts, may reduce access to food, thus lowering vital rates. Rigorous walrus survival rate estimates do not exist, and other population parameter estimates are out of date or have well‐documented bias and imprecision. To provide useful population parameter estimates we developed a Bayesian, hidden process demographic model of walrus population dynamics from 1974 through 2006 that combined annual age‐specific harvest estimates with five population size estimates, six standing age structure estimates, and two reproductive rate estimates. Median density independent natural survival was high for juveniles (0.97) and adults (0.99), and annual density dependent vital rates rose from 0.06 to 0.11 for reproduction, 0.31 to 0.59 for survival of neonatal calves, and 0.39 to 0.85 for survival of older calves, concomitant with a population decline. This integrated population model provides a baseline for estimating changing population dynamics resulting from changing harvests or sea ice.     

Quantile regression estimates of animal population trends

Ecologists often estimate population trends of animals in time series of counts using linear regression to estimate parameters in a linear transformation of multiplicative growth models, where logarithms of rates of change in counts in time intervals are used as response variables. We present quantile regression estimates for the median (0.50) and interquartile (0.25, 0.75) relationships as an alternative to mean regression estimates for common density-dependent and density-independent population growth models. We demonstrate that the quantile regression estimates are more robust to outliers and require fewer distributional assumptions than conventional mean regression estimates and can provide information on heterogeneous rates of change ignored by mean regression. We provide quantile regression trend estimates for 2 populations of greater sage-grouse (Centrocercus urophasianus) in Wyoming, USA, and for the Crawford population of Gunnison sage-grouse (Centrocercus minimus) in southwestern Colorado, USA. Our selected Gompertz models of density dependence for both populations of greater sage-grouse had smaller negative estimates of density-dependence terms and less variation in corresponding predicted growth rates (λ) for quantile than mean regression models. In contrast, our selected Gompertz models of density dependence with piecewise linear effects of years for the Crawford population of Gunnison sage-grouse had predicted changes in λ across years from quantile regressions that varied more than those from mean regression because of heterogeneity in estimated λs that were both less and greater than mean estimates. Our results add to literature establishing that quantile regression provides better behaved estimates than mean regression when there are outlying growth rates, including those induced by adjustments for zeros in the time series of counts. The 0.25 and 0.75 quantiles bracketing the median provide robust estimates of population changes (λ) for the central 50% of time series data and provide a 50% prediction interval for a single new prediction without making parametric distributional assumptions or assuming homogeneous λs. Compared to mean estimates, our quantile regression trend estimates for greater sage-grouse indicated less variation in density-dependent λs by minimizing sensitivity to outlying values, and for Gunnison sage-grouse indicated greater variation in density-dependent λs associated with heterogeneity among quantiles.     

A review of global potentially available cropland estimates and their consequences for model‐based assessments

The world's population is growing and demand for food, feed, fiber, and fuel is increasing, placing greater demand on land and its resources for crop production. We review previously published estimates of global scale cropland availability, discuss the underlying assumptions that lead to differences between estimates, and illustrate the consequences of applying different estimates in model‐based assessments of land‐use change. The review estimates a range from 1552 to 5131 Mha, which includes 1550 Mha that is already cropland. Hence, the lowest estimates indicate that there is almost no room for cropland expansion, while the highest estimates indicate that cropland could potentially expand to over three times its current area. Differences can largely be attributed to institutional assumptions, i.e. which land covers/uses (e.g. forests or grasslands) are societally or governmentally allowed to convert to cropland, while there was little variation in biophysical assumptions. Estimates based on comparable assumptions showed a variation of up to 84%, which originated mainly from different underlying data sources. On the basis of this synthesis of the assumptions underlying these estimates, we constructed a high, a medium, and a low estimate of cropland availability that are representative of the range of estimates in the reviewed studies. We apply these estimates in a land‐change model to illustrate the consequences on cropland expansion and intensification as well as deforestation. While uncertainty in cropland availability is hardly addressed in global land‐use change assessments, the results indicate a large range of estimates with important consequences for model‐based assessments.