estimation of the false discovery proportion with unknown dependence summary large scale multiple testing with correlated test statistics arises frequently in much scientific research incorporating correlation information in approximating the false discovery proportion fdp has attracted increasing attention in recent years when the covariance matrix of test statistics is known fan and his colleagues provided an accurate approximation of the fdp under arbitrary dependence structure and some sparsity assumption however the covariance matrix is often unknown in many applications and such dependence information must be estimated before approximating the fdp the estimation accuracy can greatly affect the fdp approximation in the current paper we study theoretically the effect of unknown dependence on the testing procedure and establish a general framework such that the fdp can be well approximated the effects of unknown dependence on approximating the fdp are in the following two major aspects through estimating eigenvalues or eigenvectors and through estimating marginal variances to address the challenges in these two aspects we firstly develop general requirements on estimates of eigenvalues and eigenvectors for a good approximation of the fdp we then give conditions on the structures of covariance matrices that satisfy such requirements such dependence structures include banded or sparse covariance matrices and conditional sparse precision matrices within this framework we also consider a special example to illustrate our method where data are sampled from an approximate factor model which encompasses most practical situations we provide a good approximation of the fdp via exploiting this specific dependence structure the results are further generalized to the situation where the multivariate normality assumption is relaxed our results are demonstrated by simulation studies and some real data applications

correlated binary regression using a quadratic exponential model summary a model of quadratic exponential form is parameterized in terms of marginal means and pairwise correlations for the regression analysis of correlated binary data pseudo maximum likelihood methods using a special case termed the multiplicative model are proposed but are noted to be computationally unattractive if the blocks of correlated responses are at all large on the other hand score estimating functions for mean and correlation parameters are shown to be of a particularly simple form under the quadratic exponential family special cases of such estimating functions having attractive computational properties are identified and illustrated

loglinear multidimensional irt models for polytomously scored items a loglinear irt model is proposed that relates polytomously scored item responses to a multidimensional latent space the analyst may specify a response function for each response indicating which latent abilities are necessary to arrive at that response each item may have a different number of response categories so that free response items are more easily analyzed conditional maximum likelihood estimates are derived and the models may be tested generally or against alternative loglinear irt models

brill noether theory of curves on enriques surfaces i the positive cone and gonality we study the existence of linear series on curves lying on an enriques surface and general in their complete linear system using a method that works also below the bogomolov reider range we compute in all cases the gonality of such curves we also give a new result about the positive cone of line bundles on an enriques surface and we show how this relates to the gonality

innovated higher criticism for detecting sparse signals in correlated noise higher criticism is a method for detecting signals that are both sparse and weak although first proposed in cases where the noise variables are independent higher criticism also has reasonable performance in settings where those variables are correlated in this paper we show that by exploiting the nature of the correlation performance can be improved by using a modified approach which exploits the potential advantages that correlation has to offer indeed it turns out that the case of independent noise is the most difficult of all from a statistical viewpoint and that more accurate signal detection for a given level of signal sparsity and strength can be obtained when correlation is present we characterize the advantages of correlation by showing how to incorporate them into the definition of an optimal detection boundary the boundary has particularly attractive properties when correlation decays at a polynomial rate or the correlation matrix is toeplitz

on sectional genus of quasi polarized 3 folds let x be a smooth projective variety over c and l a nef big resp ample divisor on x then x l is called a quasi polarized resp polarized manifold then we conjecture that g l q x where g l is the sectional genus of l and q x dim h1 ox is the irregularity of x in general it is unknown whether this conjecture is true or not even in the case of dim x 2 for example this conjecture is true if dim x 2 and dim ho l 0 but it is unknown if dimx 3 and dimh l 0 in this paper we prove g l q x if dimx 3 and dimh l 2 furthermore we classify polarized manifolds x l with dim x 3 dim h l 3 and g l q x

exact meta analysis approach for discrete data and its application to 2 2 tables with rare events this article proposes a general exact meta analysis approach for synthesizing inferences from multiple studies of discrete data the approach combines the p value functions also known as significance functions associated with the exact tests from individual studies it encompasses a broad class of exact meta analysis methods as it permits broad choices for the combining elements such as tests used in individual studies and any parameter of interest the approach yields statements that explicitly account for the impact of individual studies on the overall inference in terms of efficiency power and the type i error rate those statements also give rises to empirical methods for further enhancing the combined inference although the proposed approach is for general discrete settings for convenience it is illustrated throughout using the setting of meta analysis of multiple 2 2 tables in the context of rare events data such as observing few zero or zero total i e zero events in both arms out

vector bundles of rank 2 and linear systems on algebraic surfaces let s be a smooth complex algebraic surface and let l be a divisor on s it is well known that the linear system il ksi where ks is the canonical divisor plays an important role in understanding the geometry of s several authors see for example 8 11 studied various properties of this system our paper treats the same subject but the point of view is different from the works mentioned above the philosophy underlying our approach is almost classical points on s more generally effective 0 cycles in special position with respect to il ksi see definition below contain information about the geometry of s this point of view was recently revived in 5 also 10 in fact this paper contains the technique of going from the effective 0 cycle z in special position with respect to il ksi to the geometry of s for the sake of completeness we give a definition and state a theorem which can be found in 5 10

a bottom up approach to testing hypotheses that have a branching tree dependence structure with error rate control modern statistical analyses often involve testing large numbers of hypotheses in many situations these hypotheses may have an underlying tree structure that both helps determine the order that te

likelihood inference on the underlying structure of irt models the assumptions underlying item response theory irt models may be expressed as a set of equality and inequality constraints on the parameters of a latent class model it is well known that the same assumptions imply that the parameters of the manifest distribution have to satisfy a more complicated set of inequality constraints which however are necessary but not sufficient in this paper we describe how the theory for likelihood based inference under equality and inequality constraints may be used to test the underlying assumptions of irt models it turns out that the analysis based directly on the latent structure is simpler and more flexible in particular we indicate how several interesting extensions of the rasch model may be obtained by partial relaxation of the basic constraints an application to a data set provided by educational testing service is used to illustrate the approach

covers of algebraic varieties iii the discriminant of a cover of degree 4 and the trigonal construction in c e a general structure theorem for gorenstein covers of degrree d has been proved such a result has been used for characterizing covers of degree 3 4 and 5 see c e and cs respectively of algebraic varieties more precisely in section 4 resp 3 of c e it is proved that the total space x of each gorenstein cover e x y of degree 4 esp 3 is obta ned inside a suit bl p ojective bundle 7r 11 y of rank 2 resp 1 as the b se locus of a pencil relativ conics resp

confidence distributions and a unifying framework for meta analysis this article develops a unifying framework as well as robust meta analysis approaches for combining studies from independent sources the device used in this combination is a confidence distribution cd which uses a distribution function instead of a point point estimator or an interval confidence interval to estimate a parameter of interest a cd function contains a wealth of information for inferences and it is a useful device for combining studies from different sources the proposed combining framework not only unifies most existing meta analysis approaches but also leads to development of new approaches we illustrate in this article that this combining framework can include both the classical methods of combining p values and modern model based meta analysis approaches we also develop under the unifying framework two new robust meta analysis approaches with supporting asymptotic theory in one approach each study size goes to infinity and in the other approach the number of studies

marginal maximum likelihood estimation of item parameters application of an em algorithm maximum likelihood estimation of item parameters in the marginal distribution integrating over the distribution of ability becomes practical when computing procedures based on an em algorithm are used by characterizing the ability distribution empirically arbitrary assumptions about its form are avoided the em procedure is shown to apply to general item response models lacking simple sufficient statistics for ability this includes models with more than one latent dimension

the dutch identity a new tool for the study of item response models the dutch identity is a useful way to reexpress the basic equations of item response models that relate the manifest probabilities to the item response functions irfs and the latent trait distribution the identity may be exploited in several ways for example a to suggest how item response models behave for large numbers of items they are approximate submodels of second order loglinear models for 2 j tables b to suggest new ways to assess the dimensionality of the latent trait principle components analysis of matrices composed of second order interactions from loglinear models c to give insight into the structure of latent class models and d to illuminate the problem of identifying the irfs and the latent trait distribution from sample data

on the adjunction mapping of very ample vector bundles of corank one let e be a very ample vector bundle of rank n 1 over a smooth complex projective variety x of dimension n 3 the structure of x e being known when k x det e 0 we investigate the structure of the adjunction mapping when 0 k x det e n

on holland s dutch identity conjecture the manifest probabilities of observed examinee response patterns resulting from marginalization with respect to the latent ability distribution produce the marginal likelihood function in item response theory under the conditions that the posterior distribution of examinee ability given some test response pattern is normal and the item logit functions are linear holland 1990a gives a quadratic form for the log manifest probabilities by using the dutch identity further holland conjectures that this special quadratic form is a limiting one for all smooth unidimensional item response models as test length tends to infinity the purpose of this paper is to give three counterexamples to demonstrate that holland s dutch identity conjecture does not hold in general the counterexamples suggest that only under strong assumptions can it be true that the limits of log manifest probabilities are quadratic three propositions giving sets of such strong conditions are given

a class of regression models for multivariate categorical responses summary when data composed of several categorical responses together with categorical or continuous predictors are observed it is often useful to relate the response probabilities to the predictors via a generalised linear model with a composite link function this paper discusses a class of link functions that lie between the two extremes of the multivariate logistic transform of mccullagh nelder 1989 and the log linear decomposition of contingency table analysis the models derived from these link functions are shown to inherit various desirable properties of both the multivariate logistic regression models and the log linear regression models a computational scheme for implementing these models is derived and they are demonstrated to be computationally more tractable than the multivariate logistic regression models their application is illustrated in a numerical example

gauss composition for p1 and the universal jacobian of the hurwitz space of double covers abstract in this paper we give an explicit description of the moduli space of line bundles on hyperelliptic curves including singular curves we study the universal jacobian j 2 g n of degree n line bundles over the hurwitz stack of double covers of p 1 by a curve of genus g our main results are the construction of a smooth irreducible universally closed but not separated moduli compactification j bd 2 g n of j 2 g n whose points we describe simply and explicitly as sections of certain vector bundles on p 1 a description of the global geometry and moduli properties of these stacks and a computation of the picard groups of j bd 2 g n and j 2 g n in the cases when n g is even an important ingredient of our work is the parametrization of line bundles on double covers by binary quadratic forms this parametrization generalizes the classical number theoretic correspondence between ideal classes of quadratic rings and integral binary quadratic forms which in particular gives the group law on integral binary quadratic forms first discovered by gauss

marginal regression analysis of a multivariate binary response we propose the use of the mean parameter for regression analysis of a multivariate binary response we model the association using dependence ratios defined in terms of the mean parameter the components of which are the joint success probabilities of all orders this permits flexible modelling of higher order associations using maximum likelihood estimation we reanalyse two data sets one with variable cluster size and the other a longitudinal data set with constant cluster size

characterizing the manifest probability distributions of three latent trait models for accuracy and response time in this paper we study the statistical relations between three latent trait models for accuracies and response times the hierarchical model hm of van der linden psychometrika 72 3 287 308 2007 the signed residual time model sm proposed by maris and van der maas psychometrika 77 4 615 633 2012 and the drift diffusion model dm as proposed by tuerlinckx and de boeck psychometrika 70 4 629 650 2005 one important distinction between these models is that the hm and the dm either assume or imply that accuracies and response times are independent given the latent trait variables while the sm does not in this paper we investigate the impact of this conditional independence property or a lack thereof on the manifest probability distribution for accuracies and response times we will find that the manifest distributions of the latent trait models share several important features such as the dependency between accuracy and response time but we also find important differences such as in what function of response time is being modeled our method for characterizing the manifest probability distributions is related to the dutch identity holland in psychometrika 55 6 5 18 1990

a bayesian random effects model for testlets standard item response theory irt models fit to dichotomous examination responses ignore the fact that sets of items testlets often come from a single common stimuli e g a reading comprehension passage in this setting all items given to an examinee are unlikely to be conditionally independent given examinee proficiency models that assume conditional independence will overestimate the precision with which examinee proficiency is measured overstatement of precision may lead to inaccurate inferences such as prematurely ending an examination in which the stopping rule is based on the estimated standard error of examinee proficiency e g an adaptive test to model examinations that may be a mixture of independent items and testlets we modified one standard irt model to include an additional random effect for items nested within the same testlet we use a bayesian framework to facilitate posterior inference via a data augmented gibbs sampler dags tanner wong 1987 the modified and standard irt models are both applied to a data set from a disclosed form of the sat we also provide simulation results that indicates that the degree of precision bias is a function of the variability of the testlet effects as well as the testlet design

classification of smooth congruences of low degree we give a complete classification of smooth congruences i e surfaces in the grassmann variety of lines in p 3c identified with a smooth quadric in p5 of degree at most 8 by studying which surfaces of p5can lie in a smooth quadric and proving their existence we present their ideal sheaf as a quotient of natural bundles in the grassmannian what provides a perfect knowledge of its cohomology for example postulation or linear normality as well as many information on the hilbert scheme of these families such as dimension smoothness unirationality and thus irreducibility and in some cases rationality

a likelihood based method for analysing longitudinal binary responses summary in this paper we discuss a likelihood based method for analysing correlated binary responses based on a multivariate model it is related to the pseudo maximum likelihood approach suggested recently by zhao prentice 1990 their parameterization results in a simple pairwise model in which the association between responses is modelled in terms of correlations while the present paper uses conditional log odds ratios with this approach higher order associations can be incorporated in a natural way one important advantage of this parameterization is that the maximum likelihood estimates of the marginal mean parameters are robust to misspecification of the time dependence we describe an iterative two stage procedure for obtaining the maximum likelihood estimates two examples are presented to illustrate this methodology

the distribution of bidegrees of smooth surfaces in gr 1 p3 the study of algebraic surfaces in gr 1 p3 the grassmann variety parametrising lines in projective three space was a popular one for algebraic geometers of the late nineteenth and early twentieth centuries calling them line congruences researchers such as kummer fano roth and many others published many papers on the topic classifying congruences and studying their invariants since that time the field has lain dormant until very recently the classical geometers identified two numbers associated with a given congruence the order and the class thinking of a congruence as a two dimensional family of lines the order is the number of lines in the family passing through a general point in p3 and the class the number of lines in the family contained in a general plane together these two numbers make up the bidegree of the congruence in modern terms the bidegree gives the class of the congruence in the chow ring of gr 1 p3 in this paper we consider the question for what values of a and b does there exist or not exist a smooth congruence of bidegree a b in particular we try to find restrictions on the bidegree using an approach suggested by dolgachev and reider in 8 this approach is to study the restriction of the universal bundle g of gr 1 p3 which appears in the exact sequence

the generalized higher criticism for testing snp set effects in genetic association studies abstractit is of substantial interest to study the effects of genes genetic pathways and networks on the risk of complex diseases these genetic constructs each contain multiple snps which are often correlated and function jointly and might be large in number however only a sparse subset of snps in a genetic construct is generally associated with the disease of interest in this article we propose the generalized higher criticism ghc to test for the association between an snp set and a disease outcome the higher criticism is a test traditionally used in high dimensional signal detection settings when marginal test statistics are independent and the number of parameters is very large however these assumptions do not always hold in genetic association studies due to linkage disequilibrium among snps and the finite number of snps in an snp set in each genetic construct the proposed ghc overcomes the limitations of the higher criticism by allowing for arbitrary correlation structures among the s

a dynamic generalization of the rasch model in the present paper a model for describing dynamic processes is constructed by combining the common rasch model with the concept of structurally incomplete designs this is accomplished by mapping each item on a collection of virtual items one of which is assumed to be presented to the respondent dependent on the preceding responses and or the feedback obtained it is shown that in the case of subject control no unique conditional maximum likelihood cml estimates exist whereas marginal maximum likelihood mml proves a suitable estimation procedure a hierarchical family of dynamic models is presented and it is shown how to test special cases against more general ones furthermore it is shown that the model presented is a generalization of a class of mathematical learning models known as luce s beta model

adjusting for information inflation due to local dependency in moderately large item clusters when multiple items are clustered around a reading passage the local independence assumption in item response theory is often violated the amount of information contained in an item cluster is usually overestimated if violation of local independence is ignored and items are treated as locally independent when in fact they are not in this article we provide a general method that adjusts for the inflation of information associated with a test containing item clusters a computational scheme was presented for the evaluation of the factor of adjustment for clusters in the restrictive case of two items per cluster and the general case of more than two items per cluster the methodology was motivated by a study of the naep reading assessment we present a simulated study along with an analysis of a naep data set

smooth projective varieties with extremal or next to extremal curvilinear secant subspaces we intend to give a classification of smooth nondegenerate projective varieties admitting extremal or next to extremal curvilinear secant subspaces gruson lazarsfeld and peskine classified all projective integral curves with extremal secant lines on the other hand if a locally cohen macaulay variety x p n e of degree d meets with a linear subspace l of dimension at finite points then length x l d e as a finite scheme a linear subspace l for which the above length attains maximal possible value is called an extremal secant subspace and such l for which length x l d e 1 is called a next to extremal secant subspace in this paper we show that if a smooth variety x of degree d 6 has extremal or next to extremal curvilinear secant subspaces then it is either del pezzo or a scroll over a curve of genus g 1 this generalizes the results of gruson lazarsfeld and peskine 1983 for curves and the work of m a bertin 2002 who classified smooth higher dimensional varieties with extremal secant lines this is also motivated and closely related to establishing an upper bound for the castelnuovo mumford regularity and giving a classification of the varieties on the boundary

locally dependent latent trait model and the dutch identity revisited in this paper we propose a class of locally dependent latent trait models for responses to psychological and educational tests typically item response models treat an individual s multiple response to stimuli as conditional independent given the individual s latent trait in this paper instead the focus is on models based on a family of conditional distributions or kernel that describes joint multiple item responses as a function of student latent trait not assuming conditional independence specifically we examine a hybrid kernel which comprises a component for one way item response functions and a component for conditional associations between items given latent traits the class of models allows the extension of item response theory to cover some new and innovative applications in psychological and educational research an em algorithm for marginal maximum likelihood of the hybrid kernel model is proposed furthermore we delineate the relationship of the class of locally dependent models and the log linear model by revisiting the dutch identity holland 1990

simultaneously modeling joint and marginal distributions of multivariate categorical responses abstract we discuss model fitting methods for analyzing simultaneously the joint and marginal distributions of multivariate categorical responses the models are members of a broad class of generalized logit and loglinear models we fit them by improving a maximum likelihood algorithm that uses lagrange s method of undetermined multipliers and a newton raphson iterative scheme we also discuss goodness of fit tests and adjusted residuals and give asymptotic distributions of model parameter estimators for this class of models inferences are equivalent for poisson and multinomial sampling assumptions simultaneous models for joint and marginal distributions may be useful in a variety of applications including studies dealing with longitudinal data multiple indicators in opinion research cross over designs social mobility and inter rater agreement the models are illustrated for one such application using data from a recent general social survey regarding opinions about various types of government s

a new item response theory modeling approach with applications to unidimensionality assessment and ability estimation using an infinite item test framework it is argued that the usual assumption of local independence be replaced by a weaker assumption essential independence a fortiori the usual assumption of unidimensionality is replaced by a weaker and arguably more appropriatestatistically testable assumption of essential unidimennsionality essential unidimennsionnality implies the existence of a unique unidimensional latent ability essential unidimensionality is equivalent to the consistent estimation of this latnet ability in an ordinal scaling sense using anybalanced empirical scaling a variation of this estimation approach allows consistent estimation of ability on the given latent ability scale

conjunctive item response theory kernels conjunctive item response models are introduced such that a sufficient statistics for latent traits are not necessarily additive in item scores b items are not necessarily locally independent and c existing compensatory additive item response models including the binomial rasch logistic and general locally independent model are special cases simple estimates and hypothesis tests for conjunctive models are introduced and evaluated as well conjunctive models are also identified with cognitive models that assume the existence of several individually necessary component processes for a global ability it is concluded that conjunctive models and methods may show promise for constructing improved tests and uncovering conjunctive cognitive structure it is also concluded that conjunctive item response theory may help to clarify the relationships between local dependence multidimensionality and item response function form

copula functions for residual dependency most item response theory models are not robust to violations of conditional independence however several modeling approaches e g conditioning on other responses additional random effects exist that try to incorporate local item dependencies but they have some drawbacks such as the nonreproducibility of marginal probabilities and resulting interpretation problems in this paper a new class of models making use of copulas to deal with local item dependencies is introduced these models belong to the bigger class of marginal models in which margins and association structure are modeled separately it is shown how this approach overcomes some of the problems associated with other local item dependency models

higher criticism for detecting sparse heterogeneous mixtures higher criticism or second level significance testing is a multiplecomparisons concept mentioned in passing by tukey it concerns a situation where there are many independent tests of significance and one is interested in rejecting the joint null hypothesis tukey suggested comparing the fraction of observed significances at a given level to the expected fraction under the joint null in fact he suggested standardizing the difference of the two quantities and forming a z score the resulting z score tests the significance of the body of significance tests we consider a generalization where we maximize this z score over a range of significance levels 0 0 we are able to show that the resulting higher criticism statistic is effective at resolving a very subtle testing problem testing whether n normal means are all zero versus the alternative that a small fraction is nonzero the subtlety of this sparse normal means testing problem can be seen from work of ingster and jin who studied such problems in great detail in their studies they identified an interesting range of cases where the small fraction of nonzero means is so small that the alternative hypothesis exhibits little noticeable effect on the distribution of the p values either for the bulk of the tests or for the few most highly significant tests in this range when the amplitude of nonzero means is calibrated with the fraction of nonzero means the likelihood ratio test for a precisely specified alternative would still succeed in separating the two hypotheses we show that the higher criticism is successful throughout the same region of amplitude sparsity where the likelihood ratio test

examples of smooth non general type surfaces in p4 smooth projective varieties with small invariants have received renewed interest in recent years primarily due to the fine study of the adjunction mapping now through the effort of several mathematicians a complete classification of smooth surfaces in bbb p 4 has been worked out up to degree 10 and a partial one is available in degree 11 on the other side recently ellingsrud and peskine have proved hartshorne s conjecture that there are only finitely many families of smooth surfaces in bbb p 4 not of general type it is believed that the degree of the smooth non general type surfaces in bbb p 4 should be less than or equal to 15 the aim of this paper is to provide a series of examples of smooth surfaces in bbb p 4 not of general type in degrees varying from 12 up to 14 and to describe their geometry by using mainly syzygies and liaison techniques we construct the following families of surfaces begin enumerate item minimal proper elliptic surfaces of degree 12 and sectional genus pi 13 item two types of non minimal proper elliptic surfaces of degree 12 and sectional genus pi 14 item non minimal k3 surfaces of degree 13 and sectional genus 16 and item non minimal k3 surfaces of degree 14 and sectional genus 19 1991 mathematics subject classification 14m07 14j25 14j26 14j28 14c05

two sample test of high dimensional means under dependence summary the paper considers in the high dimensional setting a canonical testing problem in multivariate analysis namely testing the equality of two mean vectors we introduce a new test statistic that is based on a linear transformation of the data by the precision matrix which incorporates the correlations between the variables the limiting null distribution of the test statistic and the power of the test are analysed it is shown that the test is particularly powerful against sparse alternatives and enjoys certain optimality a simulation study is carried out to examine the numerical performance of the test and to compare it with other tests given in the literature the results show that the test proposed significantly outperforms those tests in a range of settings

an unexpected encounter with cauchy and levy the cauchy distribution is usually presented as a mathematical curiosity an exception to the law of large numbers or even as an evil distribution in some introductory courses it therefore surprised us when drton and xiao bernoulli22 2016 38 59 proved the following result for m 2 and conjectured it for m ge3 let x x 1 ldots x m and y y 1 ldots y m be i i d mathrm n 0 sigma where sigma sigma ij ge0 is an m times m and arbitrary covariance matrix with sigma jj 0 for all 1 leq j leq m then z sum j 1 m w j frac x j y j sim operatorname cauchy 0 1 as long as vec w w 1 ldots w m is independent of x y w j ge0 j 1 ldots m and sum j 1 m w j 1 in this note we present an elementary proof of this conjecture for any m geq2 by linking z to a geometric characterization of operatorname cauchy 0 1 given in willams ann math stat 40 1969 1083 1085 this general result is essential to the large sample behavior of wald tests in many applications such as factor models and contingency tables it also leads to other unexpected results such as sum i 1 m sum j 1 m frac w i w j sigma ij x i x j sim mbox levy 0 1 this generalizes the super cauchy phenomenon that the average of m i i d standard levy variables i e inverse chi squared variables with one degree of freedom has the same distribution as that of a single standard levy variable multiplied by m which is obtained by taking w j 1 m and sigma to be the identity matrix

the role of collateral information about examinees in item parameter estimation standard procedures for estimating item parameters in item response theory irt ignore collateral information that may be available about examinees such as their standing on demographic and educational variables this paper describes circumstances under which collateral information about examineesmay be used to make inferences about item parameters more precise and circumstances under which itmust be used to obtain correct inferences

modular compactifications of the space of marked trigonal curves abstract we construct a sequence of modular compactifications of the space of marked trigonal curves by allowing the branch points to coincide to a given extent beginning with the standard admissible cover compactification the sequence first proceeds through contractions of the boundary divisors and then through flips of the so called maroni strata culminating in a fano model for even genera and a fano fibration for odd genera while the sequence of divisorial contractions arises from a more general construction the sequence of flips uses the particular geometry of triple covers we explicitly describe the mori chamber decomposition given by this sequence of flips

three divisible families of skew lines on a smooth projective quintic we give an example of a family of 15 skew lines on a quintic such that its class is divisible by 3 we study properties of the codes given by arrangements of disjoint lines on quintics

on quintic surfaces of general type the study of quintic surfaces is of special interest because 5 is the lowest degree of surfaces of general type the aim of this paper is to give a classification of the quintic surfaces of general type over the complex number field c we show that if s is an irreducible quintic surface of general type then it must be normal and it has only elliptic double or triple points as essential singularities then we classify all such surfaces in terms of the classification of the elliptic double and triple points we give many examples in order to verify the existence of various types of quintic surfaces of general type we also make a study of the double or triple covering of a quintic surface over p2 obtained by the projection from a triple or double point on the surface this reduces the classification of the surfaces to the classification of branch loci satisfying certain conditions finally we derive some properties of the hilbert schemes of some types of quintic surfaces

cauchy combination test a powerful test with analytic p value calculation under arbitrary dependency structures abstract combining individual p values to aggregate multiple small effects has a long standing interest in statistics dating back to the classic fisher s combination test in modern large scale da

multivariate regression analyses for categorical data summary it is common to observe a vector of discrete and or continuous responses in scientific problems where the objective is to characterize the dependence of each response on explanatory variables and to account for the association between the outcomes the response vector can comprise repeated observations on one variable as in longitudinal studies or genetic studies of families or can include observations for different variables this paper discusses a class of models for the marginal expectations of each response and for pairwise associations the marginal models are contrasted with log linear models two generalized estimating equation approaches are compared for parameter estimation the first focuses on the regression parameters the second simultaneously estimates the regression and association parameters the robustness and efficiency of each is discussed the methods are illustrated with analyses of two data sets from public health research