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, 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.

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

Handgrip strength and physical activity in frail elderly

Abstract OBJECTIVE To investigate the association between handgrip strength (HS) and physical activity in physical frailty elderly. METHOD Cross-sectional quantitative study with a sample of 203 elderly calculated based on the population estimated proportion. Tests were applied to detect cognitive impairment and assessment of physical frailty. Descriptive statistics and multivariate analysis by binary logistic regression were used, and also Student's t-test and Fisher's exact test. RESULTS A total of 99 (64.3%) elderly showed decreased handgrip strength and 90 (58.4%) elderly presented decrease in physical activity levels. There was a statistically significant difference between these two components (p=0.019), in which elderly who have decreased HS have lower levels of physical activity. For low levels of physical activity and decreased HS, there was no evidence of significant difference in the probability of the classification as frail elderly (p<0.001). CONCLUSION The components handgrip strength and physical activity are associated with the frail elderly. The joint presence of low levels of physical activity and decreased handgrip strength leads to a significantly higher probability of the elderly to be categorized as frailty.

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.

Multiparametric brainstem segmentation using a modified multivariate mixture of Gaussians

The human brainstem is a densely packed, complex but highly organised structure. It not only serves as a conduit for long projecting axons conveying motor and sensory information, but also is the location of multiple primary nuclei that control or modulate a vast array of functions, including homeostasis, consciousness, locomotion, and reflexive and emotive behaviours. Despite its importance, both in understanding normal brain function as well as neurodegenerative processes, it remains a sparsely studied structure in the neuroimaging literature. In part, this is due to the difficulties in imaging the internal architecture of the brainstem in vivo in a reliable and repeatable fashion. A modified multivariate mixture of Gaussians (mmMoG) was applied to the problem of multichannel tissue segmentation. By using quantitative magnetisation transfer and proton density maps acquired at 3 T with 0.8 mm isotropic resolution, tissue probability maps for four distinct tissue classes within the human brainstem were created. These were compared against an ex vivo fixated human brain, imaged at 0.5 mm, with excellent anatomical correspondence. These probability maps were used within SPM8 to create accurate individual subject segmentations, which were then used for further quantitative analysis. As an example, brainstem asymmetries were assessed across 34 right-handed individuals using voxel based morphometry (VBM) and tensor based morphometry (TBM), demonstrating highly significant differences within localised regions that corresponded to motor and vocalisation networks. This method may have important implications for future research into MRI biomarkers of pre-clinical neurodegenerative diseases such as Parkinson's disease.

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.