Pocket Digest Iowa Public Library Statistics, 1999

The pocket digest for public library statistics highlights pertinent information about public libraries in Iowa.

Pocket Digest Iowa Public Library Statistics, 2000

The pocket digest for public library statistics highlights pertinent information about public libraries in Iowa.

Iowa Public Library Statistics, 2004-2005

Public library statistics are taken from the annual survey. The statistics are used at the local, regional, state, and national levels to compare library performance, justify budget requests, track library data over time, assist in planning and evaluation, and provide valuable information for grants and other library programs. The annual survey collects current information from 543 public libraries about public service outlets, holdings, staffing, income, expenditures, circulation, services, and hours open. Furthermore, it helps provide a total picture of libraries on a state and nationwide basis. This report is authorized by law (Iowa Code 256.51 (H)). Each of the 50 states collects public library information according to guidelines established by the Federal State Cooperative System for public library data (FSCS). The information contained in the Iowa Public Library Statistics is based on definitions approved by FSCS. For additional information, contact Gerry Rowland, State Library, gerry.rowland@lib.state.ia.us; 1-800-248-4483.

Iowa Public Library Statistics, 2003-2004

Public library statistics are taken from the annual survey. The statistics are used at the local, regional, state, and national levels to compare library performance, justify budget requests, track library data over time, assist in planning and evaluation, and provide valuable information for grants and other library programs. The annual survey collects current information from 543 public libraries about public service outlets, holdings, staffing, income, expenditures, circulation, services, and hours open. Furthermore, it helps provide a total picture of libraries on a state and nationwide basis. This report is authorized by law (Iowa Code 256.51 (H)). Each of the 50 states collects public library information according to guidelines established by the Federal State Cooperative System for public library data (FSCS). The information contained in the Iowa Public Library Statistics is based on definitions approved by FSCS. For additional information, contact Gerry Rowland, State Library, gerry.rowland@lib.state.ia.us; 1-800-248-4483.

Meta-analysis of gene-level associations for rare variants based on single-variant statistics.

Meta-analysis of genome-wide association studies (GWASs) has led to the discoveries of many common variants associated with complex human diseases. There is a growing recognition that identifying "causal" rare variants also requires large-scale meta-analysis. The fact that association tests with rare variants are performed at the gene level rather than at the variant level poses unprecedented challenges in the meta-analysis. First, different studies may adopt different gene-level tests, so the results are not compatible. Second, gene-level tests require multivariate statistics (i.e., components of the test statistic and their covariance matrix), which are difficult to obtain. To overcome these challenges, we propose to perform gene-level tests for rare variants by combining the results of single-variant analysis (i.e., p values of association tests and effect estimates) from participating studies. This simple strategy is possible because of an insight that multivariate statistics can be recovered from single-variant statistics, together with the correlation matrix of the single-variant test statistics, which can be estimated from one of the participating studies or from a publicly available database. We show both theoretically and numerically that the proposed meta-analysis approach provides accurate control of the type I error and is as powerful as joint analysis of individual participant data. This approach accommodates any disease phenotype and any study design and produces all commonly used gene-level tests. An application to the GWAS summary results of the Genetic Investigation of ANthropometric Traits (GIANT) consortium reveals rare and low-frequency variants associated with human height. The relevant software is freely available.

Allelic proportions of 16 STR loci-including the new European Standard Set (ESS) loci-in a Swiss population sample.

Allele frequencies and forensically relevant population statistics of 16 STR loci, including the new European Standard Set (ESS) loci, were estimated from 668 unrelated individuals of Caucasian appearance living in different parts of Switzerland. The samples were amplified with a combination of the following three kits: AmpFlSTR® NGM SElect?, PowerPlex® ESI17 and PowerPlex® ESX 17. All loci were highly polymorphic and no significant departure from Hardy-Weinberg equilibrium and linkage equilibrium was detected after correction for sampling.

Aitchison Geometry for Probability and Likelihood as a new approach to mathematical statistics

The Aitchison vector space structure for the simplex is generalized to a Hilbert space structure A2(P) for distributions and likelihoods on arbitrary spaces. Centralnotations of statistics, such as Information or Likelihood, can be identified in the algebraical structure of A2(P) and their corresponding notions in compositional data analysis, such as Aitchison distance or centered log ratio transform.In this way very elaborated aspects of mathematical statistics can be understoodeasily in the light of a simple vector space structure and of compositional data analysis. E.g. combination of statistical information such as Bayesian updating,combination of likelihood and robust M-estimation functions are simple additions/perturbations in A2(Pprior). Weighting observations corresponds to a weightedaddition of the corresponding evidence.Likelihood based statistics for general exponential families turns out to have aparticularly easy interpretation in terms of A2(P). Regular exponential families formfinite dimensional linear subspaces of A2(P) and they correspond to finite dimensionalsubspaces formed by their posterior in the dual information space A2(Pprior).The Aitchison norm can identified with mean Fisher information. The closing constant itself is identified with a generalization of the cummulant function and shown to be Kullback Leiblers directed information. Fisher information is the local geometry of the manifold induced by the A2(P) derivative of the Kullback Leibler information and the space A2(P) can therefore be seen as the tangential geometry of statistical inference at the distribution P.The discussion of A2(P) valued random variables, such as estimation functionsor likelihoods, give a further interpretation of Fisher information as the expected squared norm of evidence and a scale free understanding of unbiased reasoning

Vital Statistics of Iowa, 2005

This publication is an historical recording of the most requested statistics on vital events and is a source of information that can be used in further analysis.

Vital Statistics of Iowa, 2004

This publication is an historical recording of the most requested statistics on vital events and is a source of information that can be used in further analysis.

Vital Statistics of Iowa in Brief, 2005

This publication is an historical recording of the most requested statistics on vital events and is a source of information that can be used in further analysis.

A subsampling approach to estimating the distribution of diversing statistics with application to assessing financial market risks

In this paper we propose a subsampling estimator for the distribution ofstatistics diverging at either known rates when the underlying timeseries in strictly stationary abd strong mixing. Based on our results weprovide a detailed discussion how to estimate extreme order statisticswith dependent data and present two applications to assessing financialmarket risk. Our method performs well in estimating Value at Risk andprovides a superior alternative to Hill's estimator in operationalizingSafety First portofolio selection.

Canonical correspondence analysis in social science research

The use of simple and multiple correspondence analysis is well-established in socialscience research for understanding relationships between two or more categorical variables.By contrast, canonical correspondence analysis, which is a correspondence analysis with linearrestrictions on the solution, has become one of the most popular multivariate techniques inecological research. Multivariate ecological data typically consist of frequencies of observedspecies across a set of sampling locations, as well as a set of observed environmental variablesat the same locations. In this context the principal dimensions of the biological variables aresought in a space that is constrained to be related to the environmental variables. Thisrestricted form of correspondence analysis has many uses in social science research as well,as is demonstrated in this paper. We first illustrate the result that canonical correspondenceanalysis of an indicator matrix, restricted to be related an external categorical variable, reducesto a simple correspondence analysis of a set of concatenated (or stacked ) tables. Then weshow how canonical correspondence analysis can be used to focus on, or partial out, aparticular set of response categories in sample survey data. For example, the method can beused to partial out the influence of missing responses, which usually dominate the results of amultiple correspondence analysis.

Construyendo las bases para una comparación fiable: la Encuesta Social Europea

Surveys are a valuable instrument to find out about the social and politicalreality of our context. However, the work of researchers is often limitedby a number of handicaps that are mainly two. On one hand, the samples areusually low technical quality ones and the fieldwork is not carried out inthe finest conditions. On the other hand, many surveys are not especiallydesigned to allow their comparison, a precisely appreciated operation inpolitical research. The article presents the European Social Survey andjustifies its methodological bases. The survey, promoted by the EuropeanScience Foundation and the European Commission, is born from the collectiveeffort of the scientific community with the explicit aim to establishcertain quality standards in the sample design and in the carrying out ofthe fieldwork so as to guarantee the quality of the data and allow eachcomparison between countries.